We are in the middle of a data rush. When you are right in the center of a storm, it can seem overwhelming. Where should I start? What do I need to think about? What is the best long-term bet? But don’t forget that more data should mean great news. More data should mean more insight, more guidance, and more strategic direction. However, more data doesn’t automatically rally your entire business around common goals and insights. You need a platform and architecture that can support a thriving, analytic-driven business culture that embraces a pervasive analytics strategy.
Breakout: Operational Analytics with HadoopCloudera, Inc.
Operationalizing models and responding to large volumes of data, fast, requires bolt on systems that can struggle with processing (transforming the data), consistency (always responding to data), and scalability (processing and responding to large volumes of data). If the data volume become too large, these traditional systems fail to deliver their responses resulting in significant losses to organizations. Join this breakout to learn how to overcome the roadblocks.
The Transformation of your Data in modern IT (Presented by DellEMC)Cloudera, Inc.
Organizations have a wealth of data contained within the existing infrastructures. At DellEMC we’re helping customers remove the barriers of legacy datastores and transforming the customer experience in the modern datacentre. Learn how to unshackle the valuable data inside your existing data warehouse, leverage new techniques, applications and technology to enhance the financial impact of all your data sources
Cloudera Federal Forum 2014: The Building Blocks of the Enterprise Data HubCloudera, Inc.
Chief Technologist, Office of the CTO at Cloudera Eli Collins, shares the story of the enterprise data hub and how it relates to the enterprise data warehouse.
Put Alternative Data to Use in Capital Markets Cloudera, Inc.
Alternative data for capital markets, such as satellite imagery, logistics data, and social media feeds, has been getting a lot of attention recently. Like any trending topic, its uses and benefits can be hyped up a bit but if the right plumbing and creativity is in place, those benefits can be realized.
3 things to learn:
* Examples of alt data use cases, sources, and recent market trends
* Why a big data platform that facilitates self service and collaboration is critical in monetizing alternative data
* How alternative data can be applied to enhance current processes (Demo)
Enterprise Data Hub: The Next Big Thing in Big DataCloudera, Inc.
If you missed Strata + Hadoop World, you missed quite a bit. This year's event was packed with Big Data practitioners across industries who shared their experiences and how they are driving new innovations like never before. Just because you weren't there, doesn't mean you missed out.
In this session, we'll touch on a few of the key highlights from the show, including:
Key trends in Big Data adoption
The enterprise data hub
How the enterprise data hub is used in practice
Optimized Data Management with Cloudera 5.7: Understanding data value with Cl...Cloudera, Inc.
Across all industries, organizations are embracing the promise of Apache Hadoop to store and analyze data of all types, at larger volumes than ever before possible. But to tap into the true value of this data, organizations need to manage this data and its subsequent metadata to understand its context, see how it’s changing, and take actions on it.
Cloudera Navigator is the only integrated data management and governance for Hadoop and is designed to do exactly this. With Cloudera 5.7, we have further expanded the capabilities in Cloudera Navigator to make it even easier to understand your data and maintain metadata consistency as it moves through Hadoop.
Breakout: Operational Analytics with HadoopCloudera, Inc.
Operationalizing models and responding to large volumes of data, fast, requires bolt on systems that can struggle with processing (transforming the data), consistency (always responding to data), and scalability (processing and responding to large volumes of data). If the data volume become too large, these traditional systems fail to deliver their responses resulting in significant losses to organizations. Join this breakout to learn how to overcome the roadblocks.
The Transformation of your Data in modern IT (Presented by DellEMC)Cloudera, Inc.
Organizations have a wealth of data contained within the existing infrastructures. At DellEMC we’re helping customers remove the barriers of legacy datastores and transforming the customer experience in the modern datacentre. Learn how to unshackle the valuable data inside your existing data warehouse, leverage new techniques, applications and technology to enhance the financial impact of all your data sources
Cloudera Federal Forum 2014: The Building Blocks of the Enterprise Data HubCloudera, Inc.
Chief Technologist, Office of the CTO at Cloudera Eli Collins, shares the story of the enterprise data hub and how it relates to the enterprise data warehouse.
Put Alternative Data to Use in Capital Markets Cloudera, Inc.
Alternative data for capital markets, such as satellite imagery, logistics data, and social media feeds, has been getting a lot of attention recently. Like any trending topic, its uses and benefits can be hyped up a bit but if the right plumbing and creativity is in place, those benefits can be realized.
3 things to learn:
* Examples of alt data use cases, sources, and recent market trends
* Why a big data platform that facilitates self service and collaboration is critical in monetizing alternative data
* How alternative data can be applied to enhance current processes (Demo)
Enterprise Data Hub: The Next Big Thing in Big DataCloudera, Inc.
If you missed Strata + Hadoop World, you missed quite a bit. This year's event was packed with Big Data practitioners across industries who shared their experiences and how they are driving new innovations like never before. Just because you weren't there, doesn't mean you missed out.
In this session, we'll touch on a few of the key highlights from the show, including:
Key trends in Big Data adoption
The enterprise data hub
How the enterprise data hub is used in practice
Optimized Data Management with Cloudera 5.7: Understanding data value with Cl...Cloudera, Inc.
Across all industries, organizations are embracing the promise of Apache Hadoop to store and analyze data of all types, at larger volumes than ever before possible. But to tap into the true value of this data, organizations need to manage this data and its subsequent metadata to understand its context, see how it’s changing, and take actions on it.
Cloudera Navigator is the only integrated data management and governance for Hadoop and is designed to do exactly this. With Cloudera 5.7, we have further expanded the capabilities in Cloudera Navigator to make it even easier to understand your data and maintain metadata consistency as it moves through Hadoop.
Evolution from Apache Hadoop to the Enterprise Data Hub by Cloudera - ArabNet...ArabNet ME
A new foundation for the Modern Information Architecture.
Speaker: Amr Awadallah, CTO & Cofounder, Cloudera
Our legacy information architecture is not able to cope with the realities of today's business. This is because it is not able to scale to meet our SLAs due to separation of storage and compute, economically store the volumes and types of data we currently confront, provide the agility necessary for innovation, and most importantly, provide a full 360 degree view of our customers, products, and business. In this talk Dr. Amr Awadallah will present the Enterprise Data Hub (EDH) as the new foundation for the modern information architecture. Built with Apache Hadoop at the core, the EDH is an extremely scalable, flexible, and fault-tolerant, data processing system designed to put data at the center of your business.
