Big data introduction - Sogeti - Consulting Services - Business Technology - 20130628 v5
This is a small introduction to the topic Big Data and a small vision on how to enable a (big) company in using big data and embed it into the organisation.
Big Data Trends - WorldFuture 2015 ConferenceDavid Feinleib
David Feinleib's Big Data Trends presentation from the World Future Society's Annual Conference, WorldFuture 2015, held at the Hilton Union Square, San Francisco, California July 25, 2015.
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
Big Data Trends - WorldFuture 2015 ConferenceDavid Feinleib
David Feinleib's Big Data Trends presentation from the World Future Society's Annual Conference, WorldFuture 2015, held at the Hilton Union Square, San Francisco, California July 25, 2015.
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
What is big data ? | Big Data ApplicationsShilpaKrishna6
Big data is similar to ‘small data’ but bigger in size. It is a term that describes the large volume of data both structured and unstructured. Big data generates value from the storage and processing of very large quantities of digital information that cannot be analyzed with traditional computing techniques
Big data is a term that describes the large volume of data may be both structured and unstructured.
That inundates a business on a day-to-day basis. But it’s not the amount of data that’s important. It’s what organizations do with the data that matters.
Big Data and The Future of Insight - Future FoundationForesight Factory
As Big Data sweeps through consumer-facing businesses, we ask:
- If Big Data is truly a revolution, then what (and whom) will it eliminate or elevate?
- What value will still be derived from conventional market research and brand-building techniques?
- If every brand is backed by Big Data, can every brand prosper?
For more information please contact info@futurefoundation.net or visit www.futurefoundation.net
Looking at what is driving Big Data. Market projections to 2017 plus what is are customer and infrastructure priorities. What drove BD in 2013 and what were barriers. Introduction to Business Analytics, Types, Building Analytics approach and ten steps to build your analytics platform within your company plus key takeaways.
Data-Ed Webinar: Demystifying Big Data DATAVERSITY
We are in the middle of a data flood and we need to figure out how to tame it without drowning. Most of what has been written about Big Data is focused on selling hardware and services. But what about a Big Data Strategy that guides hardware and software decisions? While virtually every major organization is faced with the challenge of figuring out the approach for and the requirements of this new development, jumping into the fray hastily and unprepared will only reproduce the same dismal IT project results as previously experienced. Join Dr. Peter Aiken as he will debunk a number of misconceptions about Big Data as your un-typical IT project. He will provide guidance on how to establish realistic Big Data management plans and expectations, and help demonstrate the value of such actions to both internal and external decision makers without getting lost in the hype.
Takeaways:
- The means by which Big Data techniques can complement existing data management practices
- The prototyping nature of practicing Big Data techniques
- The distinct ways in which utilizing Big Data can generate business value
- Bigger Data isn’t always Better Data
Big Data Applications | Big Data Application Examples | Big Data Use Cases | ...Simplilearn
In this Big Data presentation, we will be discussing the Big data growth over the last few years followed by the various big data applications. We will look into the various sectors where big data is used such as weather forecast, healthcare, media and entertainment, logistics, travel & tourism and finally in the government & law enforcement sector.
We will be discussing how below industries are using Big Data presentation:
1. Weather forecast
2. Media and entertainment
3. Healthcare
4. Logistics
5. Travel n tourism
6. Government and law enforcement
What is this Big Data Hadoop training course about?
The Big Data Hadoop and Spark developer course have been designed to impart an in-depth knowledge of Big Data processing using Hadoop and Spark. The course is packed with real-life projects and case studies to be executed in the CloudLab.
What are the course objectives?
This course will enable you to:
1. Understand the different components of Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark
2. Understand Hadoop Distributed File System (HDFS) and YARN as well as their architecture, and learn how to work with them for storage and resource management
3. Understand MapReduce and its characteristics, and assimilate some advanced MapReduce concepts
4. Get an overview of Sqoop and Flume and describe how to ingest data using them
5. Create database and tables in Hive and Impala, understand HBase, and use Hive and Impala for partitioning
6. Understand different types of file formats, Avro Schema, using Arvo with Hive, and Sqoop and Schema evolution
7. Understand Flume, Flume architecture, sources, flume sinks, channels, and flume configurations
8. Understand HBase, its architecture, data storage, and working with HBase. You will also understand the difference between HBase and RDBMS
9. Gain a working knowledge of Pig and its components
10. Do functional programming in Spark
11. Understand resilient distribution datasets (RDD) in detail
12. Implement and build Spark applications
13. Gain an in-depth understanding of parallel processing in Spark and Spark RDD optimization techniques
14. Understand the common use-cases of Spark and the various interactive algorithms
15. Learn Spark SQL, creating, transforming, and querying Data frames
Learn more at https://www.simplilearn.com/big-data-and-analytics/big-data-and-hadoop-training
Big data course | big data training | big data classesNaviWalker
In your world of digitization, Data is an essential source. Businesses in various fields use this Data to get important ideas for their growth. Eventually, this creates a sense of urgency to start learning Big Data. By doing so, you can stay productive and solve real world problems.
Big Data helps to derive important business decisions. Furthermore, successful Big Data processing in huge industrial sectors has taught important lessons on various Big Data concepts.
Big Data training with various Big Data Analytics courses will help you master Data Analysis. In the present world, you have ample scope of becoming a Big Data Scientist. And also getting other Big Data job roles.
What is the impact of Big Data on Analytics from a Data Science perspective.
Presented at the Big Data and Analytics Summit 2014, Nasscom by Mamatha Upadhyaya.
Big Data Tutorial For Beginners | What Is Big Data | Big Data Tutorial | Hado...Edureka!
