This document summarizes the key findings of a survey conducted by Unisphere Research on the state of database administration. The survey found that:
1) While new technologies like Hadoop and NoSQL are gaining adoption, traditional relational database management systems (RDBMS) like Oracle and Microsoft SQL Server still form the foundation of information infrastructure for most organizations.
2) Database administrators (DBAs) are responsible for managing multiple database instances from different vendors, and the number of databases each DBA oversees is growing. DBAs are also taking on responsibility for administering new non-relational technologies like Hadoop and NoSQL.
3) Most companies use more than one database platform primarily to support different applications and user
The document provides an introduction to the e-book which discusses how advanced analytics and big data are transforming businesses. It notes that the amount of data in the world is doubling every two years and analytics on this data is growing. New platforms and technologies now make it possible to economically process huge datasets and lower the cost and increase the speed of analysis.
The e-book contains essays from data analytics experts organized into five sections: business change, technology platforms, industry examples, research, and marketing. The technology platforms section focuses on tools that make advanced analytics affordable for organizations of all sizes. The introduction aims to provide insights into how analytics are evolving across different fields and industries through these expert perspectives.
Hadoop: Data Storage Locker or Agile Analytics Platform? It’s Up to You.Jennifer Walker
The document discusses how Hadoop is often used primarily as a data storage system rather than an agile analytics platform. It argues that for Hadoop to enable productive analytics, companies need to transform Hadoop into a system that allows for iterative exploration of diverse data sources through intuitive interfaces that leverage machine learning. This requires addressing challenges such as a lack of data understanding, scarce expertise, and time-consuming data preparation processes. Adopting platforms that provide self-service access and leverage business context can help democratize data access and analysis.
The document discusses strategies for organizations to better manage big data when resources are limited. It recommends identifying unused data in the data warehouse in order to reduce costs by moving that data to cheaper platforms like Hadoop. Organizations can save millions by offloading data that is not frequently queried but must be retained for regulatory reasons. The document also suggests purging data that is not needed at all to further reduce storage and management costs. Proper classification and placement of data onto platforms suited to its usage level and type, such as Hadoop for less critical datasets, can help organizations get more value from their data with fewer resources.
This white paper will present the opportunities laid down by
data lake and advanced analytics, as well as, the challenges
in integrating, mining and analyzing the data collected from
these sources. It goes over the important characteristics of
the data lake architecture and Data and Analytics as a
Service (DAaaS) model. It also delves into the features of a
successful data lake and its optimal designing. It goes over
data, applications, and analytics that are strung together to
speed-up the insight brewing process for industry’s
improvements with the help of a powerful architecture for
mining and analyzing unstructured data – data lake.
How 3 trends are shaping analytics and data management Abhishek Sood
The document discusses 3 major shifts in the modern data environment that IT leaders need to understand:
1. Thinking in terms of data pipelines rather than single data buckets, as data now resides in multiple systems and needs to be integrated and accessed across these systems.
2. Using need-based data landing zones where cloud application data is integrated based on what is necessary to make the data useful, rather than automatically integrating all cloud data into the data warehouse.
3. Transforming the IT role from data protector to data mentor by embracing self-service analytics and redefining governance to be more open, while educating business users on analysis and effective data use.
Decision Ready Data: Power Your Analytics with Great DataDLT Solutions
Murthy Mathiprakasam, Principal Product Marketing Manager at Informatica, shares how to power your analytics with great data from the 2015 Informatica Government Summit.
This document discusses how Oracle Data Integrator 12c (ODI12c) can bridge the gap between big data and enterprise data. It allows users to integrate both types of data through a single unified tool. Key features include application adapters for Hadoop that enable native Hadoop integration, loading and transforming of big data, and integrated platforms and real-time analytics to simplify, optimize, and extend the value of big data.
Hadoop is an open source platform for storing and processing large amounts of data across distributed systems. The document evaluates nine major Hadoop solutions based on 32 criteria. It finds that Hadoop is becoming widely adopted in enterprises due to its ability to cost-effectively manage both structured and unstructured data at large scales. While Hadoop itself is free to use, many vendors add proprietary features and support to their commercial distributions, creating competition in the growing Hadoop market. The evaluation identifies leaders and strong performers among the solutions for meeting enterprise data and analytics needs.
The document provides an introduction to the e-book which discusses how advanced analytics and big data are transforming businesses. It notes that the amount of data in the world is doubling every two years and analytics on this data is growing. New platforms and technologies now make it possible to economically process huge datasets and lower the cost and increase the speed of analysis.
The e-book contains essays from data analytics experts organized into five sections: business change, technology platforms, industry examples, research, and marketing. The technology platforms section focuses on tools that make advanced analytics affordable for organizations of all sizes. The introduction aims to provide insights into how analytics are evolving across different fields and industries through these expert perspectives.
Hadoop: Data Storage Locker or Agile Analytics Platform? It’s Up to You.Jennifer Walker
The document discusses how Hadoop is often used primarily as a data storage system rather than an agile analytics platform. It argues that for Hadoop to enable productive analytics, companies need to transform Hadoop into a system that allows for iterative exploration of diverse data sources through intuitive interfaces that leverage machine learning. This requires addressing challenges such as a lack of data understanding, scarce expertise, and time-consuming data preparation processes. Adopting platforms that provide self-service access and leverage business context can help democratize data access and analysis.
The document discusses strategies for organizations to better manage big data when resources are limited. It recommends identifying unused data in the data warehouse in order to reduce costs by moving that data to cheaper platforms like Hadoop. Organizations can save millions by offloading data that is not frequently queried but must be retained for regulatory reasons. The document also suggests purging data that is not needed at all to further reduce storage and management costs. Proper classification and placement of data onto platforms suited to its usage level and type, such as Hadoop for less critical datasets, can help organizations get more value from their data with fewer resources.
This white paper will present the opportunities laid down by
data lake and advanced analytics, as well as, the challenges
in integrating, mining and analyzing the data collected from
these sources. It goes over the important characteristics of
the data lake architecture and Data and Analytics as a
Service (DAaaS) model. It also delves into the features of a
successful data lake and its optimal designing. It goes over
data, applications, and analytics that are strung together to
speed-up the insight brewing process for industry’s
improvements with the help of a powerful architecture for
mining and analyzing unstructured data – data lake.
How 3 trends are shaping analytics and data management Abhishek Sood
The document discusses 3 major shifts in the modern data environment that IT leaders need to understand:
1. Thinking in terms of data pipelines rather than single data buckets, as data now resides in multiple systems and needs to be integrated and accessed across these systems.
2. Using need-based data landing zones where cloud application data is integrated based on what is necessary to make the data useful, rather than automatically integrating all cloud data into the data warehouse.
3. Transforming the IT role from data protector to data mentor by embracing self-service analytics and redefining governance to be more open, while educating business users on analysis and effective data use.
Decision Ready Data: Power Your Analytics with Great DataDLT Solutions
Murthy Mathiprakasam, Principal Product Marketing Manager at Informatica, shares how to power your analytics with great data from the 2015 Informatica Government Summit.
This document discusses how Oracle Data Integrator 12c (ODI12c) can bridge the gap between big data and enterprise data. It allows users to integrate both types of data through a single unified tool. Key features include application adapters for Hadoop that enable native Hadoop integration, loading and transforming of big data, and integrated platforms and real-time analytics to simplify, optimize, and extend the value of big data.
Hadoop is an open source platform for storing and processing large amounts of data across distributed systems. The document evaluates nine major Hadoop solutions based on 32 criteria. It finds that Hadoop is becoming widely adopted in enterprises due to its ability to cost-effectively manage both structured and unstructured data at large scales. While Hadoop itself is free to use, many vendors add proprietary features and support to their commercial distributions, creating competition in the growing Hadoop market. The evaluation identifies leaders and strong performers among the solutions for meeting enterprise data and analytics needs.
Overview of mit sloan case study on ge data and analytics initiative titled g...Gregg Barrett
GE collects sensor data from industrial equipment to analyze equipment performance and predict failures. It created a "data lake" to integrate raw flight data from 3.4 million flights with other data sources. This allows data scientists to identify issues reducing equipment uptime for customers. However, GE faces challenges in finding qualified analytics talent and establishing effective data governance as it scales its data and analytics efforts.
Making Sense of NoSQL and Big Data Amidst High ExpectationsRackspace
1) There is a lot of hype around NoSQL and Big Data technologies but they provide value for specific problems involving large, varied datasets with high rates of change.
2) NoSQL databases are useful for problems that don't require a relational data model and involve huge datasets, while SQL databases remain critical for transaction processing and maintaining relationships between structured data.
3) Organizations should choose technologies based on their specific business requirements and understand each technology's strengths rather than favoring "cool" technologies.
1. A data lake is a storage repository that holds vast amounts of raw data in its native format until it is needed for analysis. It addresses challenges of big data by allowing data to be stored and analyzed together without upfront structuring.
2. Traditional data warehouses structure data upfront, limiting flexibility. A data lake avoids this by storing all data as-is and analyzing data when questions arise. This provides greater analytic power on emerging big data sources.
3. While data lakes provide benefits like reduced costs and more flexibility, challenges remain around metadata management, governance, preparation, and security when storing all raw data in one place. Effective solutions are needed for these challenges to realize the full potential of data lakes.
This document provides an introduction to big data, including its key characteristics of volume, velocity, and variety. It describes different types of big data technologies like Hadoop, MapReduce, HDFS, Hive, and Pig. Hadoop is an open source software framework for distributed storage and processing of large datasets across clusters of computers. MapReduce is a programming model used for processing large datasets in a distributed computing environment. HDFS provides a distributed file system for storing large datasets across clusters. Hive and Pig provide data querying and analysis capabilities for data stored in Hadoop clusters using SQL-like and scripting languages respectively.