Manufacturers have an abundance of data, whether from connected sensors, plant systems, manufacturing systems, claims systems and external data from industry and government. Manufacturers face increased challenges from continually improving product quality, reducing warranty and recall costs to efficiently leveraging their supply chain. For example, giving the manufacturer a complete view of the product and customer information integrating manufacturing and plant floor data, with as built product configurations with sensor data from customer use to efficiently analyze warranty claim information to reduce detection to correction time, detect fraud and even become proactive around issues requires a capable enterprise data hub that integrates large volumes of both structured and unstructured information. Learn how an enterprise data hub built on Hadoop provides the tools to support analysis at every level in the manufacturing organization.
Is your big data journey stalling? Take the Leap with Capgemini and ClouderaCloudera, Inc.
Transitioning to a Big Data architecture is a big step; and the complexity of moving existing analytical services onto modern platforms like Cloudera, can seem overwhelming.
Introducing the data science sandbox as a service 8.30.18Cloudera, Inc.
How can companies integrate data science into their businesses more effectively? Watch this recorded webinar and demonstration to hear more about operationalizing data science with Cloudera Data Science Workbench on Cazena’s fully-managed cloud platform.
The Vortex of Change - Digital Transformation (Presented by Intel)Cloudera, Inc.
The vortex of change continues all around us – inside the company, with our customers and partners. A new norm is upon us. Business models are being turned upside down – the hunters now the hunted, global equalization – size is no longer a guarantee of success. The innovative survive and thrive…the nervous and slow go under...what does all this change means for you? Find out how does Intel’s strengths help our customers in this world of change.
Extending Cloudera SDX beyond the PlatformCloudera, Inc.
Cloudera SDX is by no means no restricted to just the platform; it extends well beyond. In this webinar, we show you how Bardess Group’s Zero2Hero solution leverages the shared data experience to coordinate Cloudera, Trifacta, and Qlik to deliver complete customer insight.
Better Together: The New Data Management OrchestraCloudera, Inc.
To ingest, store, process and leverage big data for maximum business impact requires integrating systems, processing frameworks, and analytic deployment options. Learn how Cloudera’s enterprise data hub framework, MongoDB, and Teradata Data Warehouse working in concert can enable companies to explore data in new ways and solve problems that not long ago might have seemed impossible.
Gone are the days of NoSQL and SQL competing for center stage. Visionary companies are driving data subsystems to operate in harmony. So what’s changed?
In this webinar, you will hear from executives at Cloudera, Teradata and MongoDB about the following:
How to deploy the right mix of tools and technology to become a data-driven organization
Examples of three major data management systems working together
Real world examples of how business and IT are benefiting from the sum of the parts
Join industry leaders Charles Zedlewski, Chris Twogood and Kelly Stirman for this unique panel discussion, moderated by BI Research analyst, Colin White.
Open Source in the Energy Industry - Creating a New Operational Model for Dat...DataWorks Summit
The energy industry is well known to be laggard adopters of new technology. However, industry challenges such as aging assets & workforce, increased regulatory scrutiny, renewable energy sources, depressed commodity prices, changing customer expectations, and growing data volumes are pushing companies to explore new technologies to help solve these problems. Learn how Io-Tahoe’s platform built on open source technologies from Hortonworks, is helping organizations in the energy vertical transform into data driven enterprises.
2020 Cloudera Data Impact Awards FinalistsCloudera, Inc.
Cloudera is proud to present the 2020 Data Impact Awards Finalists. This annual program recognizes organizations running the Cloudera platform for the applications they've built and the impact their data projects have on their organizations, their industries, and the world. Nominations were evaluated by a panel of independent thought-leaders and expert industry analysts, who then selected the finalists and winners. Winners exemplify the most-cutting edge data projects and represent innovation and leadership in their respective industries.
Delivering Self-Service Analytics using Big Data and Data Virtualization on t...Denodo
Watch full webinar here: [https://buff.ly/2FHWnMD]
Headquartered in New York City, Guardian Life is one of the largest mutual life insurance companies in the United States. Guardian offerings range from life insurance, disability income insurance, annuities, and investments to dental and vision insurance and employee benefits. The Enterprise Data Program was initiated to modernize Guardian’s technology capabilities and transform how Guardian leverages data – the Enterprise Data Lake was implemented to democratize data and drive self-service analytics throughout the organization. Data virtualization has played a key role for delivering data services through Guardian’s Enterprise Data Marketplace, a centralized portal for analytics and reporting.
Attend this session to learn:
Who is Guardian and what were the key drivers for building a data lake?
What are the data architectural patterns on the cloud?
How data virtualization is powering analytics and reporting?
Siloed data is difficult to access and causes data consumers to only have partial views of the problem at hand. By limiting access to large volumes of disparate data, analysts and business users alike don’t have the ability to included important data in their reports and models leading to suboptimal analytic outputs. Even when this data is available to countless users, traditional systems limit them to querying small volumes of data in order to return the results in a timely matter.
Govern This! Data Discovery and the application of data governance with new s...Cloudera, Inc.
Join Tableau and Cloudera to learn how to apply governance to the discovery layer in an enterprise data hub while still meeting the speed and agility requirements of the business user.
Continuously improving factory operations is of critical importance to manufacturers. Consider the facts: the total cost of poor quality amounts to a staggering 20% of sales (American Society of Quality), and unplanned downtime costs plants approximately $50 billion per year (Deloitte).
The most pressing questions are: which process variables effect quality and yield and which process variables predict equipment failure? Getting to those answers is providing forward thinking manufacturers a leg up over competitors.
The speakers address the data management challenges facing today's manufacturers, including proprietary systems and siloed data sources, as well as an inability to make sensor-based data usable.
Integrating enterprise data from ERP, MES, maintenance systems, and other sources with real-time operations data from sensors, PLCs, SCADA systems, and historians represents a major first step. But how to get started? What is the value of a data lake? How are AI/ML being applied to enable real time action?