This Edureka Big Data tutorial helps you to understand Big Data in detail. This tutorial will be discussing about evolution of Big Data, factors associated with Big Data, different opportunities in Big Data. Further it will discuss about problems associated with Big Data and how Hadoop emerged as a solution. Below are the topics covered in this tutorial:
1) Evolution of Data
2) What is Big Data?
3) Big Data as an Opportunity
4) Problems in Encasing Big Data Opportunity
5) Hadoop as a Solution
6) Hadoop Ecosystem
7) Edureka Big Data & Hadoop Training
Big Data Characteristics And Process PowerPoint Presentation SlidesSlideTeam
We present you content-ready big data characteristics and process PowerPoint presentation that can be used to present content management techniques. It can be presented by IT consulting and analytics firms to their clients or company’s management. This relational database management PPT design comprises of 53 slides including introduction, facts, how big is big data, market forecast, sources, 3Vs and 5Vs small Vs big data, objective, technologies, workflow, four phases, types, information analytics process, impact, benefits, future, opportunities and challenges etc. Our data transformation PowerPoint templates are apt to present various topics such as information management concepts and technologies, transforming facts with intelligence, data analysis framework, data mining, technology platforms, data transfer and visualization, content management, Internet of things, data storage and analysis, information infrastructure, datasets, technology and cloud computing. Download big data characteristics and process PPT graphics to make an impressive presentation. Develop greater goodwill with our Big Data Characteristics And Process PowerPoint Presentation Slides. Folks feel friendlier towards you.
Introductory Big Data presentation given during one of our Sizing Servers Lab user group meetings. The presentation is targeted towards an audience of about 20 SME employees. It also contains a short description of the work packages for our BIg Data project proposal that was submitted in March.
This presentation introduces concepts of Big Data in a layman's language. Author does not claim the originality of the content. The presentation is made by compiling from various sources. Author does not claim copyrights or privacy issues.
Big data is exponentially rising in today's age of information and digital shrinkage. This presentation potentially clears the concept and revolving hype around it.
What is big data ? | Big Data ApplicationsShilpaKrishna6
Big data is similar to ‘small data’ but bigger in size. It is a term that describes the large volume of data both structured and unstructured. Big data generates value from the storage and processing of very large quantities of digital information that cannot be analyzed with traditional computing techniques
Big data is a term that describes the large volume of data may be both structured and unstructured.
That inundates a business on a day-to-day basis. But it’s not the amount of data that’s important. It’s what organizations do with the data that matters.
Big Data and The Future of Insight - Future FoundationForesight Factory
As Big Data sweeps through consumer-facing businesses, we ask:
- If Big Data is truly a revolution, then what (and whom) will it eliminate or elevate?
- What value will still be derived from conventional market research and brand-building techniques?
- If every brand is backed by Big Data, can every brand prosper?
For more information please contact info@futurefoundation.net or visit www.futurefoundation.net
Looking at what is driving Big Data. Market projections to 2017 plus what is are customer and infrastructure priorities. What drove BD in 2013 and what were barriers. Introduction to Business Analytics, Types, Building Analytics approach and ten steps to build your analytics platform within your company plus key takeaways.
Data-Ed Webinar: Demystifying Big Data DATAVERSITY
We are in the middle of a data flood and we need to figure out how to tame it without drowning. Most of what has been written about Big Data is focused on selling hardware and services. But what about a Big Data Strategy that guides hardware and software decisions? While virtually every major organization is faced with the challenge of figuring out the approach for and the requirements of this new development, jumping into the fray hastily and unprepared will only reproduce the same dismal IT project results as previously experienced. Join Dr. Peter Aiken as he will debunk a number of misconceptions about Big Data as your un-typical IT project. He will provide guidance on how to establish realistic Big Data management plans and expectations, and help demonstrate the value of such actions to both internal and external decision makers without getting lost in the hype.
Takeaways:
- The means by which Big Data techniques can complement existing data management practices
- The prototyping nature of practicing Big Data techniques
- The distinct ways in which utilizing Big Data can generate business value
- Bigger Data isn’t always Better Data
Big Data Applications | Big Data Application Examples | Big Data Use Cases | ...Simplilearn
In this Big Data presentation, we will be discussing the Big data growth over the last few years followed by the various big data applications. We will look into the various sectors where big data is used such as weather forecast, healthcare, media and entertainment, logistics, travel & tourism and finally in the government & law enforcement sector.
We will be discussing how below industries are using Big Data presentation:
1. Weather forecast
2. Media and entertainment
3. Healthcare
4. Logistics
5. Travel n tourism
6. Government and law enforcement
What is this Big Data Hadoop training course about?
The Big Data Hadoop and Spark developer course have been designed to impart an in-depth knowledge of Big Data processing using Hadoop and Spark. The course is packed with real-life projects and case studies to be executed in the CloudLab.
What are the course objectives?
This course will enable you to:
1. Understand the different components of Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark
2. Understand Hadoop Distributed File System (HDFS) and YARN as well as their architecture, and learn how to work with them for storage and resource management
3. Understand MapReduce and its characteristics, and assimilate some advanced MapReduce concepts
4. Get an overview of Sqoop and Flume and describe how to ingest data using them
5. Create database and tables in Hive and Impala, understand HBase, and use Hive and Impala for partitioning
6. Understand different types of file formats, Avro Schema, using Arvo with Hive, and Sqoop and Schema evolution
7. Understand Flume, Flume architecture, sources, flume sinks, channels, and flume configurations
8. Understand HBase, its architecture, data storage, and working with HBase. You will also understand the difference between HBase and RDBMS
9. Gain a working knowledge of Pig and its components
10. Do functional programming in Spark
11. Understand resilient distribution datasets (RDD) in detail
12. Implement and build Spark applications
13. Gain an in-depth understanding of parallel processing in Spark and Spark RDD optimization techniques
14. Understand the common use-cases of Spark and the various interactive algorithms
15. Learn Spark SQL, creating, transforming, and querying Data frames
Learn more at https://www.simplilearn.com/big-data-and-analytics/big-data-and-hadoop-training
Big data course | big data training | big data classesNaviWalker
In your world of digitization, Data is an essential source. Businesses in various fields use this Data to get important ideas for their growth. Eventually, this creates a sense of urgency to start learning Big Data. By doing so, you can stay productive and solve real world problems.
