Data WareHousing Services

The success of a data warehousing initiative depends on vision and the long term strategy formulated at the conceptualization stage. We work closely with clients to build a robust strategy, which forms the basis for the deployment of the data warehousing environment. The strategy phase is followed by user requirement analysis which forms the basis of the design and the functionality included in the data warehouse. The logical design is achieved by designing prototypes and iteratively refining they based on the user feedback. This ensures user commitment in the initiative which is the key to the success and also provides a sense of ownership with the user community as the design is inherently user-centric.

In a typical life cycle the business requirements are mapped to the source systems to decide the data elements that will be extracted. In some cases, all the requisite information is not available from the legacy systems. These need to be acquired from alternative or external data sources (or data providers). The data elements are matched to the information requirements and a logical model is developed. The logical model undergoes iterations to exactly match the analysis and reporting requirements. At a stage where the logical model can cater to the complete requirements, a detailed dimensional model is prepared. The dimensional model will form the basis for the DW. The benefits of this approach are continuous user participation and any errors are identified and eliminated in the earlier stages through collaborative functioning.

The methodology encapsulates the Rapid Application Development (RAD) principles which are critical for the success of a data warehousing project. Capturing business requirements takes place using Joint Requirements Planning sessions with participants from user community and Cognizant team. A prototype is developed based on the business requirements using Joint Application Development workshops. The prototype is the basis for capturing requirements accurately and soliciting user feedback. As the prototype stabilizes, the design and the architecture for the data warehouse are defined. The construction phase would build the prototype in to a workable version after rigorous testing. Typically around 35 to 50 percent of effort is spent to strategize the DW, project scoping and requirements capturing. About 50 to 65 percent of effort goes to development and testing. As Development and unit testing is done offshore, this dramatically reduces the overall development cost and ensures faster turn leveraging the extended onsite-offshore development time cycle.

Technology Expertise:
Our depth of experience across the entire spectrum of the data warehousing tools enable us to implement a best of breed solution that is ideal for your scenario. Our skills cover:

• Business Intelligence tools ranging from OLAP tools like MicroStrategy, Brio, Business Objects, Cognos, Hyperion, Information Advantage, Informix Met cube, Web focus, Hummingbird BI Suite
• Extraction Transformation Cleansing and Loading (ETCL) tools like Informatica, Datastage, Datajunction, DataMirror, John Henry, Trillium, DataFlux, ETI Extract, SAS Warehouse Administrator
• Databases like Oracle, MS SQL Server 2000, Sybase, DB2, Informix, Redbrick, Teradata; Data mining Tools like SAS Miner, Intelligent Miner, Darwin; and end to end tools such as SAP Business Warehouse suite and Oracle Data Warehousing product suite.