Join us for this educational session, which includes a view into a roadmap for an open source industrial IoT data management platform.
Key Takeaways:
• Understand key use cases commonly undertaken by manufacturing enterprises
• Understand the value of using multivariate manufacturing data sources, as opposed to a single sensor on a piece of equipment
• Understand advances in big data management and streaming analytics that are paving the way to next-generation factory performance
Making the Case for Hadoop in a Large Enterprise-British AirwaysDataWorks Summit
Making the Case for Hadoop in a Large Enterprise
British Airways
Alan Spanos
Data Exploitation Manager
British Airways
Jay Aubby
Architect
British Airways
Increase your ROI with Hadoop in Six Months - Presented by Dell, Cloudera and...Cloudera, Inc.
Are you struggling to validate the added costs of a Hadoop implementation? Are you struggling to manage your growing data?
The costs of implementing Hadoop may be more beneficial than you anticipate. Dell and Intel recently commissioned a study with Forrester Research to determine the Total Economic Impact of the Dell | Cloudera Apache Hadoop Solution, accelerated by Intel. The study determined customers can see a 6-month payback when implementing the Dell | Cloudera solution.
Join Dell, Intel and Cloudera, three big data market leaders, to understand how to begin a simplified and cost-effective big data journey and to hear case studies that demonstrate how users have benefited from the Dell | Cloudera Apache Hadoop Solution.
Emergence of MongoDB as an Enterprise Data HubMongoDB
Emergence of MongoDB as an Enterprise Data Hub, presented by Dylan Tong, Sr. Solutions Architect, MongoDB at MongoDB Evenings Seattle at the Seattle Public Library on October 6, 2015.
Oracle OpenWorld London - session for Stream Analysis, time series analytics, streaming ETL, streaming pipelines, big data, kafka, apache spark, complex event processing
Breakout: Hadoop and the Operational Data StoreCloudera, Inc.
As disparate data volumes continue to be operationalized across the enterprise, data will need to be processed, cleansed, transformed, and made available to end users at greater speeds. Traditional ODS systems run into issues when trying to process large data volumes causing operations to be backed up, data to be archived, and ETL/ ELT processes to fail. Join this breakout to learn how to battle these issues.
Evolution from Apache Hadoop to the Enterprise Data Hub by Cloudera - ArabNet...ArabNet ME
A new foundation for the Modern Information Architecture.
Speaker: Amr Awadallah, CTO & Cofounder, Cloudera
Our legacy information architecture is not able to cope with the realities of today's business. This is because it is not able to scale to meet our SLAs due to separation of storage and compute, economically store the volumes and types of data we currently confront, provide the agility necessary for innovation, and most importantly, provide a full 360 degree view of our customers, products, and business. In this talk Dr. Amr Awadallah will present the Enterprise Data Hub (EDH) as the new foundation for the modern information architecture. Built with Apache Hadoop at the core, the EDH is an extremely scalable, flexible, and fault-tolerant, data processing system designed to put data at the center of your business.
Manufacturers have an abundance of data, whether from connected sensors, plant systems, manufacturing systems, claims systems and external data from industry and government. Manufacturers face increased challenges from continually improving product quality, reducing warranty and recall costs to efficiently leveraging their supply chain. For example, giving the manufacturer a complete view of the product and customer information integrating manufacturing and plant floor data, with as built product configurations with sensor data from customer use to efficiently analyze warranty claim information to reduce detection to correction time, detect fraud and even become proactive around issues requires a capable enterprise data hub that integrates large volumes of both structured and unstructured information. Learn how an enterprise data hub built on Hadoop provides the tools to support analysis at every level in the manufacturing organization.
Is your big data journey stalling? Take the Leap with Capgemini and ClouderaCloudera, Inc.
Transitioning to a Big Data architecture is a big step; and the complexity of moving existing analytical services onto modern platforms like Cloudera, can seem overwhelming.
Introducing the data science sandbox as a service 8.30.18Cloudera, Inc.
How can companies integrate data science into their businesses more effectively? Watch this recorded webinar and demonstration to hear more about operationalizing data science with Cloudera Data Science Workbench on Cazena’s fully-managed cloud platform.
The Vortex of Change - Digital Transformation (Presented by Intel)Cloudera, Inc.
The vortex of change continues all around us – inside the company, with our customers and partners. A new norm is upon us. Business models are being turned upside down – the hunters now the hunted, global equalization – size is no longer a guarantee of success. The innovative survive and thrive…the nervous and slow go under...what does all this change means for you? Find out how does Intel’s strengths help our customers in this world of change.
Extending Cloudera SDX beyond the PlatformCloudera, Inc.
Cloudera SDX is by no means no restricted to just the platform; it extends well beyond. In this webinar, we show you how Bardess Group’s Zero2Hero solution leverages the shared data experience to coordinate Cloudera, Trifacta, and Qlik to deliver complete customer insight.
Better Together: The New Data Management OrchestraCloudera, Inc.
To ingest, store, process and leverage big data for maximum business impact requires integrating systems, processing frameworks, and analytic deployment options. Learn how Cloudera’s enterprise data hub framework, MongoDB, and Teradata Data Warehouse working in concert can enable companies to explore data in new ways and solve problems that not long ago might have seemed impossible.
Gone are the days of NoSQL and SQL competing for center stage. Visionary companies are driving data subsystems to operate in harmony. So what’s changed?
In this webinar, you will hear from executives at Cloudera, Teradata and MongoDB about the following:
How to deploy the right mix of tools and technology to become a data-driven organization
Examples of three major data management systems working together
Real world examples of how business and IT are benefiting from the sum of the parts
Join industry leaders Charles Zedlewski, Chris Twogood and Kelly Stirman for this unique panel discussion, moderated by BI Research analyst, Colin White.
Open Source in the Energy Industry - Creating a New Operational Model for Dat...DataWorks Summit
The energy industry is well known to be laggard adopters of new technology. However, industry challenges such as aging assets & workforce, increased regulatory scrutiny, renewable energy sources, depressed commodity prices, changing customer expectations, and growing data volumes are pushing companies to explore new technologies to help solve these problems. Learn how Io-Tahoe’s platform built on open source technologies from Hortonworks, is helping organizations in the energy vertical transform into data driven enterprises.
