Academy TechNotes
ATN Volume 3, Number 7, 2012
Triple strategy for data warehouse projects
E
nterprise data warehouse (EDW) should deliver unified consistent information, but usually doesn’t, due to conflicts in master data and a lack of common understanding of data sense (metadata). So the typical complaints both from IT and business users are: “We have implemented enterprise data warehouse and we don’t need metadata management. Why does EDW deliver information of improper quality?” “We have an enterprise master data management (MDM) system in production. Why can’t we agree on data sense and terminology?” “We have developed our company’s business glossary. Why do our business users still receive contradictive reports?” These problems can be solved by parallel execution of three strategic projects: metadata integration, master data integration and data integration. These three interrelated projects should be performed simultaneously in order to implement EDW: 1.
Enterprise metadata integration establishes common understanding of data and master data sense.
2.
Master data integration eliminates conflicts in data and metadata coding in various information systems.
3.
Data integration provides end users with data as a single version of truth based on consistent metadata and master data.
This triple strategy provides effective interaction of data, metadata, and master data management systems, eliminates modules with similar functionality, lowers total cost of ownership and increases user confidence in EDW data. The triple strategy allows implementing the agreed architecture, environment, life cycles, and key capabilities for data, metadata and master data management systems. As a rule, developers need to quickly demonstrate at least an insignificant success in data integration. Creation of data, metadata, and master data management environment is a high priority task. But business users do not
Sabir Asadullaev
see immediate benefits from that environment. Therefore, two or three pilot projects should be chosen for the first phase. Projects should provide minimum acceptable functionality of the future EDW. The project team needs to analyze the results of pilot projects and to adjust the tasks of data metadata, and master data integration. The second step is to choose new pilot projects to reach the basic functionality of the EDW. Data, metadata and master data management environment must be developed enough to meet the requirements of basic EDW functionality. Projects results should be reexamined after completion of pilot projects of the second phase. The next step should be the development of a fully functional EDW, which is impossible without a comprehensive support by data, metadata and master data management environment. The EDW development project is not completed when EDW is delivered into production. If new systems can provide information important for data analysis across the enterprise, these new systems must be connected to the EDW. In order to avoid integration issues it is desirable to create new systems based on the capabilities of a data, metadata and master data management environment. In turn, a data, metadata and master data management environment should be changed according to the needs of new systems. Therefore, data, metadata and master data management environment must evolve as long as the company and its IT systems exist, which is indicated on the illustration by the arrows that go beyond the schedule. About the author: Sabir Asadullaev is a Distinguished IT Architect (Open Group), Executive IT Architect in IBM Russia SWG
Please consider following @IBMAoT on Twitter and using the hashtag #IBMA`oT when mentioning IBMAoT in social media
© Copyright IBM Corporation 2012
For more information please visit the IBMAoT website.