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.
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 fueled 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.
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
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.
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.