This document discusses business analytics and intelligence. It covers topics such as big data, structured vs unstructured data, databases, infrastructure, analytics evolution, and data visualization. Big data provides value when data sets are massive, though it can be expensive to store and process. Combining structured and unstructured data enables predictive analytics. NoSQL databases were developed to handle diverse data types at large scales. Cloud infrastructure provides benefits like streamlined IT management and widespread access to business intelligence across an organization. Analytics are evolving from internal data analysis to integrating diverse external data sources and building products using predictive insights. Data visualization is an important way to communicate findings from analytics, though the quality of the underlying data impacts the credibility of any visualizations.
Solix Common Data Platform: Advanced Analytics and the Data-Driven EnterpriseLindaWatson19
Enterprise data continues to grow at an accelerating rate, increasingly in unstructured or semi-structured formats. At the same time, as Forrester shares in the report, “Business users are demanding faster, more real-time, and integrated customer analytics from multiple sources, so they can make better decisions and increase their company’s competitiveness.”
Unified query allows a single SQL statement to access and analyze data across relational databases, NoSQL data stores, and large parallel filesystems like HDFS. This integrated approach reduces the need to move data between siloed systems and enables existing tools and skills to be leveraged with big data. Oracle's Big Data SQL uses query franchising to provide unified query, maintaining high performance across data stores while also extending security and governance policies.
I have collected information for the beginners to provide an overview of big data and hadoop which will help them to understand the basics and give them a Start-Up.
Case Study - Spotad: Rebuilding And Optimizing Real-Time Mobile Adverting Bid...Vasu S
Find out how Qubole helped Spotad, Inc's mobile advertising platform, save 50 percent in its operating costs almost instantly after their migration.
https://www.qubole.com/resources/case-study/spotad
Trends in Big Data & Business Challenges Experian_US
Join our #DataTalk on Thursdays at 5 p.m. ET. This week, we tweeted with Sushil Pramanick – who is the founder and president of the The Big Data Institute (TBDI).
You can learn about upcoming chats and see the archive of past big data tweetchats here
http://www.experian.com/blogs/news/about/datadriven
IRJET- A Scrutiny on Research Analysis of Big Data Analytical Method and Clou...IRJET Journal
This document discusses big data analytical methods, cloud computing, and how they can be combined. It explains that big data involves large amounts of structured, semi-structured, and unstructured data from various sources that requires significant computing resources to analyze. Cloud computing provides a way for big data analytics to be offered as a service and processed efficiently using cloud resources. The integration of big data and cloud computing allows organizations to gain business intelligence from large datasets in a flexible, scalable and cost-effective manner.
7 Big Data Challenges and How to Overcome ThemQubole
Implementing a big data project is difficult. Hadoop is complex, and data governance is crucial. Learn common big data challenges and how to overcome them.
Enough taking about Big data and Hadoop and let’s see how Hadoop works in action.
We will locate a real dataset, ingest it to our cluster, connect it to a database, apply some queries and data transformations on it , save our result and show it via BI tool.
Big Data Ppt PowerPoint Presentation Slides SlideTeam
Big data has brought about a revolution in the field of information technology. Our content-ready big data PPT PowerPoint presentation slides shed light on the importance and relevance of large volumes of data. The data management presentation covers myriad of topics such as big data sources, market forecast, 3 Vs, technologies, workflow, data analytics process, impact, benefit, future, opportunity and challenges, and many additional slides containing graphs and charts. The biggest benefit that this big data analytics presentation template offers is that it enables you to unearth the information that can be used to shape the future of your business. Moreover, these designs can also be utilized to craft your own presentation on predictive analytics, data processing application, database, cloud computing, business intelligence, and user behavior analytics. Download big data PPT visuals which will help you make accurate business decisions. Enlighten folks on fraud with our Big Data PPt PowerPoint Presentation Slides. Convince them to be highly alert.
The top 7 trends in big data for 2015 are:
1) Cloud adoption will continue to grow dramatically as big data drives cloud growth.
2) Personal data preparation tools will make extracting, transforming, and loading (ETL) data easier.
3) NoSQL databases will continue gaining popularity for providing scale, flexibility, and faster querying of large data sets.
4) Hadoop will remain a key part of big data architectures, integrated by both legacy data storage vendors and new players.
5) Interest in the "data lake" concept of large unrefined data stores will grow as companies seek to effectively manage massive amounts of incoming data.
6) The big data ecosystem will start to change as
The document discusses what a white paper is, who writes them, and what they contain. A white paper is a fact-based marketing document published by a company or institution to promote a product, service, or idea. It provides information to help potential buyers compare products or justify purchase decisions. White papers are written by companies, governments, and academic/research institutions and read by engineers, finance professionals, and those in purchasing and R&D roles. They contain facts, technical descriptions, comparisons, analyses, and recommendations.
How to write a technology white paper to increase salesAna Thompson
Tutorial on how to write a technology white paper to increase sales. Examples of how to structure, format, and write more persuasive content to win business
Overview of mit sloan case study on ge data and analytics initiative titled g...Gregg Barrett
GE collects sensor data from industrial equipment to analyze equipment performance and predict failures. It created a "data lake" to integrate raw flight data from 3.4 million flights with other data sources. This allows data scientists to identify issues reducing equipment uptime for customers. However, GE faces challenges in finding qualified analytics talent and establishing effective data governance as it scales its data and analytics efforts.
Making Sense of NoSQL and Big Data Amidst High ExpectationsRackspace
1) There is a lot of hype around NoSQL and Big Data technologies but they provide value for specific problems involving large, varied datasets with high rates of change.
2) NoSQL databases are useful for problems that don't require a relational data model and involve huge datasets, while SQL databases remain critical for transaction processing and maintaining relationships between structured data.
3) Organizations should choose technologies based on their specific business requirements and understand each technology's strengths rather than favoring "cool" technologies.
1. A data lake is a storage repository that holds vast amounts of raw data in its native format until it is needed for analysis. It addresses challenges of big data by allowing data to be stored and analyzed together without upfront structuring.
2. Traditional data warehouses structure data upfront, limiting flexibility. A data lake avoids this by storing all data as-is and analyzing data when questions arise. This provides greater analytic power on emerging big data sources.
3. While data lakes provide benefits like reduced costs and more flexibility, challenges remain around metadata management, governance, preparation, and security when storing all raw data in one place. Effective solutions are needed for these challenges to realize the full potential of data lakes.
This document provides an introduction to big data, including its key characteristics of volume, velocity, and variety. It describes different types of big data technologies like Hadoop, MapReduce, HDFS, Hive, and Pig. Hadoop is an open source software framework for distributed storage and processing of large datasets across clusters of computers. MapReduce is a programming model used for processing large datasets in a distributed computing environment. HDFS provides a distributed file system for storing large datasets across clusters. Hive and Pig provide data querying and analysis capabilities for data stored in Hadoop clusters using SQL-like and scripting languages respectively.
This document discusses business analytics and intelligence. It covers topics such as big data, structured vs unstructured data, databases, infrastructure, analytics evolution, and data visualization. Big data provides value when data sets are massive, though it can be expensive to store and process. Combining structured and unstructured data enables predictive analytics. NoSQL databases were developed to handle diverse data types at large scales. Cloud infrastructure provides benefits like streamlined IT management and widespread access to business intelligence across an organization. Analytics are evolving from internal data analysis to integrating diverse external data sources and building products using predictive insights. Data visualization is an important way to communicate findings from analytics, though the quality of the underlying data impacts the credibility of any visualizations.
Solix Common Data Platform: Advanced Analytics and the Data-Driven EnterpriseLindaWatson19
Enterprise data continues to grow at an accelerating rate, increasingly in unstructured or semi-structured formats. At the same time, as Forrester shares in the report, “Business users are demanding faster, more real-time, and integrated customer analytics from multiple sources, so they can make better decisions and increase their company’s competitiveness.”
Unified query allows a single SQL statement to access and analyze data across relational databases, NoSQL data stores, and large parallel filesystems like HDFS. This integrated approach reduces the need to move data between siloed systems and enables existing tools and skills to be leveraged with big data. Oracle's Big Data SQL uses query franchising to provide unified query, maintaining high performance across data stores while also extending security and governance policies.
I have collected information for the beginners to provide an overview of big data and hadoop which will help them to understand the basics and give them a Start-Up.
Case Study - Spotad: Rebuilding And Optimizing Real-Time Mobile Adverting Bid...Vasu S
Find out how Qubole helped Spotad, Inc's mobile advertising platform, save 50 percent in its operating costs almost instantly after their migration.
https://www.qubole.com/resources/case-study/spotad
Trends in Big Data & Business Challenges Experian_US
Join our #DataTalk on Thursdays at 5 p.m. ET. This week, we tweeted with Sushil Pramanick – who is the founder and president of the The Big Data Institute (TBDI).
You can learn about upcoming chats and see the archive of past big data tweetchats here
http://www.experian.com/blogs/news/about/datadriven
IRJET- A Scrutiny on Research Analysis of Big Data Analytical Method and Clou...IRJET Journal
This document discusses big data analytical methods, cloud computing, and how they can be combined. It explains that big data involves large amounts of structured, semi-structured, and unstructured data from various sources that requires significant computing resources to analyze. Cloud computing provides a way for big data analytics to be offered as a service and processed efficiently using cloud resources. The integration of big data and cloud computing allows organizations to gain business intelligence from large datasets in a flexible, scalable and cost-effective manner.