2020 Cloudera Data Impact Awards FinalistsCloudera, Inc.
Cloudera is proud to present the 2020 Data Impact Awards Finalists. This annual program recognizes organizations running the Cloudera platform for the applications they've built and the impact their data projects have on their organizations, their industries, and the world. Nominations were evaluated by a panel of independent thought-leaders and expert industry analysts, who then selected the finalists and winners. Winners exemplify the most-cutting edge data projects and represent innovation and leadership in their respective industries.
Delivering Self-Service Analytics using Big Data and Data Virtualization on t...Denodo
Watch full webinar here: [https://buff.ly/2FHWnMD]
Headquartered in New York City, Guardian Life is one of the largest mutual life insurance companies in the United States. Guardian offerings range from life insurance, disability income insurance, annuities, and investments to dental and vision insurance and employee benefits. The Enterprise Data Program was initiated to modernize Guardian’s technology capabilities and transform how Guardian leverages data – the Enterprise Data Lake was implemented to democratize data and drive self-service analytics throughout the organization. Data virtualization has played a key role for delivering data services through Guardian’s Enterprise Data Marketplace, a centralized portal for analytics and reporting.
Attend this session to learn:
Who is Guardian and what were the key drivers for building a data lake?
What are the data architectural patterns on the cloud?
How data virtualization is powering analytics and reporting?
Siloed data is difficult to access and causes data consumers to only have partial views of the problem at hand. By limiting access to large volumes of disparate data, analysts and business users alike don’t have the ability to included important data in their reports and models leading to suboptimal analytic outputs. Even when this data is available to countless users, traditional systems limit them to querying small volumes of data in order to return the results in a timely matter.
Govern This! Data Discovery and the application of data governance with new s...Cloudera, Inc.
Join Tableau and Cloudera to learn how to apply governance to the discovery layer in an enterprise data hub while still meeting the speed and agility requirements of the business user.
Continuously improving factory operations is of critical importance to manufacturers. Consider the facts: the total cost of poor quality amounts to a staggering 20% of sales (American Society of Quality), and unplanned downtime costs plants approximately $50 billion per year (Deloitte).
The most pressing questions are: which process variables effect quality and yield and which process variables predict equipment failure? Getting to those answers is providing forward thinking manufacturers a leg up over competitors.
The speakers address the data management challenges facing today's manufacturers, including proprietary systems and siloed data sources, as well as an inability to make sensor-based data usable.
Integrating enterprise data from ERP, MES, maintenance systems, and other sources with real-time operations data from sensors, PLCs, SCADA systems, and historians represents a major first step. But how to get started? What is the value of a data lake? How are AI/ML being applied to enable real time action?
Join us for this educational session, which includes a view into a roadmap for an open source industrial IoT data management platform.
Key Takeaways:
• Understand key use cases commonly undertaken by manufacturing enterprises
• Understand the value of using multivariate manufacturing data sources, as opposed to a single sensor on a piece of equipment
• Understand advances in big data management and streaming analytics that are paving the way to next-generation factory performance
Making the Case for Hadoop in a Large Enterprise-British AirwaysDataWorks Summit
Making the Case for Hadoop in a Large Enterprise
British Airways
Alan Spanos
Data Exploitation Manager
British Airways
Jay Aubby
Architect
British Airways
Increase your ROI with Hadoop in Six Months - Presented by Dell, Cloudera and...Cloudera, Inc.
Are you struggling to validate the added costs of a Hadoop implementation? Are you struggling to manage your growing data?
The costs of implementing Hadoop may be more beneficial than you anticipate. Dell and Intel recently commissioned a study with Forrester Research to determine the Total Economic Impact of the Dell | Cloudera Apache Hadoop Solution, accelerated by Intel. The study determined customers can see a 6-month payback when implementing the Dell | Cloudera solution.
Join Dell, Intel and Cloudera, three big data market leaders, to understand how to begin a simplified and cost-effective big data journey and to hear case studies that demonstrate how users have benefited from the Dell | Cloudera Apache Hadoop Solution.
Emergence of MongoDB as an Enterprise Data HubMongoDB
Emergence of MongoDB as an Enterprise Data Hub, presented by Dylan Tong, Sr. Solutions Architect, MongoDB at MongoDB Evenings Seattle at the Seattle Public Library on October 6, 2015.
Oracle OpenWorld London - session for Stream Analysis, time series analytics, streaming ETL, streaming pipelines, big data, kafka, apache spark, complex event processing
Breakout: Hadoop and the Operational Data StoreCloudera, Inc.
As disparate data volumes continue to be operationalized across the enterprise, data will need to be processed, cleansed, transformed, and made available to end users at greater speeds. Traditional ODS systems run into issues when trying to process large data volumes causing operations to be backed up, data to be archived, and ETL/ ELT processes to fail. Join this breakout to learn how to battle these issues.
Hadoop World 2011: Advancing Disney’s Data Infrastructure with Hadoop - Matt ...Cloudera, Inc.
This is the story of why and how Hadoop was integrated into the Disney data infrastructure. Providing data infrastructure for Disney’s, ABC’s and ESPN’s Internet presences is challenging. Doing so requires cost effective, performant, scalable and highly available solutions. Information requirements from the business add the need for these solutions work together; providing consistent acquisition, storage and access to data. Burdened with a heavily laden commercial RDBMS infrastructure, Hadoop provided an opportunity to solve some challenging use cases at Disney. The deployment of Hadoop helped Disney to address growing costs, scalability, and data availability. In addition, it provids our businesses with new data driven business to consumer opportunities.
Real-Time Data Pipelines with Kafka, Spark, and Operational DatabasesSingleStore
Eric Frenkiel, MemSQL CEO and co-founder and Gartner Catalyst. August 11, 2015, San Diego, CA. Watch the Pinterest Demo Video here: https://youtu.be/KXelkQFVz4E
How to develop Big Data Pipelines for Hadoop, by Costin LeauCodemotion
Hadoop is not an island. To deliver a complete Big Data solution, a data pipeline needs to be developed that incorporates and orchestrates many diverse technologies. In this session we will demonstrate how the open source Spring Batch, Spring Integration and Spring Hadoop projects can be used to build manageable and robust pipeline solutions to coordinate the running of multiple Hadoop jobs (MapReduce, Hive, or Pig), but also encompass real-time data acquisition and analysis.
