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1
BI and Dashboarding Best Practices
Dorien Gardner, Solution Engineer
2
Abstract
 This session focuses on Business Intelligence Best Practices with an
emphasis on dashboard design and perform...
3
Agenda
Types of Business Intelligence
General best practices for BI
Dashboards
Performance techniques
Reporting
Co...
4
Types of Business Intelligence
 Reporting
 Analysis
• Spreadsheet analysis
• Ad-hoc
• Visualization tools
• Exploratio...
5
Types of Business Intelligence Users
 Executive team
• Wants quick pulse of key business drivers
• Dashboards, score ca...
6
Business Intelligence Best Practices
 Insure data is clean and accurate
• Obviously garbage in = garbage out
• Data cle...
7
Business Intelligence Best Practices
 Leverage the secondary (Hot Backup) for BI dashboards
• Create aggregate tables f...
8
Business Intelligence Best Practices
 Leverage visual alerts
• Provide focus on the things that are most impacting busi...
9
Dashboards
10
Why are they so valuable?
Easier than opening dozens of reports
Readily provides key information
Improves productivi...
11
Types of Dashboards
Strategic
• Executive
• Measure high level performance
• More KPIs across functional areas
• Focus...
12
Types of Dashboards
Analytical
• Help understand the who, what, how, why
• Highly interactive
• Drill to root cause
• ...
13
Types of Dashboards
Operational
• For monitoring and lower level decision making
• High use of alerts
• Data latency i...
14
Planning your Dashboard
 Identify your consumer type(s)
 What data do they need?
• KPI, metrics, trend, target, varia...
15
Planning your Dashboard
 Who are you building the dashboard for?
• Sales
• Marketing
• Supply Chain
• Finance…
 Draw ...
16
Planning your Dashboard
 Design the dashboard or TAB for a specific Business Purpose
 Typically one subject area per ...
17
Layout Considerations
 How do people read? (left to right; top to bottom)
 Allocate the size of objects based on thei...
18
Layout Considerations
 Consistency of color palette
 Naming conventions (i.e., sales vs revenue)
 Having viable desc...
19
 Minimize the number of CorVu analytic queries
• Utilize these mainly when merging from heterogeneous data sources
 C...
20
 Utilize native pre- and post-processing features
• SELECT ORDERS WITH INVOICE.DATE # ""
• select trx.mst with Invoice...
21
Performance
22
KPIs at Highest Aggregation
KPIs Mid-Grain Aggregations
Lowest Grain i.e., Transactional Data
Use of Aggregations
© 201...
23
Aggregate Tables
©2015 Rocket Software, Inc. All Rights Reserved.
24
Use Subscriber for BI and Reporting
Business intelligence and reporting
uses 10X resources than average
application
M...
25
BI Account
MV Database Server
MV DB
MV HADR/HotBackup/Report Server
MV DB
HADR/HOT Backup/Reporting Server
 Replicate ...
26
Reporting
27
 Query to Visual Report
wizard
 Highly formatted reports
• Cover sheets, summary
pages and
report annexes
 Report sc...
28
Reporting
Scheduling and distribution
Report bursting
©2015 Rocket Software, Inc. All Rights Reserved.
29
CorVu NG vs. Discover
30
CorVu vs. Discover
CorVu Discover
Developer/IT focused End user focused
High value add for partners Lower value add
IT/...
31
Additional Resources
 https://www.rocketsoftware.com/solutions/bi-and-analytics
 MVU@rocketsoftware.com
©2015 Rocket ...
32
Summary
 Types of Business Intelligence
 Some key Business Intelligence best practices
 Dashboards types and design ...
33
Disclaimer
THE INFORMATION CONTAINED IN THIS PRESENTATION IS PROVIDED FOR INFORMATIONAL PURPOSES ONLY.
WHILE EFFORTS WE...
34
Trademarks and Acknowledgements
The trademarks and service marks identified in the following list are the exclusive pro...
35
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BI and Dashboarding Best Practices

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This session focuses on Business Intelligence Best Practices with an emphasis on dashboard design and performance techniques. Learn about the different types of users and consumers of BI and how they impact your development strategy.

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BI and Dashboarding Best Practices

  1. 1. 1 BI and Dashboarding Best Practices Dorien Gardner, Solution Engineer
  2. 2. 2 Abstract  This session focuses on Business Intelligence Best Practices with an emphasis on dashboard design and performance techniques. Learn about the different types of users and consumers of BI and how they impact your development strategy. ©2015 Rocket Software, Inc. All Rights Reserved.
  3. 3. 3 Agenda Types of Business Intelligence General best practices for BI Dashboards Performance techniques Reporting CorVu NG with MV best practices CorVu NG vs. Discover ©2015 Rocket Software, Inc. All Rights Reserved.