7 Big Data Challenges and How to Overcome ThemQubole
Implementing a big data project is difficult. Hadoop is complex, and data governance is crucial. Learn common big data challenges and how to overcome them.
Enough taking about Big data and Hadoop and let’s see how Hadoop works in action.
We will locate a real dataset, ingest it to our cluster, connect it to a database, apply some queries and data transformations on it , save our result and show it via BI tool.
Big Data Ppt PowerPoint Presentation Slides SlideTeam
Big data has brought about a revolution in the field of information technology. Our content-ready big data PPT PowerPoint presentation slides shed light on the importance and relevance of large volumes of data. The data management presentation covers myriad of topics such as big data sources, market forecast, 3 Vs, technologies, workflow, data analytics process, impact, benefit, future, opportunity and challenges, and many additional slides containing graphs and charts. The biggest benefit that this big data analytics presentation template offers is that it enables you to unearth the information that can be used to shape the future of your business. Moreover, these designs can also be utilized to craft your own presentation on predictive analytics, data processing application, database, cloud computing, business intelligence, and user behavior analytics. Download big data PPT visuals which will help you make accurate business decisions. Enlighten folks on fraud with our Big Data PPt PowerPoint Presentation Slides. Convince them to be highly alert.
The top 7 trends in big data for 2015 are:
1) Cloud adoption will continue to grow dramatically as big data drives cloud growth.
2) Personal data preparation tools will make extracting, transforming, and loading (ETL) data easier.
3) NoSQL databases will continue gaining popularity for providing scale, flexibility, and faster querying of large data sets.
4) Hadoop will remain a key part of big data architectures, integrated by both legacy data storage vendors and new players.
5) Interest in the "data lake" concept of large unrefined data stores will grow as companies seek to effectively manage massive amounts of incoming data.
6) The big data ecosystem will start to change as
The document discusses what a white paper is, who writes them, and what they contain. A white paper is a fact-based marketing document published by a company or institution to promote a product, service, or idea. It provides information to help potential buyers compare products or justify purchase decisions. White papers are written by companies, governments, and academic/research institutions and read by engineers, finance professionals, and those in purchasing and R&D roles. They contain facts, technical descriptions, comparisons, analyses, and recommendations.
How to write a technology white paper to increase salesAna Thompson
Tutorial on how to write a technology white paper to increase sales. Examples of how to structure, format, and write more persuasive content to win business
Amazon has used three digital engines to reshape and dominate retail:
1. Limitless inventory - Digital enables Amazon to offer an exhaustive selection across many categories without physical space constraints.
2. Boosting customer care - Digital allows Amazon to optimize the customer experience through real-time metrics, A/B testing, and unlimited inventory.
3. Enabling high margins and low prices - Digital reduces Amazon's variable costs to negligible levels, allowing it to offer low prices while focusing on long-term growth through market share.
BM® Security Guardium® Data Activity Monitor empowers security
teams to analyze, protect and adapt for comprehensive data protection in
heterogeneous environments, including databases, data warehouses, files,
file shares, cloud, and big-data platforms such as Hadoop and NoSQL.
This document discusses how data is structured and modeled in databases and data warehouses. It introduces concepts like left-to-right entity relationship diagrams and data model depth. It examines how characteristics like model depth, data volumes, and complexity affect areas like reporting structures, data warehouse design, ETL processes, data quality, and query performance. Understanding these characteristics helps reduce their negative impacts and lower project costs.
Whitepaper: Volume Testing Thick Clients and DatabasesRTTS
Even in the current age of cloud computing there are still endless benefits of developing thick client software: non-dependency on browser version, offline support, low hosting fees, and utilizing existing end user hardware, to name a few.
It's more than likely that your organization is utilizing at least a few thick client applications. Now consider this: as your user base grows, does your think client's back-end server need to grow as well? How quickly? How do you ensure that you provide the correct amount of additional capacity without overstepping and unnecessarily eating into your profits? The answer is volume testing.
Read how RTTS does this with IBM Rational Performance Tester.
This document provides tips for writing effective white papers. It recommends that white papers establish authority, build influence, and generate revenue by answering key questions for decision makers. It suggests using active voice, concrete language, and positive phrasing while avoiding jargon and clichés. White papers should be structured to define the scope, provide context, explain the approach, and recommend a solution in a concise manner. Images and charts can help explain concepts and show relationships. The goal is to make the white paper interesting, demonstrate expertise, and build credibility for the reader.
Creating effective white papers and industry reportsSonia Quinones
An easy 7-step guide to creating lead-generating white papers. This guide is designed for marketers working in small to mid-sized B2B companies or nonprofits that need to communicate complex topics to influence and inform their audiences.
The document reviews and compares past education policies in Pakistan from 1947 to 1998. It analyzes the policies across different themes, including their vision/objectives, treatment of primary/secondary education, religious education, gender issues, and financing of education. The policies evolved over time, with earlier ones focusing more on universal brotherhood and civic values, and later ones in 1979 and 1998 emphasizing Islamization of education and envisioning Pakistan as an ideological state with Islam as the sole basis of national identity.
Our latest white paper, “Blockchain Technology and the Financial Services Market,” covers themes around:
Distributed ledger and blockchain are about to cause major business transformations in the financial services industry
Three of the most promising fields of application are payment transactions, trade finance and over-the-counter markets
Technical challenges and legal frameworks are currently a major obstacle
Many market participants are exploring ways of using blockchain, including established institutions and start-ups firms
Read the entire research report for expert insights and the full Infosys Consulting point-of-view!
The document discusses the benefits of meditation for reducing stress and anxiety. Regular meditation practice can help calm the mind and body by lowering heart rate and blood pressure. Studies have shown that meditating for just 10-20 minutes per day can have significant positive impacts on both mental and physical health over time.
- Database as a Service (DBaaS) adoption is expected to triple over the next two years as enterprises rethink data management in the cloud. A significant amount of enterprise data and core workloads will shift to cloud platforms.
- By 2024, 43% of organizations expect to run over 25% of their workloads in the cloud, compared to 14% currently. A third of data assets will be cloud-based, compared to 11% currently.
- Developers are increasingly using cloud environments for application development and testing. Over a third are running transactional databases in the cloud. Cost cutting and efficiency are driving more organizations to deliver database services in the cloud.
TOP 5 TRENDS IN BIG DATA & ANALYTICS 2015 was an interesting one in the area of big data and analytics. What used to be buzz words in conference and talk shows became the norm as more companies realized that data, in all forms and sizes, is critical.
The document discusses Luminar, an analytics company that uses big data and Hadoop to provide insights about Latino consumers in the US. Luminar collects data from over 2,000 sources and uses that data along with "cultural filters" to identify Latinos and understand their purchasing behaviors. This provides more accurate information than traditional surveys. Luminar implemented a Hadoop system to more quickly analyze this large amount of data and provide valuable insights to marketers and businesses.
This document discusses the top 5 trends in big data and analytics for 2016. It notes that in 2015, big data became more mainstream as companies realized the importance of all types of data for decision making. Going forward, tools that support unstructured and huge volumes of data will continue growing and integrate better with existing IT systems. The trends discussed are: increased adoption of NoSQL databases in enterprises; rapid growth of Apache Spark usage; continued movement of Hadoop implementations from proofs-of-concept to production; maturation of Hadoop implementations; and growth of cloud-based data warehousing with increased competition among vendors.
2015 was an interesting one in the area of big data and analytics. What used to be buzz words in conference and talk shows became the norm as more companies realized that data, in all forms and sizes, is critical to making the best business decisions.
IRJET- A Comparative Study on Big Data Analytics Approaches and ToolsIRJET Journal
This document provides an overview of big data analytics approaches and tools. It begins with an abstract discussing the need to evaluate different methodologies and technologies based on organizational needs to identify the optimal solution. The document then reviews literature on big data analytics tools and techniques, and evaluates challenges faced by small vs large organizations. Several big data application examples across industries are presented. The document also introduces concepts of big data including the 3Vs (volume, velocity, variety), describes tools like Hadoop, Cloudera and Cassandra, and discusses scaling big data technologies based on an organization's requirements.
The “death” of the data warehouse has been overhyped for
some time now, but it’s no secret that growth in this segment
of the market has been slowing. But we now see a major shift
in the application of this technology to the cloud where
Amazon led the way with an on-demand cloud data warehouse
in Redshift. Redshift was AWS’s fastest growing service
but it now has competition from Google with BigQuery,
Bigger, faster, and cloudier: that’s where big data is headed in 2016. More people are doing more things faster with their data, but the details of how continue to evolve. Get up to speed on the latest trends in big data.
The document discusses strategies for deriving business value from big data analytics. It emphasizes that collecting large amounts of data is only the first step, and the key is using analytics to find useful insights hidden in the data. It provides guidance on focusing big data initiatives by addressing data accuracy, storage needs, query performance, and scalability when planning projects. Additionally, it discusses how conferences have focused on how to deliver big data analytics to users in a way that connects to real business value.
Big data refers to large volumes of structured and unstructured data that are difficult to process using traditional database and software techniques. It encompasses the 3Vs - volume, velocity, and variety. Hadoop is an open-source framework that stores and processes big data across clusters of commodity servers using the MapReduce algorithm. It allows applications to work with huge amounts of data in parallel. Organizations use big data and analytics to gain insights for reducing costs, optimizing offerings, and making smarter decisions across industries like banking, government, and education.
