Data Warehousing

At the highest level, designing a data warehouse involves creating, manipulating, and mapping models. These models are conceptual, logical, and physical (data) representations of the business and end-user information needs. Some models already exist in source systems and must be reverse engineered. Other models, such as those defining the data warehouse are created from scratch. Creating a data warehouse requires designers to map data between source and target models, capturing the details of the transformation in a meta data repository. Certain key business objectives for companies are driving the demand for Data Warehousing Infrastructure. These include:

• Necessary data is unavailable

• Lack of collaboration with end users

• Lack of explicit end-user cognitive and conceptual models

• Data needed for decisions is delayed

• Dimensions and facts not conformed

• Insufficiently verbose data

• Data in awkward formats

• Sluggish delivery of data

• Data locked in a report or dashboard

• Prematurely aggregated data

Our Data Warehousing team has expertise in delivering comprehensive solutions for your needs including:

• End-to-end solutions design and development

• Business requirements analysis and data modeling

• ETL architecture and development

• Custom reporting and OLAP solutions

• Data Mining