IBM Insight 2014: Data Warehousing and Analytics in the Era of Big Data

By Wendy Lucas,  

Rapidly evolving technology, demanding business requirements and a world where insight drives competitive advantage are continuing to change the definition of the traditional data warehouse.  Where does today’s data warehouse fit into the information management landscape?  Is your data warehouse evolving to fit the needs of big data and analytics?

We all know the world is changing.  Technology allows us to consume more data and generate new insight.  As technology allows IT to deliver more to an organization, businesses need to quickly generate insight from information to accelerate informed decision-making and meet new user demands for mobility and self-service.  Rushing to meet these demands can easily generate complexity within traditional data warehouse architectures.   Is your architecture getting too complex?

Yet at the same time IT solutions grow in complexity, organizations are still challenged with adding more capability and answering the following questions:

  • How should my architecture change to handle big data?
  • How do I deliver faster insight for my users?
  • How do I simplify operations so my resources can spend more time innovating?
  • How do I add new data or capability without impacting performance?

Meeting these challenges requires solutions that provide simplicity in terms of implementation and administration, and seamlessly integrate with other information sources to deliver on the value in big data analytics.   And let’s not forget performance.  Great performance is a given.  It’s expected.  Solutions must have the unique combination of speed and simplicity to deliver business results and provide a platform that is agile and flexible to adapt to rapidly changing business needs. 

IBM’s Data Warehousing Solutions

IBM solutions for data warehousing are developed to simplify and accelerate the delivery of insights for business analytics, helping you meet the challenges of data warehousing.   It is IBM’s point of view that the data warehouse plays a fundamental role in providing the data foundation for analytics, but that the data warehouse must be modernized to take advantage of new data sources and systems of engagement.   We define the modern data warehouse as the means by which organizations can intelligently store and quickly access data, and deliver data to where it provides the most value.

“Through 2020, over 90% of big data implementations will augment, not replace, existing data warehouses.”[1]

Data Warehouse modernization builds on your existing foundation.  It does not require a rip and replace.  We see clients modernize their environments by adding new data sources or capacity, increasing usage or analytic capability, accelerating performance for faster time to insight, and by exploiting new technology innovations such as Hadoop, in-memory and columnar technology to boost performance of analytics.  IBM offers solutions to meet each of these entry points to data warehouse modernization. 

Data Warehousing and Analytics at Insight 2014

The Data Warehousing and Analytics track at the IBM Insight 2014 conference is dedicated to helping you turn these information challenges into opportunities.   More than 40 Elective Sessions, 8 hands-on Labs and Expert Exchanges will feature key topics such as:

  • Data Warehouse architecture and modernization
  • Data Warehouse best practices
  • Integrating data warehouse and Hadoop
  • Accelerating time- to-value and speed to insight
  • Client sessions with experiences from various industries including consumer products, financial services, healthcare, insurance and retail
  • Product sessions featuring DB2 with BLU Acceleration, IBM PureData System for Analytics (powered by Netezza), IBM DB2 Analytics Accelerator, and Informix Warehouse

Sunday, October 26 is a full day dedicated to PureData-Netezza enthusiasts.  Don’t miss this full day dedicated to discussing technical tips and best practices for the PureData System for Analytics, powered by Netezza technology.  Start off your week with this comprehensive, immersive trip through Enzee Universe, followed by a cocktail reception.  Register today and add these two sessions to your schedule:

  • IWS-6951 Enzee Universe Part 1 – Technical Sessions & Best Practices
  • IWS-6952 Enzee Universe Part 2 – Business and Product Strategy

Be sure to catch these spotlight/keynote sessions:

  • IWM-4857 The State of Data Warehousing in the Big Data World
  • IWM-4859 Driving Analytics with Common Architectural Patterns

And here are just a few examples of other informative electives:

  • IWS-4681 IBM DB2 Analytics Accelerator:  trends and directions
  • IWA-5303 Designing an integrated Big Data and DW landscape with IBM industry models
  • IWS-5338 Why University of Toronto is loving BLU – faster, smaller and simpler in only a few hours
  • IWS-5571 Case study with Dick’s Sporting Goods on Oracle to IBM PureData System for Analytics migration
  • IWM-6069 Comparing the Total Cost of Ownership of PureData for Analytics to its’ competitors
  • IWS-6295 DB2 with BLU Acceleration: the deep dive on DB2’s new super fast, super easy engine for analytics
  • IWS-6326 What’s new with IBM PureData System for Analytics, powered by Netezza

… and many others.  In addition to elective sessions, there are Expo Hall exhibits, demos and meetings with subject matter experts.  Visit the Insight website more information, and then build your agenda using the Agenda Preview Tool.

[1] “The State of Data Warehousing in 2014”, June 19, 2014, Gartner.

About Wendy Lucas

Wendy Lucas is a Program Director for IBM Data Warehouse Marketing. Wendy has over 20 years of experience in data warehousing and business intelligence solutions, including 12 years at IBM. She has helped clients in a variety of roles, including application development, management consulting, project management, technical sales management and marketing. Wendy holds a Bachelor of Science in Computer Science from Capital University and you can follow her on Twitter at @wlucas001

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