Are You Prepared For The Future Of Data Technologies?Dell World
We are increasingly coming upon an age where technology is a strong enabler of business success, where there are strong synergies between business strategy and technology strategy. You often cannot discuss business strategy without data and related technologies being a big part of it. And as such, business leaders are increasingly turning to IT to compete more effectively in the market. As IT management, it falls upon you to ensure that your data technology architecture (software & hardware) is built in a way that it can handle the business demands of today and in to the future. In this session, we will discuss the various big data technology architectures and associated tools, and what role each should play in your data environment. We will also give real life examples of how others are using these technologies. Build a better data architecture, to unlock the power of all data.
Moving Toward Big Data: Challenges, Trends and PerspectivesIJRESJOURNAL
Abstract: Big data refers to the organizational data asset that exceeds the volume, velocity, and variety of data typically stored using traditional structured database technologies. This type of data has become the important resource from which organizations can get valuable insightand make business decision by applying predictive analysis. This paper provides a comprehensive view of current status of big data development,starting from the definition and the description of Hadoop and MapReduce – the framework that standardizes the use of cluster of commodity machines to analyze big data. For the organizations that are ready to embrace big data technology, significant adjustments on infrastructure andthe roles played byIT professionals and BI practitioners must be anticipated which is discussed in the challenges of big data section. The landscape of big data development change rapidly which is directly related to the trend of big data. Clearly, a major part of the trend is the result ofthe attempt to deal with the challenges discussed earlier. Lastly the paper includes the most recent job prospective related to big data. The description of several job titles that comprise the workforce in the area of big data are also included.
Influence of Hadoop in Big Data Analysis and Its Aspects IJMER
This paper is an effort to present the basic understanding of BIG DATA and
HADOOP and its usefulness to an organization from the performance perspective. Along-with the
introduction of BIG DATA, the important parameters and attributes that make this emerging concept
attractive to organizations has been highlighted. The paper also evaluates the difference in the
challenges faced by a small organization as compared to a medium or large scale operation and
therefore the differences in their approach and treatment of BIG DATA. As Hadoop is a Substantial
scale, open source programming system committed to adaptable, disseminated, information
concentrated processing. A number of application examples of implementation of BIG DATA across
industries varying in strategy, product and processes have been presented. This paper also deals
with the technology aspects of BIG DATA for its implementation in organizations. Since HADOOP has
emerged as a popular tool for BIG DATA implementation. Map reduce is a programming structure for
effectively composing requisitions which prepare boundless measures of information (multi-terabyte
information sets) in- parallel on extensive bunches of merchandise fittings in a dependable,
shortcoming tolerant way. A Map reduce skeleton comprises of two parts. They are “mapper" and
"reducer" which have been examined in this paper. The paper deals with the overall architecture of
HADOOP along with the details of its various components in Big Data.
This document discusses big data business opportunities and solutions. It notes that big data solutions are tailored to specific data types and workloads. Common business domains for big data include web analytics, clickstream analysis using the ELK stack, and big data in the cloud to provide auto-scaling, low costs, and use of cloud services. Effective big data solutions require data governance, cluster modeling, and analytics and visualization.
This document provides an overview of big data and how to start a career working with big data. It discusses the growth of data from various sources and challenges of dealing with large, unstructured data. Common data types and measurement units are defined. Hadoop is introduced as an open-source framework for storing and processing big data across clusters of computers. Key components of Hadoop's ecosystem are explained, including HDFS for storage, MapReduce/Spark for processing, and Hive/Impala for querying. Examples are given of how companies like Walmart and UPS use big data analytics to improve business decisions. Career opportunities and typical salaries in big data are also mentioned.
This document provides an overview and introduction to big data implementation strategies using Hadoop and beyond. It discusses how big data has evolved from technologies pioneered by companies like Google to analyze vast amounts of diverse data cheaper and more effectively than traditional methods. It also outlines some of the key challenges organizations face as data volumes, varieties, and velocities outgrow existing systems, and how new big data technologies like Hadoop provide more cost-effective solutions to process and analyze data at scale. The document notes that big data represents a shift in computing paradigms rather than just data size alone.
We wanted to know how companies viewed the changing data warehousing landscape, so we surveyed 200 businesses to learn more about the issues they faced. In "Delivering the Best of All Worlds for Today's Analytics" we compare the technology, present the options, and provide findings from our survey. We also discuss the latest column store techniques and open source technology to provide both enterprise class performance and affordability.
This document discusses big data and provides an overview of key concepts and technologies. It defines big data as large volumes of data in various formats that are growing rapidly. It describes the four V's of big data - volume, velocity, variety, and value. The document then provides an overview of big data technologies like columnar databases, NoSQL, and Hadoop that are designed to handle large and complex data sets.
Similar to the-real-world-of-the-database-administrator-white-paper-15623 (20)
1. Sponsored by
THE REAL
WORLD OF THE
DATABASE
ADMINISTRATOR
By Dr. Elliot King, Research Analyst
Produced by Unisphere Research,
a Division of Information Today, Inc.
March 2015
Produced by
2. 2
THE REAL WORLD OF THE DATABASE ADMINISTRATOR was produced by Unisphere Research and sponsored by Dell Software. Unisphere Research is the market research unit of
Unisphere Media, a division of Information Today, Inc., publishers of Database Trends and Applications magazine and the 5 Minute Briefing newsletters. To review abstracts of our past
reports, visit www.dbta.com/About_Us#Unisphere. Unisphere Media, 121 Chanlon Road, New Providence, NJ 07974; 908-795-3702.
TABLE OF CONTENTS
Introduction and Key Findings���������������������������������������������������������������������������������������������������������3
The Database Infrastructure������������������������������������������������������������������������������������������������������������4
Data Under Management��������������������������������������������������������������������������������������������������������������10
DBAs’ Responsibilities�������������������������������������������������������������������������������������������������������������������14
The Future��������������������������������������������������������������������������������������������������������������������������������������21
Conclusion��������������������������������������������������������������������������������������������������������������������������������������25
Appendix A�������������������������������������������������������������������������������������������������������������������������������������26
3. 3
THE REAL WORLD OF THE DATABASE ADMINISTRATOR was produced by Unisphere Research and sponsored by Dell Software. Unisphere Research is the market research unit of
Unisphere Media, a division of Information Today, Inc., publishers of Database Trends and Applications magazine and the 5 Minute Briefing newsletters. To review abstracts of our past
reports, visit www.dbta.com/About_Us#Unisphere. Unisphere Media, 121 Chanlon Road, New Providence, NJ 07974; 908-795-3702.
INTRODUCTION AND KEY FINDINGS
In the world of IT, perhaps nothing is more exciting than the
introduction of radically new technologies. And the information
management arena may be on the verge of one of those moments.
The past 10 years have been a golden age for generating and
capturing a virtual avalanche of new kinds and quantities of data.
With the growth of cloud computing and associated storage
technologies, social media, low-cost video, and other hot new
technologies, companies have access to an abundance of new
data types.
These developments have led to new ways of thinking about
data. Approaches like those represented by Hadoop and NoSQL
seemingly point the way to a post-structured-data world. And
concepts like data lakes paint a picture of assembling huge
pools of highly varied data that can be accessed and analyzed on
demand. The idea is to get to better data analysis, quicker and
less expensively using much larger datasets to advance everything
from fraud detection to predictive analysis.
The ability to capture, store, retrieve, analyze and save data
in new ways holds the potential to gain new insights and new
ways of doing business. If information is power, to paraphrase
an old adage, more information can lead to more power. Great
information can guide companies to greater business success.
But the attention to the new developments in information
management should not obscure the fact that structured data
in relational databases still provides the foundation for the
information infrastructure in many, if not most, companies, and
will do so in most organizations for the foreseeable future. The
ways in which companies can exploit structured data is far from
exhausted. And database administrators (DBAs) still represent the
front-line personnel for data management in most enterprises.
To understand the current role of the DBA and the way
that role is changing, Dell commissioned Unisphere Research,
a division of Information Today, Inc., to survey database
administrators and others charged with managing corporate data.
The 300 respondents came from a wide range of companies in
terms of size and industry. Nearly two-thirds of the respondents
came from organizations with more than 1,000 employees and
more than a dozen industries were represented. One-quarter of
respondents’ organizations are running more than 500 databases.
Details about the respondent pool can be found in the appendix.
Among the key findings are the following:
n While Hadoop and NoSQL are exciting new technologies,
their use currently is confined primarily to large companies.
The traditional database management system still
provides the foundation for the information management
infrastructure in most organizations. Oracle and Microsoft
SQL Server are the most common platforms to support
mission-critical data.
n Most enterprises believe that more familiar “new”
technologies such as virtualization and cloud computing will
have more impact on their organization over the next several
years than “newer” emerging technologies such as Hadoop.
In fact, Hadoop and NoSQL do not factor into many
companies’ plans over the next few years.
n Information infrastructures are not static. Most companies
run multiple databases and are open to adding new database
platforms if there is a need to do so. The most common
motivating factor for adding a new database management
system is the need to support new analytical applications.
n Most DBAs are responsible for multiple database instances
from multiple vendors.
n Structured data remains the bedrock of the information
infrastructure in most organizations.
n While maintenance and performance are the top
responsibilities for most DBAs, security is becoming an
increasingly important item on their agendas. However,
currently, DBAs spend less time on security issues than they
do on supporting database development.
n The key challenge for DBAs is learning new technologies.
4. 4
THE REAL WORLD OF THE DATABASE ADMINISTRATOR was produced by Unisphere Research and sponsored by Dell Software. Unisphere Research is the market research unit of
Unisphere Media, a division of Information Today, Inc., publishers of Database Trends and Applications magazine and the 5 Minute Briefing newsletters. To review abstracts of our past
reports, visit www.dbta.com/About_Us#Unisphere. Unisphere Media, 121 Chanlon Road, New Providence, NJ 07974; 908-795-3702.
