Datawarehousing and Business Intelligence Center OF Excellence

Smart enterprises use information to deliver superior business results and to gain a strategic edge over competition. Proliferation in data volumes, complexity of data sources along with real-time information requirements demand fresh approaches to designing business intelligence solutions. The challenges of designing high performance data warehousing environments that meet the varying and evolving demands of businesses require exceptional skills.

The DW and BI Center of Excellence distills information from projects executed, identifies technology trends and provides thought leadership to the entire organization. The group sets direction, refines methodologies and processes for data warehouse development and shares best practices. The group is also involved in the research of areas relevant to businesses today.

Research Areas:

- Performance Management High performance corporations all use information to differentiate themselves from the competition. Defining strategy, translating strategy to measurable objectives and effectively managing performance requires careful integration, using a set of metrics, processes and tools. Regulatory compliance demands have fuelled the demand for performance management.

- Very Large Data Warehouses With complex data sources and explosion in data volumes, the volumes of data required to be stored in a data warehouse is growing at a frantic pace. Terabyte size data warehouses are very common these days. The impact of this on DW environments span architecture, hardware platforms, storage systems, tool selection, data modeling, ETL and end-user reporting. Fresh approaches are required to scale the data warehouse gracefully and optimize performance.

- Business Analytics Leveraging business data can be a challenge for companies that need to respond to rapidly evolving markets and changing customer dynamics. The goal of high-end business analytics is to turn individually useful, but often marginalized data resources, into something that lets business managers immediately grasp the dynamic state of their business. The areas researched currently include supply chain and customer analytics.

- Technology Selection Today's marketplace is crowded with numerous vendors and products, often with competing claims. With many new entrants and varying degrees of product maturity, cutting through the maze is never easy. Technology too is constantly evolving and multiple choices and architectures are available to suit multiple requirements.

- Information Quality Many data warehousing initiatives fail due to poor data quality. It is important to define data quality from the customer's perspective and then define architecture and processes to effectively manage this. This includes preventing recurrence of data defects as well as implementing data cleansing routines.

- Managing Data Warehousing Environments Building a data warehouse is only one part of the story. A right environment is critical to effect transformation by utilizing this information efficiently and effectively. This includes understanding critical success factors, ensuring management support, identifying risks and preparing mitigation plans and putting in place proper data governance and stewardship programs.