  4. 4. 4 Types of Business Intelligence  Reporting  Analysis • Spreadsheet analysis • Ad-hoc • Visualization tools • Exploration  Monitoring • Dashboards • Key Performance Indicators (KPIs) • Business performance management  Predictive • Data mining • Predictive modeling © 2015 Rocket Software, Inc. All Rights Reserved.
  5. 5. 5 Types of Business Intelligence Users  Executive team • Wants quick pulse of key business drivers • Dashboards, score cards, EPM, BPM  Data analyst • Explores and finds new insights • Creates insight for people within the organization • Dashboards are not typically their preferred consumption  Business user • They make decisions • Don't want to build from scratch • They want the critical information to make them successful • They want the insights to be actionable ©2015 Rocket Software, Inc. All Rights Reserved.
  6. 6. 6 Business Intelligence Best Practices  Insure data is clean and accurate • Obviously garbage in = garbage out • Data cleansing is imperative (particularly for any predictive analysis) • You cannot make accurate business decisions based on inaccurate data  Work with customers to determine best KPIs/Metrics  Dictionary descriptions should be user friendly and meaningful • Use clear naming conventions for descriptions that have obvious meaning • Centralize the metadata definitions for consistency • Centralize calculations as much as possible (one version of the truth) • Create and use alternate dictionaries © 2015 Rocket Software, Inc. All Rights Reserved.
  7. 7. 7 Business Intelligence Best Practices  Leverage the secondary (Hot Backup) for BI dashboards • Create aggregate tables for the various hierarchical levels • Initial KPI view should be highest possible level • Enough information to determine next course of analysis  Provide a guided path analysis • Allow user to drill to each next level of detail based on the information • Provide comparative analysis to determine trend vs. anomaly • Basis for root-cause analysis • Critical for a performant dashboard © 2015 Rocket Software, Inc. All Rights Reserved.
  8. 8. 8 Business Intelligence Best Practices  Leverage visual alerts • Provide focus on the things that are most impacting business • Manage by exception (best/worst based on a trend)  High and low latency data requirements • Acceptable age of data needed to make timely decisions • What is real time? • Historical trend analysis  View BI from both top down AND bottom up  Utilize professional services for Business Intelligence consulting © 2015 Rocket Software, Inc. All Rights Reserved.
  9. 9. 9 Dashboards
  10. 10. 10 Why are they so valuable? Easier than opening dozens of reports Readily provides key information Improves productivity and decision making Focuses the attention on the target and goals Long lasting ©2015 Rocket Software, Inc. All Rights Reserved.
  11. 11. 11 Types of Dashboards Strategic • Executive • Measure high level performance • More KPIs across functional areas • Focused on trend analysis and predictive • Data latency is not critical • Long decision horizon ©2015 Rocket Software, Inc. All Rights Reserved.
  12. 12. 12 Types of Dashboards Analytical • Help understand the who, what, how, why • Highly interactive • Drill to root cause • Data latency requirements are mixed • Leverage alerts to help drive analytic navigation • Mid-decision horizon ©2015 Rocket Software, Inc. All Rights Reserved.
  13. 13. 13 Types of Dashboards Operational • For monitoring and lower level decision making • High use of alerts • Data latency is low (regular live updates) • Short decision horizon ©2015 Rocket Software, Inc. All Rights Reserved.
  14. 14. 14 Planning your Dashboard  Identify your consumer type(s)  What data do they need? • KPI, metrics, trend, target, variance • Is it available and from where? • Trust of the data (one version of the truth)  What security needs to be applied? ©2015 Rocket Software, Inc. All Rights Reserved.
  15. 15. 15 Planning your Dashboard  Who are you building the dashboard for? • Sales • Marketing • Supply Chain • Finance…  Draw out and plan the general layout, what and where  Show draft and get feedback BEFORE building ©2015 Rocket Software, Inc. All Rights Reserved.
  16. 16. 16 Planning your Dashboard  Design the dashboard or TAB for a specific Business Purpose  Typically one subject area per tab (except scorecard)  Do not overwhelm the users or boil the ocean ©2015 Rocket Software, Inc. All Rights Reserved.
  17. 17. 17 Layout Considerations  How do people read? (left to right; top to bottom)  Allocate the size of objects based on their importance  Leverage report links for related reports • Too many objects on a dashboard will have a performance impact  Elements need to be well labeled • There should be no question what a particular chart or report ID is for  Avoid scrolling as much as possible ©2015 Rocket Software, Inc. All Rights Reserved.
  18. 18. 18 Layout Considerations  Consistency of color palette  Naming conventions (i.e., sales vs revenue)  Having viable descriptions  One version of truth for calculations  Direct the user to what is important  Use conditional formatting (colors and shapes)  Use annotations and reference lines ©2015 Rocket Software, Inc. All Rights Reserved.