THE DATABASE INFRASTRUCTURE
Although a lot of attention has rightly been lavished on
emerging new information management technologies, mainstay
database management systems still play the critical role in the
information infrastructure. As Figure 1 shows, Microsoft SQL
Server and Oracle are found in the overwhelming majority
of organizations, with MySQL, IBM DB2, and MongoDB
representing the next most popular database management systems.
The appearance of MongoDB on this list provides evidence
for a growing acceptance of NoSQL technology, particularly
in larger companies. Around 70% of all MongoDB users are
running more than 100 databases and 30% are running more
than 500 databases. And, nearly 60% of the MongoDB users are
in companies with more than 5,000 employees.
While there is relative diversity in the use of database
platforms—more than 20 different brands were mentioned by
respondents—Oracle, Microsoft SQL Server, IBM DB2 LUW, and
SAP Sybase ASE were the dominant RDBMSs running mission-
critical data, with Oracle and Microsoft SQL Server clearly the
leaders. Indeed, approximately 78% of the respondents indicated
that they were running mission-critical data on Oracle and 72%
said they were using Microsoft SQL Server as a platform for their
mission-critical data. Almost one-quarter of the respondents
said that they had turned to IBM DB2 LUW for mission-critical
activities and almost 12% have opted for SAP Sybase ASE.
In contrast, roughly 6% of the respondents are using
MongoDB, the most popular NoSQL database technology in
this pool, for mission-critical data. As a whole, the survey results
provide a good barometer for the current state of the adoption
of NoSQL technology. NoSQL is beginning to penetrate larger
companies but is not yet routinely a platform of mission-critical
data. Moreover, as Figure 2 shows, many companies have not yet
factored NoSQL into their plans in the next few years.
Along the same lines, although Hadoop has justifiably
generated attention as a next-generation information
management, its use is still largely confined to large companies.
In fact, 60% of respondents who are currently using Hadoop are
running more than 100 databases and 45% are running more
than 500 databases. Moreover, approximately two-thirds of the
respondents using Hadoop are employed by companies with
more than 1,000 people.
Furthermore, as Figure 3 shows, Hadoop does not yet factor
into most companies’ plans. At this time, only 15% of the
respondents are actually using Hadoop (and around another 5%
are in the process of deploying it), and nearly 60% currently have
no plans to use it in the future.
Clearly, traditional RDBMSs shoulder the lion’s share of
data management in most organizations. And since more than
85% of the respondents are running Microsoft SQL Server and
about 80% use Oracle, the evidence is clear that most companies
support two or more DBMS brands. As Figure 4 shows, by
far, the most important reason companies use more than one
database platform is to support different applications, with the
need to support multiple user groups the second most common
reason. Supporting increased data volume was only the fifth most
important reason for adding a new DBMS platform.
Under the right circumstances, organizations are open to
adding new DBMS platforms. The most common reason given
for adding a new brand is the emergence of a new analytical use
case. But other factors can also motivate a company to add a new
DBMS as well, including the need to improve performance and
flexibility as well as to better manage costs. (See Figure 5).
Several key insights are reflected in these results. First, most
companies run multiple databases and are open to adding new
database platforms if there is a perceived need to do so. The most
common motivational factor to add a new database management
system is to support new analytical applications. This scenario
bodes well for Hadoop if it can deliver on its promise to make
analysis more flexible and less costly. At this moment, however,
the use of Hadoop and NoSQL technology is largely confined to
bigger companies and many companies have no plans to explore
these newer technologies at all.
The Role of the DBA
As the information infrastructure changes due to both the
growth of data under management as well as the introduction
of new technologies, including cloud-based computing, it could
be expected that the role of the DBA, long on the front lines of
data management, would change as well. In this survey, 75% of
respondents’ companies had between 1 and 25 people with the
specific title of DBA, and 15% had more than 25 people with the
title of DBA (although in many companies, people who have other
titles will perform tasks associated with database administration).
As might be expected, most DBAs are responsible for multiple
database instances. As Figure 6 shows, almost half of the DBAs
manage more than 25 database instances each, and almost 10%
manage more than 100 database instances each.
Not surprisingly, the number of database instances for which
each DBA is responsible is growing. (See Figure 7.) The number
of databases for which each DBA is responsible is decreasing at
only 5% of the respondents’ companies.
Not only are DBAs responsible for managing multiple database
instances, they manage database management systems from
multiple vendors as well. As indicated in Figure 8, approximately
70% of the respondents said that the DBAs in their organizations
t
t
5. 5
THE REAL WORLD OF THE DATABASE ADMINISTRATOR was produced by Unisphere Research and sponsored by Dell Software. Unisphere Research is the market research unit of
Unisphere Media, a division of Information Today, Inc., publishers of Database Trends and Applications magazine and the 5 Minute Briefing newsletters. To review abstracts of our past
reports, visit www.dbta.com/About_Us#Unisphere. Unisphere Media, 121 Chanlon Road, New Providence, NJ 07974; 908-795-3702.
were responsible for managing databases from at least two vendors,
and 7% of respondents said the DBAs at their companies were
responsible for managing databases from five or more vendors.
The growth or potential growth of non-relational data
management technology such as NoSQL and Hadoop raises
an interesting question. Will DBAs be responsible for non-
relational information management technology? Or, will a
different job classification emerge to claim stewardship of those
technologies? The answer to that question is not yet clear but the
indication is that over the long term, DBAs will be responsible
for non-relational information management platforms as well.
Figure 9 shows that roughly two-thirds of the respondents that
had deployed either Hadoop or NoSQL said that DBAs were
responsible for managing those technologies.
Drilling down, in 62% of the organizations that have
already deployed a NoSQL platform—but not Hadoop—
DBAs are responsible for managing the NoSQL technology. In
organizations that have deployed Hadoop—but not NoSQL—
only 52% of the organizations have DBAs managing Hadoop.
And, in companies that have both Hadoop and NoSQL
installed, DBAs are responsible for managing the non-relational
technologies 72% of the time.
Clearly, the long-term trends that DBAs have faced are still in
place. DBAs are the front-line data management administrators.
Each DBA is responsible for multiple database instances from
multiple vendors and the number of databases each DBA is
expected to manage is increasing. But, there is a twist. Over the
next few years, as Hadoop and NoSQL become more common
in the enterprise, DBAs are also likely to be the ones responsible
for the administration of non-relational data infrastructure
technologies.
Microsoft SQL Server 87.37%
Oracle 79.86%
MySQL 41.3%
IBM DB2 LUW 28.33%
Mongo DB 14.33%
0 20 40 60 80 100
0 20 40 60 80 100
Figure 1: What database brands do you have running in your organization?
6. 6
THE REAL WORLD OF THE DATABASE ADMINISTRATOR was produced by Unisphere Research and sponsored by Dell Software. Unisphere Research is the market research unit of
Unisphere Media, a division of Information Today, Inc., publishers of Database Trends and Applications magazine and the 5 Minute Briefing newsletters. To review abstracts of our past
reports, visit www.dbta.com/About_Us#Unisphere. Unisphere Media, 121 Chanlon Road, New Providence, NJ 07974; 908-795-3702.
Already using a NoSQL database 9.66%
Currently deploying 11.72%
Will deploy in 1 to 2 years 17.59%
Will deploy in 2 to 3 years 1.38%
Will deploy in 3+ years 3.45%
No plans 56.21%
0 20 40 60 80 100
0 20 40 60 80 100
Figure 2: Does your company currently have plans to adopt NoSQL database
technology?
Already using Hadoop 15.15%
Currently deploying 5.3%
Will deploy in 1 to 2 years 14.39%
Will deploy in 2 to 3 years 3.79%
Will deploy in 3+ years 3.79%
No plans 57.58%
0 20 40 60 80 100
0 20 40 60 80 100
Figure 3: Does your company use or have plans to use Hadoop?
7. 7
THE REAL WORLD OF THE DATABASE ADMINISTRATOR was produced by Unisphere Research and sponsored by Dell Software. Unisphere Research is the market research unit of
Unisphere Media, a division of Information Today, Inc., publishers of Database Trends and Applications magazine and the 5 Minute Briefing newsletters. To review abstracts of our past
reports, visit www.dbta.com/About_Us#Unisphere. Unisphere Media, 121 Chanlon Road, New Providence, NJ 07974; 908-795-3702.
Supporting multiple applications 80.29%
Supporting multiple user groups 45.88%
Supporting multiple workloads 31.18%
Managing database licensing and 29.03%
support costs
Supporting increasing data volumes 17.56%
0 20 40 60 80 100
0 20 40 60 80 100
Figure 4: What is the most important reason for using multiple database
platforms in your organization?
Supporting new analytical use cases 46.42%
Improving database flexibility 35.47%
Improving database performance 35.09%
Supporting increasing data volumes 32.45%
Managing increasing database 32.45%
licensing and support costs
Supporting unstructured data growth 27.55%
Consolidating data infrastructure 25.28%
0 20 40 60 80 100
0 20 40 60 80 100
Figure 5: What are the most important reasons for adopting a new database
management system in your organization?
8. 8
THE REAL WORLD OF THE DATABASE ADMINISTRATOR was produced by Unisphere Research and sponsored by Dell Software. Unisphere Research is the market research unit of
Unisphere Media, a division of Information Today, Inc., publishers of Database Trends and Applications magazine and the 5 Minute Briefing newsletters. To review abstracts of our past
reports, visit www.dbta.com/About_Us#Unisphere. Unisphere Media, 121 Chanlon Road, New Providence, NJ 07974; 908-795-3702.