Big Data helps to derive important business decisions. Furthermore, successful Big Data processing in huge industrial sectors has taught important lessons on various Big Data concepts.
Big Data training with various Big Data Analytics courses will help you master Data Analysis. In the present world, you have ample scope of becoming a Big Data Scientist. And also getting other Big Data job roles.
What is the impact of Big Data on Analytics from a Data Science perspective.
Presented at the Big Data and Analytics Summit 2014, Nasscom by Mamatha Upadhyaya.
Big Data Tutorial For Beginners | What Is Big Data | Big Data Tutorial | Hado...Edureka!
This Edureka Big Data tutorial helps you to understand Big Data in detail. This tutorial will be discussing about evolution of Big Data, factors associated with Big Data, different opportunities in Big Data. Further it will discuss about problems associated with Big Data and how Hadoop emerged as a solution. Below are the topics covered in this tutorial:
1) Evolution of Data
2) What is Big Data?
3) Big Data as an Opportunity
4) Problems in Encasing Big Data Opportunity
5) Hadoop as a Solution
6) Hadoop Ecosystem
7) Edureka Big Data & Hadoop Training
Big Data Characteristics And Process PowerPoint Presentation SlidesSlideTeam
We present you content-ready big data characteristics and process PowerPoint presentation that can be used to present content management techniques. It can be presented by IT consulting and analytics firms to their clients or company’s management. This relational database management PPT design comprises of 53 slides including introduction, facts, how big is big data, market forecast, sources, 3Vs and 5Vs small Vs big data, objective, technologies, workflow, four phases, types, information analytics process, impact, benefits, future, opportunities and challenges etc. Our data transformation PowerPoint templates are apt to present various topics such as information management concepts and technologies, transforming facts with intelligence, data analysis framework, data mining, technology platforms, data transfer and visualization, content management, Internet of things, data storage and analysis, information infrastructure, datasets, technology and cloud computing. Download big data characteristics and process PPT graphics to make an impressive presentation. Develop greater goodwill with our Big Data Characteristics And Process PowerPoint Presentation Slides. Folks feel friendlier towards you.
Introductory Big Data presentation given during one of our Sizing Servers Lab user group meetings. The presentation is targeted towards an audience of about 20 SME employees. It also contains a short description of the work packages for our BIg Data project proposal that was submitted in March.
This presentation introduces concepts of Big Data in a layman's language. Author does not claim the originality of the content. The presentation is made by compiling from various sources. Author does not claim copyrights or privacy issues.
Big data is exponentially rising in today's age of information and digital shrinkage. This presentation potentially clears the concept and revolving hype around it.
Big Data Processing in the Cloud: A Hydra/Sufia Experiencerotated8
This presentation addresses the challenge of processing big data in a cloud-based data repository. Using the Hydra Project’s Hydra and Sufia ruby gems and working with the Hydra community, we created a special repository for the project, and set up background jobs. Our approach is to create the metadata with these jobs, which are distributed across multiple computing cores. This will allow us to scale our infrastructure out on an as-needed basis, and decouples automatic metadata creation from the response times seen by the user. While the metadata is not immediately available after ingestion, it does mean that the object is. By distributing the jobs, we can compute complex properties without impacting the repository server. Hydra and Sufia allowed us to get a head start by giving us a simple self deposit repository, complete with background jobs support via Redis and Resque.
Big Data Processing in the Cloud: a Hydra/Sufia Experience
Zhiwu Xie, Ph.D., Associate Professor and Technology Development Librarian, Center for Digital Research and Scholarship University Libraries, Virginia Tech
General introduction to Big Data terms and technologies: Velocity, Volume, Variety (3V) and Veracity (4V), NoSQL, Data Science, main data stores (key-value, column, document, graph), Elasticsearch, ...
Presentation of data.be products leveraging Big Data & Elasticsearch
Open Data Science Conference Big Data Infrastructure – Introduction to Hadoop...DataKitchen
The main objective of this workshop is to give the audience hands on experience with several Hadoop technologies and jump start their hadoop journey. In this workshop, you will load data and submit queries using Hadoop! Before jumping in to the technology, the Founders of DataKitchen review Hadoop and some of its technologies (MapReduce, Hive, Pig, Impala and Spark), look at performance, and present a rubric for choosing which technology to use when.
NOTE: To complete hands on poriton in the time allotted, attendees should come with a newly created AWS (Amazon Web Services) Account and complete the other prerequisites found in the DataKitchen blog <http: />.
Here is Matt Brender's presentation at Big Data TechCon centered on understanding how distributed systems play a role in Big Data.
Full description:
Whether you’re an experienced user of Hadoop or a recent convert to Spark, you recognize that data is powerful when stored and analyzed. Analysis, as a workload, can be contrasted with the initial creation and storage of that data. These “active” workloads are what generate the data we covet.
Understanding this persistence of data as workload requires an appreciation of distributed systems. We will explore what factors affect your choice in database technology and particularly how to prioritize the choice in core architectural underpinnings present in NoSQL designs. We will also explore what these technologies solve and suggestions for how to align them with your business objectives.
