The data architecture defines the data along with the schemas, integration, transformations, storage and workflow required to enable the analytical requirements of the information architecture. A solid data architecture is a blueprint that helps align your company’s data with its business strategies. The data architecture guides how the data is collected, integrated, enhanced, stored, and delivered to business people who use it to do their jobs. It helps make data available, accurate and complete so it can be used for business decision-making.
Data architecture is important for many reasons, including that it:
- Helps you gain a better understanding of the data.
- Provides guidelines for managing data from its initial capture in source systems all the way to information consumption by business people
- Provides a structure upon which to develop and implement data governance.
- Helps with enforcement of security and privacy.
- Supports your BI and DW activities, particularly Big Data.
Data architecture has grown far more sophisticated than its hub-and-spoke roots. We recommend an analytical data architecture, which is a hybrid model.
How we've helped others with their data architecture needs:
- Revitalized the bottlenecked data architecture of a large financial firm, supporting their needs for trading across worldwide exchanges and over one billion trades per day.
- When configuring custom machinery, a heavy equipment manufacturer was forced to use paper documents because data could not be shared between the manufacturing plants, engineering departments and retail outlets. Our data architecture solution helped obtain, synchronize and update data from the various sources so they could develop the specifications, configure the products and deliver them to the customers more quickly, efficiently and cost-effectively.
