Your SlideShare is downloading. ×
0
BI: How Can Your High-Performance BISystem Meet Expectations When You       Feed It 85 Octane Data    Making Data Quality ...
Brought to You By:
BI Failure Reasons          Gartner: 70%-80% BI Projects Fail•   Lack of Business Support and Ownership•   Poor Quality Da...
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 i...
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...
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 overallmanagement of theavailability, usability, integrity, and securit...
Data Governance Facets•   Data Stewardship•   Data Dictionary/Glossary•   Master Data Management•   Strong Management Prom...
Data Stewardship• Splits responsibility for ensuring great data• Business  – Defines what important data elements are  – D...
Data Dictionary• Platform for spreading the knowledge• Is used in conjunction with reporting tools• The more data knowledg...
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 ...
Data Governance and Lifecycle• Data Creation  – Standard values  – Validation at the source• Operational use  – Required f...
Data Governance is NOT a Program!• Culture Change• Integrated with other activities  – Business Intelligence  – Business P...
Data Governance Tips• Prioritize   – Based on business value   – Based on Pain   – Low Hanging Fruit• Don’t try to boil th...
ResourcesDAMA International (www.dama.org)     Enterprise Data WorldDAMA Philadelphia (www.dama-phila.org)Data Governance ...
Upcoming SlideShare
Loading in...5
×

BI: How Can Your High-Performance BI System Meet Expectations When You Feed It 85 Octane Data

90

Published on

Many BI projects fail, some because of data issues. Using Data Governance and associated skills such as Master Data Management and Data Stewardship can help improve your information and projects.

Published in: Business
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total Views
90
On Slideshare
0
From Embeds
0
Number of Embeds
0
Actions
Shares
0
Downloads
3
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

Transcript of "BI: How Can Your High-Performance BI System Meet Expectations When You Feed It 85 Octane Data"

  1. 1. BI: How Can Your High-Performance BISystem Meet Expectations When You Feed It 85 Octane Data Making Data Quality Part of the Data Life Cycle Ray McGlew raymcglew@gmail.com
  2. 2. Brought to You By:
  3. 3. 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
  4. 4. Life Cycle of Data• Creation (usually transactions)• Operational Use• Analytical Use• Destruction
  5. 5. 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
  6. 6. Data Concerns• Privacy – Credit Cards – Health Records• Security• Accuracy• Usability• Availability
  7. 7. 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
  8. 8. Quality Data• Easiest to clean at the source• Some methods to “clean” data – Standardize – Validate• Data Cleansing Tools
  9. 9. Data Cleansing
  10. 10. Data Governance“Data governance (DG) refers to the overallmanagement of theavailability, usability, integrity, and security ofthe data employed in an enterprise. “
  11. 11. Data Governance Facets• Data Stewardship• Data Dictionary/Glossary• Master Data Management• Strong Management Promotion
  12. 12. 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
  13. 13. 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
  14. 14. Master Data Management• Data Governance should drive MDM• Technology – Facilitates – NOT the driver
  15. 15. 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 “
  16. 16. 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
  17. 17. Data Governance is NOT a Program!• Culture Change• Integrated with other activities – Business Intelligence – Business Process Re-engineering – ERP Implementation – Mergers
  18. 18. Data Governance Tips• Prioritize – Based on business value – Based on Pain – Low Hanging Fruit• Don’t try to boil the ocean!
  19. 19. ResourcesDAMA International (www.dama.org) Enterprise Data WorldDAMA 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.
  1. A particular slide catching your eye?

    Clipping is a handy way to collect important slides you want to go back to later.

×