Designing high performance datawarehouseUday Kothari
Just when the world of “Data 1.0” showed some signs of maturing; the “Outside In” driven demands seem to have already initiated some the disruptive changes to the data landscape. Parallel growth in volume, velocity and variety of data coupled with incessant war on finding newer insights and value from data has posed a Big Question: Is Your Data Warehouse Relevant?
In short, the surrounding changes happening real time is the new “Data 2.0”. It is characterized by feeding the ever hungry minds with sharper insights whether it is related to regulation, finance, corporate action, risk management or purely aimed at improving operational efficiencies. The source in this new “Data 2.0” has to be commensurate to the outside in demands from customers, regulators, stakeholders and business users; and hence, you would need a high relformance (relevance + performance) data warehouse which will be relevant to your business eco-system and will have the power to scale exponentially.
We starts this webinar by giving the audiences a sneak preview of what happened in the Data 1.0 world & which characteristics are shaping the new Data 2.0 world. It then delves deep on the challenges that growing data volumes have posed to the Data warehouse teams. It also presents the audiences some of the practical and proven methodologies to address these performance challenges. Finally, in the end it will highlight some of the thought provoking ways to turbo charge your data warehouse related initiatives by leveraging some of the newer technologies like Hadoop. Overall, the webinar will educate audiences with building high performance and relevant data warehouses which is capable of meeting the newer demands while significantly driving down the total cost of ownership.
Logical Data Warehouse and Data Lakes can play a role in many different type of projects and, in this presentation, we will look at some of the most common patterns and use cases. Learn about analytical and big data patterns as well as performance considerations. Example implementations will be discussed for each pattern.
- Architectural patterns for logical data warehouse and data lakes.
- Performance considerations.
- Customer use cases and demo.
This presentation is part of the Denodo Educational Seminar, and you can watch the video here goo.gl/vycYmZ.
Hive, Impala, and Spark, Oh My: SQL-on-Hadoop in Cloudera 5.5Cloudera, Inc.
Inefficient data workloads are all too common across enterprises - causing costly delays, breakages, hard-to-maintain complexity, and ultimately lost productivity. For a typical enterprise with multiple data warehouses, thousands of reports, and hundreds of thousands of ETL jobs being executed every day, this loss of productivity is a real problem. Add to all of this the complex handwritten SQL queries, and there can be nearly a million queries executed every month that desperately need to be optimized, especially to take advantage of the benefits of Apache Hadoop. How can enterprises dig through their workloads and inefficiencies to easily see which are the best fit for Hadoop and what’s the fastest path to get there?
Cloudera Navigator Optimizer is the solution - analyzing existing SQL workloads to provide instant insights into your workloads and turns that into an intelligent optimization strategy so you can unlock peak performance and efficiency with Hadoop. As the newest addition to Cloudera’s enterprise Hadoop platform, and now available in limited beta, Navigator Optimizer has helped customers profile over 1.5 million queries and ultimately save millions by optimizing for Hadoop.
This is the presentation for the talk I gave at JavaDay Kiev 2015. This is about an evolution of data processing systems from simple ones with single DWH to the complex approaches like Data Lake, Lambda Architecture and Pipeline architecture
The Vision & Challenge of Applied Machine LearningCloudera, Inc.
Learn how Cloudera provides a unified platform that breaks down data silos commonly seen in organizations. By unifying the data needed for applied machine learning, organizations are better equipped to gather valuable insights from their data.
Build a modern platform for anti-money laundering 9.19.18Cloudera, Inc.
In this webinar, you will learn how Cloudera and BAH riskCanvas can help you build a modern AML platform that reduces false positive rates, investigation costs, technology sprawl, and regulatory risk.
Data Driven With the Cloudera Modern Data Warehouse 3.19.19Cloudera, Inc.
In this session, we will cover how to move beyond structured, curated reports based on known questions on known data, to an ad-hoc exploration of all data to optimize business processes and into the unknown questions on unknown data, where machine learning and statistically motivated predictive analytics are shaping business strategy.
Capgemini Leap Data Transformation Framework with ClouderaCapgemini
https://www.capgemini.com/insights-data/data/leap-data-transformation-framework
The complexity of moving existing analytical services onto modern platforms like Cloudera can seem overwhelming. Capgemini’s Leap Data Transformation Framework helps clients by industrializing the entire process of bringing existing BI assets and capabilities to next-generation big data management platforms.
During this webinar, you will learn:
• The key drivers for industrializing your transformation to big data at all stages of the lifecycle – estimation, design, implementation, and testing
• How one of our largest clients reduced the transition to modern data architecture by over 30%
• How an end-to-end, fact-based transformation framework can deliver IT rationalization on top of big data architectures
The 6th Wave of Automation: Automation of Decisions | Cloudera Analytics & Ma...Cloudera, Inc.
This presentation provides detail on how we are now in the 6th wave of automation, that is based on Machine Learning. In this 6th wave, Cloudera plays a critical role in providing the data platform for Machine Learning and Analytics built for the Cloud.
Standing Up an Effective Enterprise Data Hub -- Technology and BeyondCloudera, Inc.
Federal organizations increasingly are focused on creating environments that enable more data-driven decisions. Yet ensuring that all data is considered and is current, complete, and accurate is a tall order for most. To make data analytics meaningful to support real-world transformation, agency staff need business tools that provide user-friendly dashboards, on-demand reporting, and methods to manage efficiently the rise of voluminous and varied data sets and types commonly associated with big data. In most cases, existing systems are insufficient to support these requirements. Enter the enterprise data hub (EDH), a software architecture specifically designed to be a unified platform that can economically store unlimited data and enable diverse access to it at scale. Plan to attend this discussion to understand the key considerations to making an EDH the architectural center of your agency’s modern data strategy.
The 5 Biggest Data Myths in Telco: ExposedCloudera, Inc.
