BI Data Management

Data management includes all the disciplines related to managing data as a valuable resource. It is commonly referred to as Data Resource Management, which is defined as "the development and execution of architectures, policies, practices and procedures that properly manage the full data lifecycle needs of an enterprise."

Why Data Management Is Iimportant

A Teradata survey in 2005 revealed that "over 80 percent of executives surveyed in Europe, Australia and New Zealand said that data has increased over the past five years and about 70 percent expect the increases to continue for the next five years"....that has driven data solutions to the forefront of business capability.

"Significantly, 71 percent say they are using or moving toward enterprise data warehousing .....And close to 90 percent of all respondents say that enterprise data warehousing improves company profitability, productivity and long-term growth, with over 80 percent citing customer service and customer expansion."

What is Data Management?

Data Management includes a number of data related processes and functions:

• Data Analysis
• Data Modeling
• Database Administration
• Data Governance
• Meta Data Management
• Master Data Management
• Data Architecture
• Data Warehousing
• Data Movement
• Data Mining
• Data Quality Assurance
• Data Security
• Database Management System

Data Management In Business Intelligence

Data Management should be isolated from application development in the BI Program.

A lot of BI programs are constrained by lack of data delivery knowledge.

BI maturity is aligned with DM maturity, meaning data needs to evolve in step with the applications being delivered. If this is done managed, analytic capability will be severely constrained and users will become frustrated, risking adoption of the entire BI program.

Measuring Data Management Capabiltiy

BI Project Scorecards are a good way of managing the alignment of data development and application development.

Data maturity is not just in data integration but also in the usage of data as a business asset:

1. Reuse - the sharing and reuse of data across the organisation
2. Robust data modelling capability
3. Ancillary meta data backed into each BI projects, in increments

Usage of data is a KPI of BI.

Next: Master Data Management

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