BI: How Can Your High-Performance BI System Meet Expectations When You

Feed It 85 Octane Data

Making Data Quality Part of the Data Life CycleRay McGlew raymcglew@gmail.com

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BI Failure Reasons

Gartner: 70%-80% BI Projects Fail• Lack of Business Support and Ownership• Poor Quality Data• Lack of Requirements• Scope Creep• Funding• Big-Bang Approach

Life Cycle of Data

• Creation (usually transactions)• Operational Use• Analytical Use• Destruction

Who “Owns” The Data?

• IT responsible for conserving it– Restrict use according to rules– Providing access– Keeping it safe

• Business responsible for managing it– Create rules for IT to use– Providing IT with requirements for access

• Bottom line… it is a Corporate Resource

Data Concerns

• Privacy – Credit Cards– Health Records

• Security• Accuracy• Usability• Availability

Regulatory Compliance

• Privacy regulations• Legal limits on how long you can keep certain

data• Providing lineage on data used for reporting– Sarbanes Oxley– SEC filings

Quality Data

• Easiest to clean at the source• Some methods to “clean” data– Standardize– Validate

• Data Cleansing Tools

Data Cleansing

Data Governance

“Data governance (DG) refers to the overall management of the availability, usability, integrity, and security of the data employed in an enterprise. “

Data Governance Facets

• Data Stewardship• Data Dictionary/Glossary• Master Data Management• Strong Management Promotion

Data Stewardship

• Splits responsibility for ensuring great data• Business– Defines what important data elements are– Defines the rules for acquiring data– Looks for cross-organizational uses

• IT– Responsible for technical methods– Acquires and maintains tools

Data Dictionary

• Platform for spreading the knowledge• Is used in conjunction with reporting tools• The more data knowledge is used, the better it

gets• Can be started using in-house tools• Starting point for Master Data Management

Master Data Management

• Data Governance should drive MDM• Technology – Facilitates– NOT the driver

Strong Management Promotion

• Cross-functional at the highest level of the organization

• Will require funding• Must break through “It will cost my

department to improve the data quality so their department can save time “

Data Governance and Lifecycle

• Data Creation– Standard values– Validation at the source

• Operational use– Required for some customers and vendors

• Analytical use– Easier to integrate across systems and groups

• Destruction

Data Governance is NOT a Program!

• Culture Change• Integrated with other activities– Business Intelligence– Business Process Re-engineering– ERP Implementation– Mergers

Data Governance Tips

• Prioritize– Based on business value– Based on Pain– Low Hanging Fruit

• Don’t try to boil the ocean!

Resources

DAMA International (www.dama.org)Enterprise Data World

DAMA Philadelphia (www.dama-phila.org)Data Governance (www.datagovernance.com)Data Governance Professionals Org (www.dgpo.org)

Love your data, and stay the course, for it will be with you long after flashy apps are gone.