One 1.14%
2 to 10 27%
11 to 25 21.29%
26 to 100 28.52%
101 to 500 8.75%
500 2.66%
Don’t know 10.65%
0 20 40 60 80 100
0 20 40 60 80 100
Figure 6: Approximately how many database instances does each
DBA manage?
Figure 7: Is the number of databases for which each DBA is responsible
increasing, decreasing, or staying the same?
Increasing 72.31%
Decreasing 5%
Staying the same 22.69%
9. 9
THE REAL WORLD OF THE DATABASE ADMINISTRATOR was produced by Unisphere Research and sponsored by Dell Software. Unisphere Research is the market research unit of
Unisphere Media, a division of Information Today, Inc., publishers of Database Trends and Applications magazine and the 5 Minute Briefing newsletters. To review abstracts of our past
reports, visit www.dbta.com/About_Us#Unisphere. Unisphere Media, 121 Chanlon Road, New Providence, NJ 07974; 908-795-3702.
Figure 8: How many database platforms (i.e., platforms from different vendors)
is each DBA responsible for managing in your organization?
One 30.62%
Two 41.47%
Three to five 20.54%
More than five 7.36%
Figure 9: Are the DBAs that are responsible for managing relational database
management systems also responsible for managing non-relational
systems (such as NoSQL and Hadoop)?
Yes 68% No 32%
(Only respondents who had deployed Hadoop or NoSQL technology)
10. 10
THE REAL WORLD OF THE DATABASE ADMINISTRATOR was produced by Unisphere Research and sponsored by Dell Software. Unisphere Research is the market research unit of
Unisphere Media, a division of Information Today, Inc., publishers of Database Trends and Applications magazine and the 5 Minute Briefing newsletters. To review abstracts of our past
reports, visit www.dbta.com/About_Us#Unisphere. Unisphere Media, 121 Chanlon Road, New Providence, NJ 07974; 908-795-3702.
DATA UNDER MANAGEMENT
What seems to be explosive data growth has been a constant
feature of information technology and management for a long
time. The sheer volume of data under management seems
staggering and yet what was once considered a lot of data is now
seen as trivial. The respondents in this survey manage a high
volume of data, with close to 30% managing more than 500TB.
Over the past 5 years, however, the raw growth of data has
been only part of the story. As importantly, more data types are
being captured, stored, and made available for analysis. Moreover,
companies have access to more data that they themselves did not
create. Those two drivers—new data types and new data sources—
have led to the interest in what is called big data.
For all the interest in how to capture and manage unstructured
and semi-structured data, structured data remains the bedrock
of the information infrastructure in most companies. As Figure
10 shows, two-thirds of the respondents indicated that structured
data represented at least 75% of the data under management.
Nearly one-third said that their organizations do not actively
manage unstructured data at all.
Interestingly, the reported rate of growth for the total amount
of data under management is substantially less than is commonly
reported. Slightly less than half of the respondents reported that
the total amount of data under management—both structured
and unstructured—has been growing at a rate of 25% or less
annually. Looked at another way, however, around two-thirds of
the respondents said their overall data is growing between 10%
and 50% annually. (See Figure 11.)
The growth rate of structured data generally parallels the
growth rate of data overall. As Figure 12 shows, about two-thirds
of the respondents indicate that their structured data is growing
between 10% and 50% annually.
Since some organizations are not yet managing much
unstructured data, the rate of growth for unstructured data
overall as reported in this survey is not as great as might be
expected. Figure 13 shows that less than 12% of the respondents
believe that the growth rate of unstructured data under
management in their organization is more than 50% annually.
But this chart also reveals another important point. About one-
third of the respondents simply do not know how fast the amount
of unstructured data under management is growing. This can be
taken as evidence that in many organizations, unstructured data
may still be outside normal data management processes.
Figures 14 and 15 show the sources for data growth. Figure
14 asked about the sources of structured data growth and Figure
15 posed the same question for unstructured growth. Both
returned interesting results. The primary driver for the growth
in structured data is transactional data, including e-commerce
data, followed by data from ERP systems and then financial data.
Structured data from the internet outside of e-commerce, such as
clickstream data, represented a significantly less important source
of structured data growth.
As for unstructured data, despite all the attention that has
been lavished on social media as a potential new data source
for analytics, the most important driver for the growth of
unstructured data is internally generated documents, followed by
email. Clearly, when it comes to unstructured data, the challenges
of managing internally generated data have a top priority.
11. 11
THE REAL WORLD OF THE DATABASE ADMINISTRATOR was produced by Unisphere Research and sponsored by Dell Software. Unisphere Research is the market research unit of
Unisphere Media, a division of Information Today, Inc., publishers of Database Trends and Applications magazine and the 5 Minute Briefing newsletters. To review abstracts of our past
reports, visit www.dbta.com/About_Us#Unisphere. Unisphere Media, 121 Chanlon Road, New Providence, NJ 07974; 908-795-3702.
Less than 10% 3.49%
At least 10%, but less than 25% 6.98%
At least 25%, but less than 50% 7.36%
At least 50%, but less than 75% 9.3%
At least 75%, but less than 100% 35.27%
100% (we don’t actively manage 28.29%
unstructured data)
Don’t know 9.3%
0 20 40 60 80 100
0 20 40 60 80 100
Figure 10: What percentage of this data is structured (i.e., stored in traditional
relational database management systems)?
Less than 10% 7.39%
At least 10%, but less than 25% 40.47%
At least 25%, but less than 50% 28.79%
At least 50%, but less than 75% 6.23%
At least 75%, but less than 100% 2.72%
100% or more (i.e., the amount of data 2.33%
under management is doubling annually)
Don’t know 12.06%
0 20 40 60 80 100
0 20 40 60 80 100
Figure 11: How fast is the total amount of data under management at your
organization growing annually (both structured and unstructured)?
12. 12
THE REAL WORLD OF THE DATABASE ADMINISTRATOR was produced by Unisphere Research and sponsored by Dell Software. Unisphere Research is the market research unit of
Unisphere Media, a division of Information Today, Inc., publishers of Database Trends and Applications magazine and the 5 Minute Briefing newsletters. To review abstracts of our past
reports, visit www.dbta.com/About_Us#Unisphere. Unisphere Media, 121 Chanlon Road, New Providence, NJ 07974; 908-795-3702.
Less than 10% 8.66%
At least 10%, but less than 25% 43.31%
At least 25%, but less than 50% 25.2%
At least 50%, but less than 75% 6.69%
At least 75%, but less than 100% 1.97%
100% or more (i.e., the amount of data 2.36%
under management is doubling annually)
Don’t know 11.81%
0 20 40 60 80 100
0 20 40 60 80 100
Figure 12: How fast is the amount of structured data growing annually?
Less than 10% 17.39%
At least 10%, but less than 25% 20.95%
At least 25%, but less than 50% 18.58%
At least 50%, but less than 75% 3.56%
At least 75%, but less than 100% 2.77%
100% or more (i.e., the amount of data 3.95%
under management is doubling annually)
Don’t know 32.81%
0 20 40 60 80 100
0 20 40 60 80 100
Figure 13: How fast is the amount of unstructured data growing annually?
13. 13
THE REAL WORLD OF THE DATABASE ADMINISTRATOR was produced by Unisphere Research and sponsored by Dell Software. Unisphere Research is the market research unit of
Unisphere Media, a division of Information Today, Inc., publishers of Database Trends and Applications magazine and the 5 Minute Briefing newsletters. To review abstracts of our past
reports, visit www.dbta.com/About_Us#Unisphere. Unisphere Media, 121 Chanlon Road, New Providence, NJ 07974; 908-795-3702.
Growth in transactional data 83%
(including e-commerce)
Growth in management data 51.78%
(such as ERP systems)
Growth in financial data 40.32%
Growth in structured data from internet 24.9%
sources (such as clicks of visitors to
your website)
Other 3%
0 20 40 60 80 100
0 20 40 60 80 100
Figure 14: What are the most important sources of structured data growth
at your organization?
Growth in internally generated 50.41%
documents
Growth in email 35.54%
Other internet sources of data 30.58%
such as the web
Machine-generated data 31.4%
New data types such as video 29.34%
and audio
Social media 25.62%
Other 4%
0 20 40 60 80 100
0 20 40 60 80 100
Figure 15: What are the most important sources of unstructured data growth
at your organization?
14. 14
THE REAL WORLD OF THE DATABASE ADMINISTRATOR was produced by Unisphere Research and sponsored by Dell Software. Unisphere Research is the market research unit of
Unisphere Media, a division of Information Today, Inc., publishers of Database Trends and Applications magazine and the 5 Minute Briefing newsletters. To review abstracts of our past
reports, visit www.dbta.com/About_Us#Unisphere. Unisphere Media, 121 Chanlon Road, New Providence, NJ 07974; 908-795-3702.
DBAS’ RESPONSIBILITIES
Given the importance of data and databases to the overall
functioning and success of every organization, effective database
administration is critical. DBAs perform many tasks, and the
demands on their time have changed as database technology has
evolved and new capabilities have been introduced. Some tasks
that were once performed manually are now automated. And
many database administration tools have been introduced that
help DBAs perform their essential tasks.
Figure 16 shows the tasks DBAs perform that respondents
consider the most important. The results are not surprising.
The DBAs’ top responsibilities are maintenance, performance,
and configuration. In other words, DBAs must make sure that
the databases are up and running, performing well, and are
configured to function appropriately. Beyond that, DBAs must
be concerned with a wide range of tasks ranging from capacity
planning to security.