You’ll leave this session with an understanding of the basic principles of NoSQL architectural design and a deeper understanding of the considerations when identifying a persistence solution for your active workloads.
Very basic Introduction to Big Data. Touches on what it is, characteristics, some examples of Big Data frameworks. Hadoop 2.0 example - Yarn, HDFS and Map-Reduce with Zookeeper.
My talk at the Winter School on Big Data in Tarragona, Spain.
Abstract: We have made much progress over the past decade toward harnessing the collective power of IT resources distributed across the globe. In high-energy physics, astronomy, and climate, thousands work daily within virtual computing systems with global scope. But we now face a far greater challenge: Exploding data volumes and powerful simulation tools mean that many more--ultimately most?--researchers will soon require capabilities not so different from those used by such big-science teams. How are we to meet these needs? Must every lab be filled with computers and every researcher become an IT specialist? Perhaps the solution is rather to move research IT out of the lab entirely: to leverage the “cloud” (whether private or public) to achieve economies of scale and reduce cognitive load. I explore the past, current, and potential future of large-scale outsourcing and automation for science, and suggest opportunities and challenges for today’s researchers.
Author: Stefan Papp, Data Architect at “The unbelievable Machine Company“. An overview of Big Data Processing engines with a focus on Apache Spark and Apache Flink, given at a Vienna Data Science Group meeting on 26 January 2017. Following questions are addressed:
• What are big data processing paradigms and how do Spark 1.x/Spark 2.x and Apache Flink solve them?
• When to use batch and when stream processing?
• What is a Lambda-Architecture and a Kappa Architecture?
• What are the best practices for your project?
Big data nowadays is a new challenge to be managed, not as a barrier to grow up business. Data storages costs relatively is inexpensive, with more transactions generated from social media, machine, and sensors, data increased from pieces by pieces into pentabytes.
This slide explained what the challenges of Big Data (Volume, Velocity, and Variety) and give a solution how to managed them.
There are many tools that could help to solve the problems, but the main focus tools in this slide is Apache Hadoop.
Big Data for beginners, the main points you need to know. Simple answers to: What is Big Data? What are the benefits of Big Data? What is the future of Big Data?
Big Data - Introduction and Research Topics - for Dutch KadasterJust van den Broecke
Presentation (in Dutch) on Big Data (BD) given on Oct 10, 2013 for Dutch Kadaster. To provide an introduction on BD, what could be BD in the geospatial domain, what could be opportunities and research topics for Dutch Kadaster. A personal view, i.e. by no means that this represents opinions or positions of Dutch Kadaster. Just a clarification beyond the buzzword...
Data Strategy Design: An Open Source Toolbox & Method for Data Thinking. Datentreiber
Developing successful AI strategies & products is a complex and interdisciplinary effort. It requires a profound business, user, and data understanding and a skilled team of domain experts, product designers, and AI engineers. There is a proven way and a set of free tools that support your organization in mastering this challenge: it’s called Data Strategy Design and is used by dozens of companies and hundreds of business managers, product innovators, and data scientists around the world. You will also learn how to apply this method and tools for your AI projects.
Common Presentation from Datentreiber Martin Szugat and Design Thinking Expert Martijn Bakker for Data Brain Meetup on 8 Oktober 2020.
And here is the recording on youtube in case you missed it:
https://www.youtube.com/watch?v=U8EbR2gnl_o&feature=youtu.be
VU Amsterdam - Big data en datagedreven waardecreatie: valt er nog iets te ki...BigDataExpo
In zijn presentatie gaat Frans Feldberg in op het ‘Waarom, Wat, en Hoe’ van big data en datagedreven business model innovation. Hoe is de wereld, als het om data gaat, de laatste jaren veranderd? Waarom zijn big data, business analytics en kunstmatige intelligentie belangrijke digitale innovaties die hoog op menig managementagenda staat en waarom investeren organisaties aanzienlijk in big data en data science? Hoe kunnen organisaties waarde met data creëren door zowel het verbeteren van het bestaande business model als door nieuwe data-gedreven business modellen te ontwikkelen. Dit zijn vragen die in zijn presentatie beantwoord zullen worden.
DAS Webinar: Emerging Trends in Data Architecture – What’s the Next Big Thing?DATAVERSITY
With technological innovation and change occurring at an ever-increasing rate, it’s hard to keep track of what’s hype and what can provide practical value for your organization. Join this webinar to see the results of a recent DATAVERSITY® survey on Emerging Trends in Data Architecture, along with practical commentary and advice from industry expert Donna Burbank.
Big Data is a topic that in on the strategic agenda of almost every organization. The demand for Big Data professionals keeps growing, and there is already a shortage in capacity of qualified and skilled people in this domain. As a result, a war on talent for the most qualified people in the industry has begun.
Are you interested in the domain of Big Data and Data Science, but wondering where to start? In this webinar, a select panel of experts from the Big Data Framework, DAMA (Data Management Association) and training organizations will discuss the problems and opportunities presented by the explosion of Big Data which has taken place in the last two years.
The panel will discuss how to get started with Big Data, both from an enterprise point of view (through strategy, processes and technology) as well as an individual point of view (which skills and knowledge do you need). The panel will discuss practical information and tips that will help you to get started in the Big world of Big Data.
Panellists include: Andrew Smailes – Australian National President of the Data Management Association (DAMA), Vincent Marsi, Director at HiLogic, Jan-Willem Middelburg, VP Asia at Pink Elephant, Shane Johnson, Principal Consultant at ITSMHub and Lawrie Kirk, Business Development Manager in Australia and New Zealand.
