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30 Reasons You Still Need to Stage Your Data
www.senturus.com/blog/30-reasons-you-still-need-to-stage-your-data/
November 29, 2016 Business Strategy & Perspectives
If you sit in on Senturus team meetings, you’ll hear impassioned discussions about how folks need to properly stage
their data. And we’re not talking about merely replicating tables in a separate database offline and calling that a data
warehouse. We mean a high performance, business-centric, subject-area-organized system, aligned with the
company’s strategic goals. One with validated and secure metrics that is easy to pull data from and as a result
enjoys high adoption rates across the organization.
As technologies advance and data types grow, the more we see the need for solidly architected data warehouses.
Our CEO and co-founder John Peterson can wax poetic on the subject. He recently pulled together this quick list of
real-life, practical reasons why a data warehouse plays such an important role in any data driven organization.
(We’d bet John’s got another good 30 reasons in his back pocket!)
To make data truly usable and valuable, it needs to be transformed into business centric terms and metrics that
support organizational decision-making and enriched to provide roll up and drill down access into information. This
transformation needs to take place somewhere between the raw source and the final report/analysis. It becomes a
question of where and how you handle that transformation, upstream or downstream.
Addressing the transformation downstream simply forces business end-users to tackle it themselves, which leads to
the horribly time consuming process of what we call “Excel hell.” It also results in complex, slow and inaccurate self-
service dashboards and reports and data “acquisition aggravation.”
Senturus recommends you do the work upstream by properly staging your data to avoid “Excel hell”… and for at
least 30 other good reasons.
30 Reasons You Still Need to Stage Data
1. Consolidates multiple sources of data
2. Retains history when changing/upgrading systems
3. Captures snapshots and realigns data
1/3
4. Consolidates data from cloud and on-premise
5. Provides persistent storage of critical data
6. Increases efficiency by storing data only once
7. Cleanses data
8. Handles and fixes NULL values
9. Applies universal, one-time filters
10. Improves performance (end-user reports, etc.)
11. Eliminates “expensive” and incorrect joins
12. Transforms complex source data into usable facts
13. Captures strategic business-centric metrics
14. Consolidates and simplifies disparate attribute data
15. Adds mandatory business “dimensional richness”
16. Simplifies complex data relationships
17. Applies logic to complete and align data
18. Facilitates allocation and attribution
19. Provides “insulating layer” from source systems
20. Eliminates complex logic needed in BA layer(s)
21. Allows for “slow-changing dimensions”
22. Captures “slow-changing facts”
23. Eliminates live connections to source data
24. Eliminates spreadmarts and local databases
25. Reduces challenges associated when key person(s) leave
26. Eliminates incorrect calculations by end-users
27. Provides security and controlled access
28. Helps reduce software license fees
29. Enables consolidated dashboards and aligned metrics
30. Enables better dashboards thru context
Benefits of Properly Staged Data
Properly staged data offer numerous strategic advantages to an organization. Benefits include:
Better decisions
Faster actions
Unified strategic direction: what gets measured, gets managed
Greater efficiency: less time in "Excel hell"
Less redundancy and waste
Fewer errors: some can cost $millions
Happier business users
2/3
Greater user adoption
For more on this topic, you can hear direct from John in his recorded webinar Death of the Data Warehouse?
Stay on top of business intelligence topics, read other Senturus blogs at: http://www.senturus.com/blog/.
Data Prep
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30 Reasons You Still Need to Stage Your Data Senturus Blog

  • 1. 30 Reasons You Still Need to Stage Your Data www.senturus.com/blog/30-reasons-you-still-need-to-stage-your-data/ November 29, 2016 Business Strategy & Perspectives If you sit in on Senturus team meetings, you’ll hear impassioned discussions about how folks need to properly stage their data. And we’re not talking about merely replicating tables in a separate database offline and calling that a data warehouse. We mean a high performance, business-centric, subject-area-organized system, aligned with the company’s strategic goals. One with validated and secure metrics that is easy to pull data from and as a result enjoys high adoption rates across the organization. As technologies advance and data types grow, the more we see the need for solidly architected data warehouses. Our CEO and co-founder John Peterson can wax poetic on the subject. He recently pulled together this quick list of real-life, practical reasons why a data warehouse plays such an important role in any data driven organization. (We’d bet John’s got another good 30 reasons in his back pocket!) To make data truly usable and valuable, it needs to be transformed into business centric terms and metrics that support organizational decision-making and enriched to provide roll up and drill down access into information. This transformation needs to take place somewhere between the raw source and the final report/analysis. It becomes a question of where and how you handle that transformation, upstream or downstream. Addressing the transformation downstream simply forces business end-users to tackle it themselves, which leads to the horribly time consuming process of what we call “Excel hell.” It also results in complex, slow and inaccurate self- service dashboards and reports and data “acquisition aggravation.” Senturus recommends you do the work upstream by properly staging your data to avoid “Excel hell”… and for at least 30 other good reasons. 30 Reasons You Still Need to Stage Data 1. Consolidates multiple sources of data 2. Retains history when changing/upgrading systems 3. Captures snapshots and realigns data 1/3
  • 2. 4. Consolidates data from cloud and on-premise 5. Provides persistent storage of critical data 6. Increases efficiency by storing data only once 7. Cleanses data 8. Handles and fixes NULL values 9. Applies universal, one-time filters 10. Improves performance (end-user reports, etc.) 11. Eliminates “expensive” and incorrect joins 12. Transforms complex source data into usable facts 13. Captures strategic business-centric metrics 14. Consolidates and simplifies disparate attribute data 15. Adds mandatory business “dimensional richness” 16. Simplifies complex data relationships 17. Applies logic to complete and align data 18. Facilitates allocation and attribution 19. Provides “insulating layer” from source systems 20. Eliminates complex logic needed in BA layer(s) 21. Allows for “slow-changing dimensions” 22. Captures “slow-changing facts” 23. Eliminates live connections to source data 24. Eliminates spreadmarts and local databases 25. Reduces challenges associated when key person(s) leave 26. Eliminates incorrect calculations by end-users 27. Provides security and controlled access 28. Helps reduce software license fees 29. Enables consolidated dashboards and aligned metrics 30. Enables better dashboards thru context Benefits of Properly Staged Data Properly staged data offer numerous strategic advantages to an organization. Benefits include: Better decisions Faster actions Unified strategic direction: what gets measured, gets managed Greater efficiency: less time in "Excel hell" Less redundancy and waste Fewer errors: some can cost $millions Happier business users 2/3
  • 3. Greater user adoption For more on this topic, you can hear direct from John in his recorded webinar Death of the Data Warehouse? Stay on top of business intelligence topics, read other Senturus blogs at: http://www.senturus.com/blog/. Data Prep 3/3