Five Steps to Optimizing BI and Data Warehouse Performance - InformationWeek

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Software // Information Management

Five Steps to Optimizing BI and Data Warehouse Performance

The pressure is on business intelligence and data warehousing professionals to handle ever-higher data volumes and ever-more-complex queries while reducing decision latency. Follow this five-step approach to identify key business drivers, optimize system performance, guide new technology deployments, improve responsiveness, and invest for future performance demands.

In recent years, business intelligence (BI) and data warehouse systems have evolved from their beginnings as batch-oriented systems for basic reporting, querying and analysis used by small, well-defined user communities. Today, many are enterprise systems that handle many kinds of queries and must be continuously available for diverse user communities.

Organizations in nearly all industries now view data warehouses as integral to financial reporting, customer relationship management, marketing and other functions. An increasing number see the ability to use data for BI, performance management and other forms of analysis as a competitive differentiator; they want users in nearly all business operations to have access to broad-based, timely, accurate data to use for both trend analysis and daily operational decision-making. This demand puts tremendous pressure on BI and data warehouse systems to perform well.

As requirements change, traditional approaches to managing and optimizing BI and data warehouse performance are becoming outmoded. Having been put together piece by piece, most BI and data warehouse systems are managed through tools designed to work only with a single database, storage system, operating system, server or BI system. This "silo" arrangement has made it difficult for IT managers to see performance from the user's perspective; individual components appear to be working fine, yet users report inadequate performance. Workload analysis and tuning tools can help IT managers to capture information about user activity, data flows and query performance, and to analyze the information for ways to improve BI and data warehouse performance. However, most organizations are just beginning to identify and access information sources for workload analysis and to deploy tools specifically intended for this purpose.

In light of these changes, Ventana Research recently conducted benchmark research to examine the tools used to identify queries that perform poorly or that put burdens on the system disproportionate to their business importance. We also sought to better understand how organizations are addressing performance problems through tuning and optimization of current systems as well as through deployment of new technologies, such as data warehouse appliances, specialized databases and query accelerators. Finally, we sought to discover organizations' plans for future deployments to address business information demands.

This article presents an executive summary of the resulting report, "Optimizing BI and Data Warehouse Performance," which examines the progress organizations are making toward gaining a more complete view of BI and data warehouse performance. As described in greater detail in the full, 63-page report, organizations face big challenges as they attempt to gain fuller analysis of data about customers, products and other key areas. In particular, firms have difficulty scaling warehouses as they attempt to analyze more data and handle ever more complex queries. What's more, performance lags even as they are faced with demands for lower data latency and continuous, seven-day-a-week, 24-hours-per-day availability. Presented below are the key findings of Ventana's recent research along with a five-step approach that will help you:

1. Identify key business drivers that should direct performance improvement efforts.
2. Improve information assets for analyzing and tuning performance.
3. Use performance demand to guide deployment of appliances, specialized databases and query accelerators.
4. Reduce the time it takes to remedy unsatisfactory performance and implement information change requests.
5. Assess your organization’s maturity and invest for improvement.

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