Watch recording here: https://apmg-international.com/events/big-data-how-get-started
Enabling a Bimodal IT Framework for Advanced Analytics with Data VirtualizationDenodo
Watch: https://bit.ly/2FLc5I2
Being able to maintain a well managed and curated Data Warehouse, along with keeping up with all of the demands of a very sophisticated consumer group can be a challenge. The new user wants access to data, they want to experiment, fail fast and if they do find usable insights/algorithms they want them productionized. This puts pressure on an IT organization and pushes them closer to a Bimodal operation where the regular IT processes that are highly curated, well defined and managed contrast sharply with the demands of the more sophisticated user.
In the recently published TDWI Best Practices Report ,“Data Management for Advanced Analytics”, Philip Russom, DM for Advanced Analytics some of these newer requirements for the more sophisticated user are discussed in some length. How can IT support traditional demands around traditional BI and Reporting, whilst enabling the business with more demand for data and Advanced Analytics in mind?
Attend and learn:
- How data virtualization enables this Bi-Modal approach to Data Management.
- How data virtualization enables compelling use cases for data management and advanced analytics
- How we can achieve this important balance with process and technology.
Operationalizing the Buzz: Big Data 2013VMware Tanzu
The 2013 EMA/9sight Big Data research makes a clear case for the maturation of Big Data as a critical approach for innovative companies. This year’s survey went beyond simple questions of strategy, adoption and use to explore why and how companies are utilizing Big Data. This year’s findings show an increased level of Big Data sophistication between 2012 and 2013 respondents. An improved understanding of the “domains of data” drives this increased sophistication and maturity. Highly developed use of
Process-mediated, Machine-generated and Human-sourced information is prevalent throughout this year’s study.
Present european sdg summit template sdg roundtables_sitra_fibsSitra / Hyvinvointi
Sitra & Fibs Webinar at The European SDG Summit 26 October 2020: The New Dimension for CSR - Data as part of Corporate Social Responsibility
Heli Parikka, Sitra
Tiina Härkönen, Sitra
Mikko Merisaari, Funtos Oy
DAS Slides: Self-Service Reporting and Data Prep – Benefits & RisksDATAVERSITY
As more organizations see the value of becoming data-driven, an increasing number of business stakeholders want to become more actively involved in the reporting and preparation of critical business data. Tools and technologies have evolved to support this desire, and the ability to manage and analyze vast amounts of disparate data has become more accessible than ever before. With this increased visibility and usage of data, the need for data quality, metadata context, lineage and audit, and other core fundamental best practices is greater than ever.
How can an effective architecture & governance model be created that supports both business agility, as well as long-term sustainability and risk reduction? Where do these responsibilities lie between business and IT stakeholders? Join our panel of experts as they discuss the latest best practices, architectures, and tools that support self-service reporting and data prep to maximize benefits while at the same time reducing risk.
Application of Big Data in Enterprise Managementijtsrd
With the continuous development of information technology, enterprises have gradually entered the era of big data. How to analyze the complex data and find out the useful information to promote the development of enterprises is becoming more and more important in the modernization of science and technology. This paper expounds the importance and existing problems of big data application in enterprise management, and briefly analyzes and discusses its application in enterprises and its future development direction and trend. With the rapid development of Internet of things, cloud computing and other information technology, the world ushered in the era of big data. It has become a trend to promote the deep integration of Internet, big data, artificial intelligence and real economy. Due to the rapid development of economy, the amount of data information generated in the process of consumption and production is very large. Under the traditional management mode, enterprises cannot meet the needs of the current social and economic development. However, the application of big data technology in enterprises can achieve better analysis and Research on these data information, so as to provide reliable data basis for enterprises to carry out various business management decisions. Feng GUO | Hui-lin QIN "Application of Big Data in Enterprise Management" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, URL: https://www.ijtsrd.compapers/ijtsrd43622.pdf Paper URL: https://www.ijtsrd.commanagement/business-economics/43622/application-of-big-data-in-enterprise-management/feng-guo
Sharing the story on how connected architecture came into being. The thought process that has led up to a people perspective on data architecture and what it takes to create a sustainable data landscape.
This presentation was given at the Free Frogs customer day in May 2018.
Similar to Big data introduction - Big Data from a Consulting perspective - Sogeti (20)
Defining antifragility and the application on organisation design @ DADD 2011...Edzo Botjes
The .com crisis of 2000, the financial crisis of 2008 and the COVID-19 crisis of 2020 show us the importance for organisations to become resilient or even antifragile to survive (unexpected) external stressors. Research states that the current VUCA world will expose enterprises to more and more stressors. Resilience is the way a system bounces back from impact by a stressor. Antifragile is the way a system improves from impact by a stressor. In his master thesis Edzo combines (1) literature research on resilience with (2) the antifragile attributes found in the literature and (3) variety engineering into one model, an Extended Antifragile Attribute List (EAAL). Enabling the leadership of an organisation to determine if the organisation should aim to be antifragile or to be a specific type of resilient. The presentation consists of the EAAL model, theory and practical application via an interactive discussion on how to recognize the context and how to adjust your behaviour as an architect.
Is a secure cloud possible or an neverending rat-race? We know the debate around “The Cloud Is Just Someone Else's Computer.” The cloud is an technology ecosystem that provided us so much more options than time-share mainframe, multi-user unix systems or patterns as CORBA and RPC could provide us. I'll introduce you into the concept of Variety known from Requisite Variety. One of the key attributes of an antifragile IT systems. This concept will help you in design decision on the risk mitigation in the cloud.
