High Performance: The Secret of Success and Survival in BI/DW/DI
By Philip Russom, TDWI Research Director
High performance continues to intensify as a critical success factor for user implementations in data warehousing (DW), business intelligence (BI), data integration (DI), and analytics. Users are challenged by big data volumes, new and demanding analytic workloads, growing user communities, and business requirements for real-time operation. Vendor companies have responded with many new and improved products and functions for high performance—so many that it’s hard for users to grasp them all.
In other words, just about everything we do in DW, BI, DI, and analytics has some kind of high-performance requirement. Users want quick responses to their queries, analysts need to rescore analytic models as soon as possible, and some managers want to refresh their dashboards on demand. Then there’s scalability, as in the giant data volumes of big data, growing user communities, and the overnight refresh of thousands of reports and analyses. Other performance challenges come from the increasing adoption of advanced analytics, mixed workloads, streaming data, and real-time practices such as operational BI.
Across all these examples, you can see that high-performance data warehousing (HiPerDW) is all about achieving speed and scale, despite increasing complexity and concurrency. This applies to every layer of the complex BI/DW/DI technology stack, as well as processes that unfold across multiple layers.
Luckily, today’s high-performance challenges are being addressed by numerous technical advancements in vendor tools and platforms. For example, there are now multiple high-performance platform architectures available for your data warehouse, including MPP, grids, clusters, server virtualization, clouds, and SaaS. For real-time data, databases and data integration tools are now much better at handling streaming big data, service buses, SOA, Web services, data federation, virtualization, and event processing. 64-bit computing has fueled an explosion of in-memory databases and in-memory analytic processing in user solutions; flash memory and solid-state drives will soon fuel even more innovative practices. Other performance enhancements have recently come from multi-core CPUs, appliances, columnar storage, high-availability features, MapReduce, Hadoop, and in-database analytics.
My next Best Practices Report from TDWI will help users understand new business and technology requirements for high-performance data warehousing (HiPerDW), as well as the many options and solutions available to them. Obviously, performance doesn’t result solely from the data warehouse platform, so the report will also reach out to related platforms for analytics, BI, visualization, data integration, clouds, grids, appliances, data services, Hadoop, and so on. My upcoming TDWI report (to be published in October 2012) will provide tips and strategies for prioritizing your own adoption of high-performance features.
Please help me with the research for the HiPerDW report, by taking its survey, online at: http://svy.mk/HiPerDW
. And please forward this email to anyone you feel is appropriate, especially people who have experience implementing or optimizing the high performance of systems for BI/DW/DI and analytics. If you tweet about HiPerDW, please use the Twitter hash tag #HiPerDW. Thank you!
Posted by Philip Russom, Ph.D. on May 18, 2012