More than any business, telecommunications firms have long been dealing with huge, diverse sets of data. Big Data. Data that is unstructured, unwieldy and disorganised, making it difficult to analyse and costly to manage. Your landscape is fiercely competitive and you instinctively know it's exactly that data that would allow you to be more innovative. Data that would set you apart from the competition. You would like to realise its true potential yet you have concerns around security, RoI or integration with existing data management solutions.
Seeking Cybersecurity--Strategies to Protect the DataCloudera, Inc.
Agency professionals are responsible for protecting the data they collect, store, analyze, and share. While Hadoop has been especially popular for data analytics given its ability to handle volume, velocity, and variety of data, this flexibility and scale can present challenges for securing and governing the data. Plan to attend this session to understand the Hadoop Security Maturity Model—from the fundamentals to the latest developments--and how to ensure your data analytics cluster complies with the latest INFOSEC standards and audit requirements. Bring your experience and your questions to this informative and interactive cybersecurity session.
Analytics, Everywhere. Keys to Effective Analytics and Data DiscoveryDLT Solutions
Webster Mudge, Senior Director of Technology Solutions at Cloudera, shares keys to effective analytics and data discovery at the 2015 Informatica Government Summit.
Learn how Cloudera is using our own platform to build the applications our support teams use every day to solve complex problems in Hadoop.
Recorded Webinar: http://www.cloudera.com/content/www/en-us/resources/recordedwebinar/data-driven-customer-support.html
Get an inside look at how Cloudera delivers the industry's best customer support. Hear from Adam Warrington, senior manager of Cloudera’s Internal Systems Engineering team, about the intelligent data applications enabling Cloudera’s diagnostic, predictive, and proactive support processes.
Cloudera Altus: Big Data in the Cloud Made EasyCloudera, Inc.
Cloudera Altus makes it easier for data engineers, ETL developers, and anyone who regularly works with raw data to process that data in the cloud efficiently and cost effectively. In this webinar we introduce our new platform-as-a-service offering and explore challenges associated with data processing in the cloud today, how Altus abstracts cluster overhead to deliver easy, efficient data processing, and unique features and benefits of Cloudera Altus.
Simplifying Real-Time Architectures for IoT with Apache KuduCloudera, Inc.
3 Things to Learn About:
*Building scalable real time architectures for managing data from IoT
*Processing data in real time with components such as Kudu & Spark
*Customer case studies highlighting real-time IoT use cases
Intel and Cloudera: Accelerating Enterprise Big Data SuccessCloudera, Inc.
The data center has gone through several inflection points in the past decades: adoption of Linux, migration from physical infrastructure to virtualization and Cloud, and now large-scale data analytics with Big Data and Hadoop.
Please join us to learn about how Cloudera and Intel are jointly innovating through open source software to enable Hadoop to run best on IA (Intel Architecture) and to foster the evolution of a vibrant Big Data ecosystem.
3 Things to Learn About:
*The IoT ecosystem and data management considerations for IoT
*Top IoT use cases and data architecture strategies for managing the sheer volume and variety of IoT data
*Real-life case studies on how our customers are using Cloudera Enterprise to drive insights and analytics from all of their IoT data
Similar to Keynote: The Journey to Pervasive Analytics (20)
Cloudera Data Impact Awards 2021 - Finalists Cloudera, Inc.
This annual program recognizes organizations who are moving swiftly towards the future and building innovative solutions by making what was impossible yesterday, possible today.
The winning organizations' implementations demonstrate outstanding achievements in fulfilling their mission, technical advancement, and overall impact.
The 2021 Data Impact Awards recognize organizations' achievements with the Cloudera Data Platform in seven categories:
Data Lifecycle Connection
Data for Enterprise AI
Cloud Innovation
Security & Governance Leadership
People First
Data for Good
Industry Transformation
Machine Learning with Limited Labeled Data 4/3/19Cloudera, Inc.
Cloudera Fast Forward Labs’ latest research report and prototype explore learning with limited labeled data. This capability relaxes the stringent labeled data requirement in supervised machine learning and opens up new product possibilities. It is industry invariant, addresses the labeling pain point and enables applications to be built faster and more efficiently.
Introducing Cloudera DataFlow (CDF) 2.13.19Cloudera, Inc.
Watch this webinar to understand how Hortonworks DataFlow (HDF) has evolved into the new Cloudera DataFlow (CDF). Learn about key capabilities that CDF delivers such as -
-Powerful data ingestion powered by Apache NiFi
-Edge data collection by Apache MiNiFi
-IoT-scale streaming data processing with Apache Kafka
-Enterprise services to offer unified security and governance from edge-to-enterprise
Introducing Cloudera Data Science Workbench for HDP 2.12.19Cloudera, Inc.
Cloudera’s Data Science Workbench (CDSW) is available for Hortonworks Data Platform (HDP) clusters for secure, collaborative data science at scale. During this webinar, we provide an introductory tour of CDSW and a demonstration of a machine learning workflow using CDSW on HDP.
Shortening the Sales Cycle with a Modern Data Warehouse 1.30.19Cloudera, Inc.
Join Cloudera as we outline how we use Cloudera technology to strengthen sales engagement, minimize marketing waste, and empower line of business leaders to drive successful outcomes.
Leveraging the cloud for analytics and machine learning 1.29.19Cloudera, Inc.
Learn how organizations are deriving unique customer insights, improving product and services efficiency, and reducing business risk with a modern big data architecture powered by Cloudera on Azure. In this webinar, you see how fast and easy it is to deploy a modern data management platform—in your cloud, on your terms.
Modernizing the Legacy Data Warehouse – What, Why, and How 1.23.19Cloudera, Inc.
Join us to learn about the challenges of legacy data warehousing, the goals of modern data warehousing, and the design patterns and frameworks that help to accelerate modernization efforts.
Leveraging the Cloud for Big Data Analytics 12.11.18Cloudera, Inc.
Learn how organizations are deriving unique customer insights, improving product and services efficiency, and reducing business risk with a modern big data architecture powered by Cloudera on AWS. In this webinar, you see how fast and easy it is to deploy a modern data management platform—in your cloud, on your terms.