Attributes relevant to antifragile organizations - Paper - IEEE CBI 2021 2021...Edzo Botjes
Presentation of paper titled: Attributes relevant to antifragile organizations @ IEEE CBI 2021 - 09
DOI: not-yet-available
Slides: https://www.edzob.com/page/slideshare/
Discord chat: https://discord.gg/2wZzNWaCzv
Find the hidden easter egg(s) and share them in the comments.
Authors: Edzo Botjes ∗ , Martin van den Berg † , Bas van Gils ‡ , § and Hans Mulder §
∗ Xebia, Hilversum, The Netherlands
† Hogeschool Utrecht, Utrecht, The Netherlands
‡ Strategy Alliance, Amersfoort, The Netherlands
§ Antwerp Management School, Antwerpen, Belgium
Paper abstract —Organizations operate in a socio-economic context,
and alignment with this context is key for business success. The
rate of change and impact of these changes on the operating
model of the organization appears to be increasing. Major trends
are the aftermath of the financial crisis of 2008, the “VUCA”
aspects (volatility, uncertainty, complexity, ambiguity), and the
Covid-pandemic. The challenge for organizations is to become
resilient or even antifragile to survive (unexpected) external
stressors.
Antifragility refers to a class of systems that do not deteriorate
(fragile) or withstand (robust) stressors, but actually improve as
a result of stressors. Our objective is to find attributes that are
relevant for an organization to be(come) antifragile. The list of
attributes found is based on an extensive survey of available
literature, and is validated with domain experts and leaders of
various organizations. We dub the list of attributes found the
Extended Antifragile Attribute List (EAAL).
Considering the current economic and social impact on organi-
zations and people of the Covid-pandemic, the EAAL is relevant
as well timely. The EAAL turns out to be extensive and holistic.
We consider the EAAL to be a stepping stone in setting the scene
of the domain of antifragility.
We suspect that the EAAL might also be applied to generic
system design including technology infrastructure and software
systems. This exploration is part of future research
Workshop on Presentation skills
AIHACKCOVID
There have been millions of deaths and recoveries worldwide from COVID-19. If we work together and learn from worldwide data on the pandemic, we can prevent or better manage future pandemics.
This June, we are empowering the Artificial Intelligence and Medical community of Northern NL to hack the COVID-19 crisis together and to advise Dutch policy makers.
Using machine learning techniques, you are are invited to explore a worldwide data set of COVID-19 hospitalizations, policy decisions, and more to find patterns that can hack our crisis.
It's good to know what resilience is. It's better to know what your organisation can get out of it!
In this webinar, I will discuss how to utilize and “hack” resilience to enforce luck onto ourselves.
Presented at the Xebia XKE of 2021-01-19.
Viable Systems Model is A tool for diagnosing if a system can stay alive. This is a short presentation (30 min) into the model. Goal is to introduce VSM and start internal dialog on the applicability and relevance.
Open source an origin story to freedom covers the origin on open source, the two main currents in the landscape and the options we now have how to go forward.
Presentation held for 100 IT Coordinators of the secundary education.. About that the easy step to improvement is, asking the why question.. why do we do this.. gtf
What the analyst can learn from spaghetti sausEdzo Botjes
When you watch the ted talk from malcolm gladwell and combine it with some theory, we can ask ourself. what can we learn from it.
People don't know what they want and People don't know what they don't know. Maybe the interviewing and analyzing method isn't that great.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
4. 4Big Data a Start | People Consulted | Amersfoort | 2013 05 28 |
People Consulted
Big Data experts
IT
Data Experts
Business
Information
Architects
Big Data experts
Business
Data Experts
Information
Management
Architects
Business
Big Data experts
VINT
Big Data expert
R20
Desk Research
5. 5Big Data a Start | Content | Amersfoort | 2013 05 28 |
What were the questions from
The management team?
Content
Conclusion / Answers
Actions to take as MT
6. 6Big Data a Start | What were the questions | Amersfoort | 2013 05 28 |
What were the questions
• Question 1
- What is Big Data?
• Question 2
- Big Data in current organization?
• Question 3
- What is the future role of the Information
Management department in the subject
Big Data?
7. 7Big Data a Start | Content | Amersfoort | 2013 05 28 |
Content
Conclusion / Answers
Actions to take as MT
What were the questions from
The management team?
8. 8Big Data a Start | What were the questions | Amersfoort | 2013 05 28 |
Why Big Data is a MT subject
Source: http://www.myforrester.net/big-data-webinar ; http://www.airlineleader.com/pdfs/Airline%20Leader%20Issue%2014.pdf
9. 9Big Data a Start | What were the questions | Amersfoort | 2013 05 28 |
Why Big Data is a MT subject
Source: https://www.bmelv.de/SharedDocs/Downloads/Verbraucherschutz/Internet-Telekommunikation/SaferInternetDay2013Ksker.pdf?__blob=publicationFile page 14
“Big Data, was ist das?", Dr. Holger Kisker, VP and Research Director Forrester. February 2013
10. 10Big Data a Start | What is data | Amersfoort | 2013 05 28 |
What is data / information ?
11. 11Big Data a Start | What is data | Amersfoort | 2013 05 28 |
From data to wisdom
Source: http://blog.vint.sogeti.com/wp-content/uploads/2012/07/VINT-Sogeti-on-Big-Data-1-of-4-Creating-Clarity.pdf page 6
"Creating clarity with Big Data", ViNT research report 1 of 4 by Jaap Bloem. et al. June 2012
12. 12Big Data a Start | What is data | Amersfoort | 2013 05 28 |
Role of insight
Source: http://blog.vint.sogeti.com/wp-content/uploads/2012/07/VINT-Sogeti-on-Big-Data-1-of-4-Creating-Clarity.pdf page 8
"Creating clarity with Big Data", ViNT research report 1 of 4 by Jaap Bloem. et al. June 2012
Source: http://cci.uncc.edu/sites/cci.uncc.edu/files/media/pdf_files/MIT-SMR-IBM-Analytics-The-New-Path-to-Value-Fall-2010.pdf page 4
13. 13Big Data a Start | Definition | Amersfoort | 2013 05 28 |
Definition of Big Data ?