The way DBAs spend their work days largely aligns with
their perception of their most important responsibilities. (See
Figure 17.) Interestingly, however, DBAs may spend less time
on security issues than they do on supporting development even
though security is generally a higher priority. They also seem to
spend less time on data integration and capacity planning than
might be expected.
Given that DBAs view systems uptime and performance as
their two most important responsibilities, it is appropriate that
those are the two metrics by which they measure themselves.
Figure 18 shows the top five criteria by which DBAs evaluate their
own performance.
Although the way DBAs judge their performance is consistent
with what they perceive as their top priorities, they believe that
their managers evaluate them differently. As Figure 19 reveals,
survey respondents felt that the speed of resolving problems
was a more important issue for managers in evaluating DBA
performance than system performance, and system performance
was slightly more valued than system uptime.
Of course, the way DBAs spend their time changes as new
responsibilities are added, as new technology is incorporated
into the infrastructure both at the data management and data
administration levels, and as staffing changes and organizations
generally evolve. Figure 20 presents some of the granular tasks
DBAs perform and assesses which of those tasks now require
more time and which require less.
For most DBAs, the amount of time spent on specific tasks
is not changing much. But there are some notable exceptions.
More than 60% of the respondents indicated that they are
spending more time on performance tuning and more than 53%
said cloning or provisioning databases for test and development
required more attention. Very few tasks seem to have required
less attention. Indeed, the only tasks tabbed by more than 20%
as requiring more attention were verifying that all scheduled jobs
had run (22.08%), and verifying all instances are up (20.6%).
One approach to making a DBAs’ job more efficient is to
automate routine tasks. There are several different approaches
to automating tasks, including using third-party tools or writing
custom scripts. Figure 21 provides insight into which DBA tasks
are automated.
Clearly, at most organizations, many fundamental
administrative tasks are automated. More than 80% of the
respondents say that verifying that all the database instances are
up has been automated. And more than 70% report that verifying
all jobs have run, backups have been successful, and there is
adequate disk space, is currently automated as well. The tasks
that are most commonly performed manually are performance
tuning (78.85%) and provisioning or cloning databases (67.98%).
That finding is consistent with the earlier finding that those tasks
require an increasing amount of DBAs’ attention.
Finally, as more tasks are automated DBAs are sometimes
called on to do database development tasks as well. In Figure 22,
respondents indicated which development tasks they thought
required the most time, regardless of whether development was
done by a DBA or a database developer.
Even as new non-SQL-based technologies begin to gain
traction, SQL is still very much the primary focus for most DBAs
and database developers.
15. 15
THE REAL WORLD OF THE DATABASE ADMINISTRATOR was produced by Unisphere Research and sponsored by Dell Software. Unisphere Research is the market research unit of
Unisphere Media, a division of Information Today, Inc., publishers of Database Trends and Applications magazine and the 5 Minute Briefing newsletters. To review abstracts of our past
reports, visit www.dbta.com/About_Us#Unisphere. Unisphere Media, 121 Chanlon Road, New Providence, NJ 07974; 908-795-3702.
Maintenance (backup, alerts, 70.16%
integrity checks, defragmentation, etc.)
Performance (system and data availability, 68.55%
diagnostics, optimizing and tuning, etc.)
Configuration (adding features, patching, 56.45%
upgrading, etc.)
Change management 44.35%
(deploying schema changes, etc.)
Security (auditing, configuring, 41.13%
documenting, etc.)
Data integration (ETL, moving data, 33.06%
merging data, etc.)
Capacity planning (forecasting future 33.06%
workloads and system capacity needs,
identifying new technologies, etc.)
Supporting development efforts 33.06%
(creating test and development databases
and synchronizing them with production, etc.)
0 20 40 60 80 100
0 20 40 60 80 100
Figure 16: What do you consider the most important responsibilities
for DBAs?
16. 16
THE REAL WORLD OF THE DATABASE ADMINISTRATOR was produced by Unisphere Research and sponsored by Dell Software. Unisphere Research is the market research unit of
Unisphere Media, a division of Information Today, Inc., publishers of Database Trends and Applications magazine and the 5 Minute Briefing newsletters. To review abstracts of our past
reports, visit www.dbta.com/About_Us#Unisphere. Unisphere Media, 121 Chanlon Road, New Providence, NJ 07974; 908-795-3702.
Maintenance (backup, alerts, integrity 63.11%
checks, defragmentation, etc.)
Performance (system and data availability, 59.43%
diagnostics, optimizing and tuning, etc.)
Configuration (i.e., adding features, 46.31%
patching, upgrading, etc.)
Change Management (deploying schema 44.67%
changes, etc)
Supporting development efforts 31.56%
(creating test and development databases
and synchronizing them with production)
Database development (data modeling, 27.46%
programming, deploying code to production, etc.)
Security (auditing, configuring, 22.95%
documenting)
Data integration (data management, 22.95%
ETL, moving data, merging data)
0 20 40 60 80 100
0 20 40 60 80 100
Figure 17: To which of these responsibilities do you think DBAs typically
devote the most time?
17. 17
THE REAL WORLD OF THE DATABASE ADMINISTRATOR was produced by Unisphere Research and sponsored by Dell Software. Unisphere Research is the market research unit of
Unisphere Media, a division of Information Today, Inc., publishers of Database Trends and Applications magazine and the 5 Minute Briefing newsletters. To review abstracts of our past
reports, visit www.dbta.com/About_Us#Unisphere. Unisphere Media, 121 Chanlon Road, New Providence, NJ 07974; 908-795-3702.
System performance 72.95%
System uptime 67.62%
Project delivery time 32.38%
Efficiency in resolving pre-production 23.77%
issues such as identifying and fixing bugs
Efficiency in resolving post-production 20.49%
issues such as configuration problems
0 20 40 60 80 100
0 20 40 60 80 100
Figure 18: What are the most important metrics by which you measure
your performance?
Speed of issue resolution 59.84%
System performance 54.1%
System uptime 52.05%
Adherence to service-level agreements 34.43%
Capacity management 9.84%
0 20 40 60 80 100
0 20 40 60 80 100
Figure 19: What are the most important metrics by which your manager
measures your performance?
18. 18
THE REAL WORLD OF THE DATABASE ADMINISTRATOR was produced by Unisphere Research and sponsored by Dell Software. Unisphere Research is the market research unit of
Unisphere Media, a division of Information Today, Inc., publishers of Database Trends and Applications magazine and the 5 Minute Briefing newsletters. To review abstracts of our past
reports, visit www.dbta.com/About_Us#Unisphere. Unisphere Media, 121 Chanlon Road, New Providence, NJ 07974; 908-795-3702.
Figure 20: Among these responsibilities commonly assigned to DBAs, is
the amount of time you devote to each responsibility increasing,
decreasing, or staying the same?
Increasing Decreasing Staying the same
Verify all instances are up 24.89% 20.6% 54.51%
Inspect error logs for unusual events 29% 17.32% 53.68%
Verify that all scheduled jobs have run successfully 16.88% 22.08% 61.04%
Verify success of database backups 23.38% 19.48% 57.14%
Monitor disk space 30.3% 19.48% 50.22%
Review database size and growth settings 37.83% 12.61% 49.57%
Cloning or provision databases for test and 53.68% 10.39% 35.93%
development
Verify that replicated databases are synchronized 26.09% 13.91% 60%
Performance tuning for database workload 61.21% 4.31% 34.48%
(rewriting SQL statements, adding indexes, etc.)
19. 19
THE REAL WORLD OF THE DATABASE ADMINISTRATOR was produced by Unisphere Research and sponsored by Dell Software. Unisphere Research is the market research unit of
Unisphere Media, a division of Information Today, Inc., publishers of Database Trends and Applications magazine and the 5 Minute Briefing newsletters. To review abstracts of our past
reports, visit www.dbta.com/About_Us#Unisphere. Unisphere Media, 121 Chanlon Road, New Providence, NJ 07974; 908-795-3702.
Figure 21: Of the tasks that many DBAs perform, which are automated,
performed manually or not generally performed?
Automated Manual Not generally
performed
Verify all instances are up 81.14% 15.35% 3.51%
Inspect error logs for unusual events 46.49% 45.61% 7.89%
Verify that all scheduled jobs have run successfully 70.93% 23.35% 15.73%
Verify success of database backups 71.18% 25.33% 3.49%
Monitor disk space 72.49% 24.45% 3.06%
Review database size and growth settings 40.79% 50.88% 8.33%
Cloning or provision databases for test and 23.68% 67.98% 8.33%
development
Verify that replicated databases are synchronized 42.92% 36.28% 20.8%
Performance tuning for database workload 15.42% 78.85% 5.73%
(rewriting SQL statements, adding indexes, etc.)
20. 20
THE REAL WORLD OF THE DATABASE ADMINISTRATOR was produced by Unisphere Research and sponsored by Dell Software. Unisphere Research is the market research unit of
Unisphere Media, a division of Information Today, Inc., publishers of Database Trends and Applications magazine and the 5 Minute Briefing newsletters. To review abstracts of our past
reports, visit www.dbta.com/About_Us#Unisphere. Unisphere Media, 121 Chanlon Road, New Providence, NJ 07974; 908-795-3702.
Tuning SQL 73.48%
Writing and debugging code 39.57%
Editing and making code changes 32.61%
Querying 27.83%
Load testing 24.35%
Unit testing 11.74%
Re-factoring 10.87%
Other 3%
0 20 40 60 80 100
0 20 40 60 80 100
Figure 22: Regardless of who is specifically responsible for database
development, which of the following development tasks
do you feel occupies the most time?