Explore new trends and use cases in data warehousing including exploration and discovery, self-service ad-hoc analysis, predictive analytics and more ways to get deeper business insight. Modern Data Warehousing Fundamentals will show how to modernize your data warehouse architecture and infrastructure for benefits to both traditional analytics practitioners and data scientists and engineers.
Explore new trends and use cases in data warehousing including exploration and discovery, self-service ad-hoc analysis, predictive analytics and more ways to get deeper business insight. Modern Data Warehousing Fundamentals will show how to modernize your data warehouse architecture and infrastructure for benefits to both traditional analytics practitioners and data scientists and engineers.
Explore new trends and use cases in data warehousing including exploration and discovery, self-service ad-hoc analysis, predictive analytics and more ways to get deeper business insight. Modern Data Warehousing Fundamentals will show how to modernize your data warehouse architecture and infrastructure for benefits to both traditional analytics practitioners and data scientists and engineers.
Federated Learning: ML with Privacy on the Edge 11.15.18Cloudera, Inc.
Join Cloudera Fast Forward Labs Research Engineer, Mike Lee Williams, to hear about their latest research report and prototype on Federated Learning. Learn more about what it is, when it’s applicable, how it works, and the current landscape of tools and libraries.
Analyst Webinar: Doing a 180 on Customer 360Cloudera, Inc.
451 Research Analyst Sheryl Kingstone, and Cloudera’s Steve Totman recently discussed how a growing number of organizations are replacing legacy Customer 360 systems with Customer Insights Platforms.
In this webinar, we’ll show you how Cloudera SDX reduces the complexity in your data management environment and lets you deliver diverse analytics with consistent security, governance, and lifecycle management against a shared data catalog.
Workload Experience Manager (XM) gives you the visibility necessary to efficiently migrate, analyze, optimize, and scale workloads running in a modern data warehouse. In this recorded webinar we discuss common challenges running at scale with modern data warehouse, benefits of end-to-end visibility into workload lifecycles, overview of Workload XM and live demo, real-life customer before/after scenarios, and what's next for Workload XM.
Get started with Cloudera's cyber solutionCloudera, Inc.
Cloudera empowers cybersecurity innovators to proactively secure the enterprise by accelerating threat detection, investigation, and response through machine learning and complete enterprise visibility. Cloudera’s cybersecurity solution, based on Apache Spot, enables anomaly detection, behavior analytics, and comprehensive access across all enterprise data using an open, scalable platform. But what’s the easiest way to get started?
Spark and Deep Learning Frameworks at Scale 7.19.18Cloudera, Inc.
We'll outline approaches for preprocessing, training, inference, and deployment across datasets (time series, audio, video, text, etc.) that leverage Spark, along with its extended ecosystem of libraries and deep learning frameworks using Cloudera's Data Science Workbench.
Cloud Data Warehousing with Cloudera Altus 7.24.18Cloudera, Inc.
This webinar will help you maximize the full potential of the cloud. Understand how to leverage cloud environments for different analytic workloads to empower business analysts and keep IT happy. An intricate, beautiful balance. The learn best practices in design, performance tuning, workload considerations, and hybrid or multi-cloud strategies.
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
GridMate - End to end testing is a critical piece to ensure quality and avoid...ThomasParaiso2
End to end testing is a critical piece to ensure quality and avoid regressions. In this session, we share our journey building an E2E testing pipeline for GridMate components (LWC and Aura) using Cypress, JSForce, FakerJS…
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!SOFTTECHHUB
As the digital landscape continually evolves, operating systems play a critical role in shaping user experiences and productivity. The launch of Nitrux Linux 3.5.0 marks a significant milestone, offering a robust alternative to traditional systems such as Windows 11. This article delves into the essence of Nitrux Linux 3.5.0, exploring its unique features, advantages, and how it stands as a compelling choice for both casual users and tech enthusiasts.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024Neo4j
Neha Bajwa, Vice President of Product Marketing, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIVladimir Iglovikov, Ph.D.
Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
This presentation delves into the journey of Albumentations.ai, a highly successful open-source library for data augmentation.
Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentations
Key Takeaway: Analytics are accelerating the pace of learning. But as they accelerate the pace of learning and continue to be applied to new use cases, we need to make sure we get the right analytics to the right people, and that is not always the case. People don’t always have access to the right information, if any at all.
Key Takeaway: What does analytics look like today? Whether you are looking at the business or consumer space, analytics are supplying us value today. But this value is still limited and not always what we want.
What happens when that report is not quite right? Or what happens to your product recommendations when your daughter makes a purchase?
Key Takeaway: Analytics are becoming ingrained into everything we do. They are informing the companies and products that we use everyday. Sometimes customers are the users of the analytics, other times the company uses them to offer a better service to that customer.
Tell a story piecing all of the use cases on the slides together (Don’t name customers)…
A box with hardware in it (Netapp: predictive support)
Electricity from light (Opower: Energy usage analytics).
The right ad served to you on the computer (OpenX ad exchange)
Detecting malware for your business (CounterTack security platform)
A new technology is emerging that combines data science expertise with deep understanding of business problems. These solutions use algorithmic data mining on your own data and often on external third party data accessible by cloud ecosystems and APIs. Data Driven Solutions make predictions about business functions, prescribe what to do next, and in many cases take action autonomously. Trained analysts are not required to query databases. Instead, business users get answers directly from the software. These answers typically feed seamlessly into the flow of business activity, often invisibly.
These solutions make predictions about business functions, prescribe what to do next, and in many cases take action autonomously.
http://www.forbes.com/sites/ciocentral/2014/04/18/8-ways-to-build-and-use-the-new-breed-of-data-driven-applications/
Key takeaway: We can measure and act on everything now. 16B connected devices. Only those that can harness this data can take advantage of it. “If you can’t measure it, you can’t fix it.” –DJ Patil
Source: http://www.forbes.com/sites/gilpress/2014/08/22/internet-of-things-by-the-numbers-market-estimates-and-forecasts/
Key Takeaway: We can analyze anything now. Numerical, text, audio, video. We are now able to discover insights in complex data. Leveraging text analytics, rich media analytics, graph analytics, time series, etc. All of these analytics allow us to get a complete understanding of any data problem we are trying to solve. And they are no longer limited by data. This allows us to enter new use cases and expand our understanding of the problems at hand.