14. 14Big Data a Start | Definition | Amersfoort | 2013 05 28 |
The Attack of the exponentials
Source: http://www.slideshare.net/medriscoll/driscoll-strata-buildingdatastartups25may2011clean slide 4
"Building Data Start-ups: Fast, Big and Focused" by Michael E. Driscoll CTO Metamarkets, May 2011
15. 15Big Data a Start | Definition | Amersfoort | 2013 05 28 |
3 V’s that define Big Data (or 4?)
VALUE
Source: http://www.slideshare.net/multiscope/data-pioneers-sander-duivestein-vint-future-of-data slide 9
“The future of data” by Sander Duivestein , June 2012
16. 16Big Data a Start | Definition | Amersfoort | 2013 05 28 |
Big Data definition at Goldman Sachs et al.
BIG DATA
==
Transaction
+
Interaction
+
Observation
Source: http://hortonworks.com/blog/7-key-drivers-for-the-big-data-market/
"7 Key Drivers for the Big Data Market" by Shaun Connolly at the Goldman Sachs Cloud Conference May 2012
17. 17Big Data a Start | Definition | Amersfoort | 2013 05 28 |
Big Data Definition by Edzo
BIG DATA
==
Real time data
+
Real time analysis
(graph data)
+
Real time reaction
(feedback loop)
Source: Edzo Botjes
18. 18Big Data a Start | Examples | Amersfoort | 2013 05 28 |
Examples of the 3 V's
19. 19Big Data a Start | Examples | Amersfoort | 2013 05 28 |
Examples of Size and Source
Source: http://hortonworks.com/blog/7-key-drivers-for-the-big-data-market/
Source: http://blog.vint.sogeti.com/wp-content/uploads/2012/07/VINT-Sogeti-on-Big-Data-1-of-4-Creating-Clarity.pdf
20. 20Big Data a Start | Examples | Amersfoort | 2013 05 28 |
Examples of Big Data Analytics
Source: http://blog.vint.sogeti.com/wp-content/uploads/2012/07/VINT-Sogeti-on-Big-Data-1-of-4-Creating-Clarity.pdf page 18
"Creating clarity with Big Data", ViNT research report 1 of 4 by Jaap Bloem et al.. June 2012
21. 21Big Data a Start | Examples | Amersfoort | 2013 05 28 |
Examples Big Data
22. 22Big Data a Start | Examples | Amersfoort | 2013 05 28 |
Examples of Big Data in the real life
Source:http://www.computerworld.com/s/article/9233587/Barack_Obama_39_s_Big_Data_won_the_US_election http://www.infoworld.com/d/big-data/the-real-story-of-how-big-data-analytics-helped-obama-win-212862
http://www.forbes.com/sites/kashmirhill/2012/02/16/how-target-figured-out-a-teen-girl-was-pregnant-before-her-father-did/ http://commons.wikimedia.org/wiki/File:Target_logo.svg http://www.rfgen.com/blog/bid/285148/Tesco-Improves-Supply-Chain-with-Big-Data-Automated-Data-
Collection http://www.computerweekly.com/news/2240184482/Tesco-uses-big-data-to-cut-cooling-costs-by-up-to-20m http://img.dooyoo.co.uk/GB_EN/orig/0/7/7/7/3/777389.jpg
23. 23Big Data a Start | Examples | Amersfoort | 2013 05 28 |
Big Data ready?
24. 24Big Data a Start | Examples | Amersfoort | 2013 05 28 |
Your Big Data profile: what does that look like?
Big Data is concerned with exceptionally large, often widespread bundles of
semi structured or unstructured data. In addition, they are often incomplete
and not readily accessible.
“Exceptionally large” means the following, measured against the
extreme boundaries of current standard it and relational databases:
petabytes of data or more, millions of people or more, billions of records or
more, and a complex combination of all these.
With fewer data and greater complexity, you will encounter a serious Big
Data challenge, certainly if your tools, knowledge and expertise are not fully
up to date. Moreover, if this is the case, you are not prepared for future data
developments. Semi-structured or unstructured means that the connections
between data elements are not clear, and probabilities will have to be
determined.
Further to read:
B. Ten Big Data management challenges: what are your issues?
C. Five requirements for your Big Data project: are you ready?
Source: http://blog.vint.sogeti.com/wp-content/uploads/2012/07/VINT-Sogeti-on-Big-Data-1-of-4-Creating-Clarity.pdf page 18
"Creating clarity with Big Data", ViNT research report 1 of 4 by Jaap Bloem et al. June 2012
Are you Big
Data ready?
Or to big a
leap?
“Big”
25. 25Big Data a Start | Tips | Amersfoort | 2013 05 28 |
Most important Tip (s)
26. 26Big Data a Start | Tips | Amersfoort | 2013 05 28 |
Tips
• Never, Ever, start without a Business Case and thus a
business sponsor.
• Added value of Big Data is combination of “External”
Sources. Think outside the box, outside your silo.
• Maturity is key.