21. 21
THE REAL WORLD OF THE DATABASE ADMINISTRATOR was produced by Unisphere Research and sponsored by Dell Software. Unisphere Research is the market research unit of
Unisphere Media, a division of Information Today, Inc., publishers of Database Trends and Applications magazine and the 5 Minute Briefing newsletters. To review abstracts of our past
reports, visit www.dbta.com/About_Us#Unisphere. Unisphere Media, 121 Chanlon Road, New Providence, NJ 07974; 908-795-3702.
THE FUTURE
The relational database has been at the foundation of large-scale
information management for several decades and should continue
to be so for the foreseeable future. That said, interesting new
information management, storage, and analytical technologies are
making their way into many enterprises and DBAs will play a role
in their implementation and use. At the same time, as companies
use more data types from more sources, both complexity and risk
are escalating. Both of those developments will present challenges
to DBAs. Figure 23 reveals what respondents believe will be the
most significant challenges facing DBAs over the next 3 years in
terms of the developments in data itself.
Managing data growth and improving security are on most
people’s radars as areas that need to be addressed in the future.
Beyond that, there is widespread disagreement about where DBAs
need to focus over the next several years. This variety of opinions
can be seen as evidence that we are heading into a period of change
and the demands those changes will place on DBAs is not yet clear.
The same wide array of opinions exists when respondents
are asked to anticipate the key changes in the data management
infrastructure over the next several years. As Figure 24 suggests,
no single technology or change has truly come into sharp focus.
No single technology or changes was tabbed by at least 50% of
the respondents.
Interestingly, in terms of new technologies, DBAs do not
believe that Hadoop and NoSQL are going to have the biggest
impact on their organizations over the next several years. They
are more focused on the continued growth of cloud computing
and virtualization. (See Figure 25.)
Obviously, changes in the data and data management
infrastructure will put pressure on DBAs and their organizational
teams. As Figure 26 shows, DBAs realize that they will have to
learn new technologies and they may have to do so in an era of
smaller budgets.
Change, of course, represents both opportunities and threats.
DBAs will be critical for enterprises to be able to maximize the
benefits of the opportunities and minimize the threats.
Over the next year, however, the most pressing items on the
agenda of DBAs will be more evolutionary than revolutionary.
When asked to identify their most important project for next
year, the most common answer was upgrading their database
systems or enterprise applications, followed by consolidating
their information infrastructure. That consolidation could
come as the result of an upgrade or move to the cloud, or it
could be independent of other projects. Cloud technology is
on the radars of many DBAs. Many would like to automate
more tasks associated with database administration. No single
project or project area emerged as a consensus issue from this
survey. However, one of the most challenging aspects of database
administration is that each setting is unique.
22. 22
THE REAL WORLD OF THE DATABASE ADMINISTRATOR was produced by Unisphere Research and sponsored by Dell Software. Unisphere Research is the market research unit of
Unisphere Media, a division of Information Today, Inc., publishers of Database Trends and Applications magazine and the 5 Minute Briefing newsletters. To review abstracts of our past
reports, visit www.dbta.com/About_Us#Unisphere. Unisphere Media, 121 Chanlon Road, New Providence, NJ 07974; 908-795-3702.
The overall growth of data 66.23%
(structured and unstructured)
Improving data security 55.26%
Implementing databases running 37.28%
on cloud
Managing multiple database platforms 35.96%
The proliferation of new sources for data 28.51%
The need to manage new data types 25.44%
Improving data quality 24.12%
The overall growth of unstructured data 23.68%
The overall growth of structured data 20.18%
If other, please specify 3%
0 20 40 60 80 100
0 20 40 60 80 100
Figure 23: In terms of data itself, over the next 3 years, what do you
anticipate will be the top challenges facing DBAs?
23. 23
THE REAL WORLD OF THE DATABASE ADMINISTRATOR was produced by Unisphere Research and sponsored by Dell Software. Unisphere Research is the market research unit of
Unisphere Media, a division of Information Today, Inc., publishers of Database Trends and Applications magazine and the 5 Minute Briefing newsletters. To review abstracts of our past
reports, visit www.dbta.com/About_Us#Unisphere. Unisphere Media, 121 Chanlon Road, New Providence, NJ 07974; 908-795-3702.
Incorporating cloud technologies 43.67%
Improving overall system performance 39.3%
Automating more tasks associated 38.86%
with database management
Increased complexity (heterogeneity) 38.43%
Incorporating non-relational data 37.12%
management technologies
Increasing overall system capacity 34.06%
Making data available to more 25.76%
stakeholders
0 20 40 60 80 100
0 20 40 60 80 100
Figure 24: In terms of the data management infrastructure, what do you think
will be the top challenges facing DBAs over the next few years?
Cloud 64.32%
Virtualization 48.02%
Big data 47.14%
High availability 33.48%
NoSQL 33.04%
Hadoop 29.96%
Consolidation 23.35%
IaaS (infrastructure-as-a-service) 21.15%
Agile development 19.38%
0 20 40 60 80 100
0 20 40 60 80 100
Figure 25: What technology trends do you think will have the most impact
on database administration over the next 3 years?
24. 24
THE REAL WORLD OF THE DATABASE ADMINISTRATOR was produced by Unisphere Research and sponsored by Dell Software. Unisphere Research is the market research unit of
Unisphere Media, a division of Information Today, Inc., publishers of Database Trends and Applications magazine and the 5 Minute Briefing newsletters. To review abstracts of our past
reports, visit www.dbta.com/About_Us#Unisphere. Unisphere Media, 121 Chanlon Road, New Providence, NJ 07974; 908-795-3702.
The need to need to learn new 53.51%
technologies
Shrinking IT budgets 49.12%
The need to manage more databases 46.05%
per DBA
The lack of trained personnel 37.72%
Shrinking IT staffs 32.46%
Not having the proper database 17.54%
management tools
The need to train more users 8.77%
0 20 40 60 80 100
0 20 40 60 80 100
Figure 26: In terms of database administration itself, over the next 3 years,
what do you think will be the top challenges facing DBAs?
25. 25
THE REAL WORLD OF THE DATABASE ADMINISTRATOR was produced by Unisphere Research and sponsored by Dell Software. Unisphere Research is the market research unit of
Unisphere Media, a division of Information Today, Inc., publishers of Database Trends and Applications magazine and the 5 Minute Briefing newsletters. To review abstracts of our past
reports, visit www.dbta.com/About_Us#Unisphere. Unisphere Media, 121 Chanlon Road, New Providence, NJ 07974; 908-795-3702.
CONCLUSION
While exciting new information management technologies
such as Hadoop and NoSQL are beginning to make inroads in
large companies, by and large, traditional database management
systems still represent the critical informational foundation in
most companies. DBAs are the front-line personnel maintaining
that foundation, responsible for ensuring that performance meets
the needs of the organization. With that in mind, several long-
term trends are still in place. DBAs are being asked to manage
more database instances and DBMSs from different platforms.
The amount of data under management continues to grow at
a crisp pace. And while some routine administrative tasks have
been automated, performance tuning, and provisioning are still
often done manually.
Perhaps as importantly, as the use of new technologies
grows, DBAs will be the ones responsible for integrating those
opportunities into their organizations. To that end, they have to
continue to learn new technologies and continue to find ways to
do more with less.
26. 26
THE REAL WORLD OF THE DATABASE ADMINISTRATOR was produced by Unisphere Research and sponsored by Dell Software. Unisphere Research is the market research unit of
Unisphere Media, a division of Information Today, Inc., publishers of Database Trends and Applications magazine and the 5 Minute Briefing newsletters. To review abstracts of our past
reports, visit www.dbta.com/About_Us#Unisphere. Unisphere Media, 121 Chanlon Road, New Providence, NJ 07974; 908-795-3702.
APPENDIX A
The following figures show the characteristics of the pool of respondents.
Database administrator (DBA) 48.03%
IT director or manager 19.65%
Database developer 4.37%
Analyst 3.49%
IT staff 2.62%
Other CEO 2.18%
Other C-level executive 1.75%
Project manager 1.75%
Chief information officer (CIO) 1.31%
DevOps engineer 1.31%
LOB director or manager 1.31%
Chief data officer (CDO) 0.44%
Other 11.79%
0 20 40 60 80 100
0 20 40 60 80 100
Figure 27: What is your primary job title?
27. 27
THE REAL WORLD OF THE DATABASE ADMINISTRATOR was produced by Unisphere Research and sponsored by Dell Software. Unisphere Research is the market research unit of
Unisphere Media, a division of Information Today, Inc., publishers of Database Trends and Applications magazine and the 5 Minute Briefing newsletters. To review abstracts of our past
reports, visit www.dbta.com/About_Us#Unisphere. Unisphere Media, 121 Chanlon Road, New Providence, NJ 07974; 908-795-3702.
IT services/consulting/system integration 18.86%
Financial services 12.28%
Government (all levels) 10.96%
Utility/telecommunications/transportation 8.33%
Software/application development 7.89%
Education (all levels) 7.89%
Manufacturing 7.89%
Retail/distribution 6.14%
Healthcare/medical 5.7%
Insurance 4.39%
Business or consumer services 2.19%
High-tech manufacturing 1.75%
Other 5.7%
0 20 40 60 80 100
0 20 40 60 80 100
Figure 28: What is your organization’s primary industry classification?
1 to 100 employees 11.35%
101 to 500 employees 13.97%
501 to 1,000 employees 10.48%
1,001 to 5,000 employees 24.45%
5,00 to 10,000 employees 13.1%
10,000 employees 24.02%
Don’t know/unsure 2.62%
0 20 40 60 80 100
0 20 40 60 80 100
Figure 29: Approximately how many employees (including all locations,
branches, and subsidiaries) are in your organization?