Analytics continues to drive more value. Early analytic returns 13X per $1 spent
Key Takeaway:
Source: 18th Annual Global CEO survey
Key Takeaway: Through implementing countless analytics solutions across a variety of industries we have learned some secretes and have acquired some skills. Let’s examine what is needed in order to reach a pervasive analytics end state.
Key Takeaways: The model for growth is simple. It is a function of money, people, and technology. The only purpose of technology is to make people more efficient. In the context of pervasive analytics there are two ways to think of this. People need to build, deploy, and manage analytics more efficiently and will this analytic make the person more efficient. If we can do both, then serious economic change is upon us.
In order to create a revolution we must direct our attention to how we can make our labor more efficient. How can analytics help make our employees more efficient? We aren’t talking about data.
Solow growth model for macro economic growth: Y = f (K, L*E)
K= capital
L= labor
E = labor efficiency (technology)
Key Takeaways: In order to create a revolution we must direct our attention to how we can make people more efficient. And the final answer isn’t having them sift through more data. We need to provide them the right information.
Industrial revolution = manufacturing technology improved allowing for massive economic growth.
Green revolution = Produce more per acre with less labor allowing people to leave the fields and add to the GDP.
Data revolution = repetitive decision making will be automated. This time savings will allow humans to tackle unforeseen problems. When this happens, humans won’t sit idle, they are too curious.
Key Takeaways: Employees are already asking the right questions, we just need to help them achieve their goals through the use of data.
Key Takeaways: Industries are already beginning to transform. How can data help transform the way employees and customers interact with these industries.
Key Takeaways: Our customers are already thinking this way. How do we offer a better product or service that differentiates us through the use of data.
Tell a story piecing all of the customers on the slides together…
A box with hardware in it (Netapp: predictive support)
Electricity from light (Opower: Energy usage analytics).
The right ad served to you on the computer (OpenX ad exchange)
Detecting malware for your business (CounterTack security platform)
Key Takeaway: Through implementing countless analytics solutions across a variety of industries we have learned some secretes and have acquired some skills. Let’s examine what is needed in order to reach a pervasive analytics end state.
Key Takeaway: No one person can roll out an analytic solution to end consumers. There are 3 groups needed. IT, Analysts, and Users. What do each of the groups care about?
Technical (IT or engineering) care about…
Flexibility
Scalability and robustness
It just works
Data (Analysts or Data Scientists) care about…
Rapid experimentation
Model development
Building the Right metrics
Product (Employees or customers) care about…
Solution vision
Impact
Moving Success Metrics
Key takeaway: But there are obvious challenges that the team must address in order to effectively build analytic applications for the average business user.
Ingesting diverse data
Securely storing more data
Processing data efficiently for operational and analytical use so there is not latency.
Can your system handle today’s and tomorrow’s use cases?
Key takeaway: What are the data challenges that the data team is thinking about.
Having access to the different analytic techniques they need. They need more than just SQL access.
Historic and diverse data access for smarter analytics (large sample sets to test against, better predictions and view from through complementary data)
Can they iterate fast? What is their model development time?
Key takeaway: What are the user challenges they are facing.
Latency in analytics being fed to users can causes users to bounce off of the applications
Analytics need to be consistent
Bring the analytics to the user
Key Takeaway: Keeping in mind the needs and the challenges of the team, what is needed to help the team as they continue to bring analytics to the masses? An enterprise data hub,
In response, many organizations have turned to a new architecture – an enterprise data hub – to complement and extend existing investments.
An enterprise data hub can store unlimited data, cost-effectively and reliably, for as long as you need, and lets users access that data in a variety of ways. Data can be collected, stored, processed, explored, modeled, and served in one unified platform. It’s connected to the systems you already rely on.
Cloudera’s enterprise data hub, powered by Apache Hadoop, the popular open source distributed data platform, is differentiated in several crucial areas. We provide:
Leading query performance.
The enterprise management and governance that you require of all of your mission-critical infrastructure.
Comprehensive, transparent, compliance-ready security at the core.
An open source platform that is also built of open standards – projects that are supported by multiple vendors to ensure sustainability, portability, and compatibility.
Our platform runs in your choice of environment, whether on-premises or in the cloud.
===
Cheat Sheet version: Our enterprise data hub is:
One place for unlimited data
Accessible to anyone
Connected to the systems you already depend on
Secure, governed, managed & compliant
Built on open source and open standards
Deployed however you want
Coupled with the support and enablement you need to succeed.
Important Note: Our EDH emphasizes “unified analytics” over “unified data”: It’s not practical or probable that customers will actually unify all their data. Much of it lives in the cloud or on storage (e.g. Isilon), in remote datacenters, is of uncertain value vs. cost of moving it to a hub, or security mandates preclude collocation. We enable customers to gather unlimited data, while bringing diverse processing and analytics to that data.
Key Takeaway: So we talked about the right team and the right platform, but no one organization can do it on their own, they need a supporting community to help them along the way.
Key Takeaway: First and foremost we have the Apache Hadoop community. This ever growing community continues to add projects in order to more efficiently protect
Key Takeaway: Expertise,
Cloudera partners more broadly and deeply across the Hadoop ecosystem than any other vendor. With over 1200 partners and counting, our partnerships offer:
Compatibility with your existing tools and skills
160+ certified on Cloudera 5, including all 12 of the 12 Gartner Business Intelligence Magic Quadrant leaders
Flexible deployment options
On-premises
Public, private, or hybrid cloud
Appliances and engineered systems
Partnerships you can trust
Deep engineering relationships
Comprehensive certification program
Key Takeaway: Everyone is a data innovator. It is not just IT, it is everyone in the business. Identify the solutions you want to build and understand the challenges that you need to overcome.
You need to start asking the right questions… you are in control.
Key Takeaway: Depending on your organizations current challenges, you will start the journey at a different place. Having trouble ingesting, storing, and processing data? Or having trouble creating a flexible analytic environment? Or do you want to serve analytics out to more end users?