- Start with identifying
- then go optimizing, scale to BI, BI++ and
- then to real time added value Big Data
feedback loops
27. 27Big Data a Start | Tips | Amersfoort | 2013 05 28 |
Maturity (Big Data is young and quick)
The notion that opportunities to capitalize on Big Data are simply
lying there, ready to be seized, is echoing everywhere. In 2011, the
McKinsey Global Institute called Big Data “the next frontier for
innovation, competition, and productivity” and the Economist
Intelligence Unit spoke unequivocally of “a game-changing asset.”
These are quotes taken from titles of two directive reports on Big
Data, a topical theme that is developing vigorously, and about
which the last word has certainly not been uttered.
McKinsey states it very explicitly:
This research by no means represents the final word on big data;
instead, we see it as a beginning. We fully anticipate that this is a
story that will continue to evolve as technologies and techniques
using big data develop and data, their uses, and their economic
benefits grow (alongside associated challenges and risks).
•“Innovation”
•“Competition”
•“Productivity”
Source: http://blog.vint.sogeti.com/wp-content/uploads/2012/07/VINT-Sogeti-on-Big-Data-1-of-4-Creating-Clarity.pdf page 18
"Creating clarity with Big Data", ViNT research report 1 of 4 by Jaap Bloem et al. June 2012
28. 28Big Data a Start | Questions | Amersfoort | 2013 05 28 |
What were the questions
• Question 1
- What is Big Data?
• Question 2
- Big Data in current organization?
• Question 3
- What is the future role of the Information
Management department in the subject
Big Data?
29. 29Big Data a Start | Current Organization | Amersfoort | 2013 05 28 |
Big data in current organization
CRM
Internal R&D
Internal BI
Social Media
Data
Virtualization
30. 30Big Data a Start | Questions | Amersfoort | 2013 05 28 |
What were the questions
• Question 1
- What is Big Data?
• Question 2
- Big Data in current organization?
• Question 3
- What is the future role of the Information
Management department in the subject
Big Data?
31. 31Big Data a Start | Role | Amersfoort | 2013 05 28 |
Vision / Role
32. 32Big Data a Start | Role | Amersfoort | 2013 05 28 |
Information Management Role
be an advising guide
Bring together
Create
innovation environment
Bring
success to production
33. 33Big Data a Start | Role | Amersfoort | 2013 05 28 |
Information Management Role
Facilitate Execute
Be a leader
Bring together
Create
innovation environment
Bring
success to production
Source:
http://www.alfredoartist.com/Optimized%20Images/Rodriguez-InSearchOfGold.jpg
http://resources1.news.com.au/images/2011/07/27/1226102/848013-gold-prospecting.jpg
http://www.refinedinvestments.com/wp-content/uploads/2012/10/gold-mining400x282.jpg
http://en.rockscrusher.com/wp-content/uploads/2011/04/gold-mining-plant.jpg
34. 34Big Data a Start | Role | Amersfoort | 2013 05 28 |
Information Management Role
Not the Information Management Role
1.Employ Data scientists
2.Develop new data analyses technique’s
3.Be a business sponsor
Information Management Role
1.Facilitate the gold finding process (POCs)
Bring data scientist in touch with business
2.Be owner of the gold mining process (projects)
3.Have and Execute a vision on data governance and data
virtualization. (reduce future costs on projects, POCs and
changes etc.)
35. 35Big Data a Start | Questions | Amersfoort | 2013 05 28 |
What were the questions
• Question 1
- What is Big Data?
• Question 2
- Big Data in current organization?
• Question 3
- What is the future role of the Information
Management division in the subject
Big Data?
36. 36Big Data a Start | Content | Amersfoort | 2013 05 28 |
Content
Conclusion / Answers
Actions to take as MT
What were the questions from
The management team?
37. 37Big Data a Start | Actions | Amersfoort | 2013 05 28 |
Big Data Actions
Data Board
Data Governance
Data Virtualization
Create a Network
38. 38Big Data a Start | Actions | Amersfoort | 2013 05 28 |
Goals of the Data board
• Role of a Steering Committee / Governance
• Once a month (2 months) meeting
• Advice to POCs, brainstorm for POCs, Assist
breaking silos, create a platform for governance
issues
(Possible KPI.. 3 POCs per year?)
• Great Variety inside Organization and outside (for
example a professor, young people, R&D and
business and more experienced internal employees)
39. 39Big Data a Start | Actions | Amersfoort | 2013 05 28 |
Subjects – Data Governance
• Where is what data ?
• Who owns the data ?
• Who owns the application that stores the data ?
• Who can access the data ?
• Who is responsible of data quality (and how) ?
• What are the legal implications and boundaries ?
40. 40Big Data a Start | Actions | Amersfoort | 2013 05 28 |
Subjects – Data Virtualization
• Future enormous cost reduction
• Improvement of MI
• Faster data centric solution
• Lower cost of projects
Source: http://res.sys-con.com/story/may11/1849158/data%20virt%20image_0.jpg
41. 41Big Data a Start | Actions | Amersfoort | 2013 05 28 |
Subjects – Create a Network
Create connections with and between:
• Universities
• External experts / stakeholders
• (Small) specialized companies
• Internal experts / stakeholders
Source: http://learnthat.com/files/2008/06/people-network1.jpg
42. 42Big Data a Start | Content | Amersfoort | 2013 05 28 |
Content
Conclusion / Answers
Actions to take as MT
What were the questions from
The management team?
43. 43Big Data a Start | Actions | Amersfoort | 2013 05 28 |
Big Data in the Enterprise
Data Board
Data Governance
Data Virtualization
Create a network
Facilitate Execute
Kopieer onderstaande regel in de adresregel van je browser voor de gebruikershandleiding van deze template: https://einstein.sogeti.nl/sites/einstein.sogeti.nl/files/page_attachments/PP%20handleiding%20130318.pdf