  19. 19. 19  Minimize the number of CorVu analytic queries • Utilize these mainly when merging from heterogeneous data sources  Create and leverage dictionary correlatives to pull data from multiple related tables • TRANS(‘CUSTOMERS’,CustomerID, ‘Region’, ‘X’) • f;8(tterritories;x;;2);(tsalesreps;x;;1) • A and S types in UniVerse are interpreted and not compiled so this may be less efficient than utilizing CorVu Analytic Queries  When data latency is not as important, leverage scheduled cached queries CorVu Specific Tips © 2015 Rocket Software, Inc. All Rights Reserved.
  20. 20. 20  Utilize native pre- and post-processing features • SELECT ORDERS WITH INVOICE.DATE # "" • select trx.mst with Invoice.Year NE "" AND with Sales.Rep NE "" • GET-LIST ClosedOrders  For complex data access and rules, consider creating a Virtual Data Source via a web service call • Reuse existing logic from your basic programs for data retrieval • Web services could also be used for actionable BI and database write-backs © 2015 Rocket Software, Inc. All Rights Reserved. CorVu Specific Tips
  21. 21. 21 Performance
  22. 22. 22 KPIs at Highest Aggregation KPIs Mid-Grain Aggregations Lowest Grain i.e., Transactional Data Use of Aggregations © 2015 Rocket Software, Inc. All Rights Reserved. PassContext Dimensional examples • KPI/Metrics by Year, QTR, Country, Region, Product Line • KPI/Metrics by Year- QTR-Month, Country- Region-State, Line- Category Define appropriate Indexes
  23. 23. 23 Aggregate Tables ©2015 Rocket Software, Inc. All Rights Reserved.
  24. 24. 24 Use Subscriber for BI and Reporting Business intelligence and reporting uses 10X resources than average application Move reporting and analysis to Subscriber/Hot Backup Save valuable computing resources on production © 2015 Rocket Software, Inc. All Rights Reserved.
  25. 25. 25 BI Account MV Database Server MV DB MV HADR/HotBackup/Report Server MV DB HADR/HOT Backup/Reporting Server  Replicate to Secondary Server ©2015 Rocket Software, Inc. All Rights Reserved. Triggers or Automated Batch Columnar Database  Leverage Triggers or scheduled process to prepare and aggregate data  Aggregate data into another MV Account, add indexes, stratify files etc. Create BI specific dictionaries  Data Options  Load data into an OLAP data Cube  Load data into a Columnar data-store
  26. 26. 26 Reporting
  27. 27. 27  Query to Visual Report wizard  Highly formatted reports • Cover sheets, summary pages and report annexes  Report scheduling and email  Multiple data sources  Output graphical reports in Excel, HTML or PDF  Deploy to web users CorVu NG Report Summary © 2015 Rocket Software, Inc. All Rights Reserved.
  28. 28. 28 Reporting Scheduling and distribution Report bursting ©2015 Rocket Software, Inc. All Rights Reserved.
  29. 29. 29 CorVu NG vs. Discover
  30. 30. 30 CorVu vs. Discover CorVu Discover Developer/IT focused End user focused High value add for partners Lower value add IT/partner pre-build content and deploy Can have base templates/then user builds Pixel perfect control Limited layout control Monitoring/dashboard/reporting Analysis/exploration focused Pre-defined navigation (by developer) Flexible drill/navigation Embeddable BI (operational) N/A Can embed text entry fields Strong collaboration (live chat…) © 2014 Rocket Software, Inc. All Rights Reserved.
  31. 31. 31 Additional Resources  https://www.rocketsoftware.com/solutions/bi-and-analytics  MVU@rocketsoftware.com ©2015 Rocket Software, Inc. All Rights Reserved.
  32. 32. 32 Summary  Types of Business Intelligence  Some key Business Intelligence best practices  Dashboards types and design principals  Performance considerations and best practices  MultiValue specific best practices with CorVu NG  CorVu NG vs. Discover ©2015 Rocket Software, Inc. All Rights Reserved.
  33. 33. 33 Disclaimer THE INFORMATION CONTAINED IN THIS PRESENTATION IS PROVIDED FOR INFORMATIONAL PURPOSES ONLY. WHILE EFFORTS WERE MADE TO VERIFY THE COMPLETENESS AND ACCURACY OF THE INFORMATION CONTAINED IN THIS PRESENTATION, IT IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED. IN ADDITION, THIS INFORMATION IS BASED ON ROCKET SOFTWARE’S CURRENT PRODUCT PLANS AND STRATEGY, WHICH ARE SUBJECT TO CHANGE BY ROCKET SOFTWAREWITHOUT NOTICE. ROCKET SOFTWARE SHALL NOT BE RESPONSIBLE FOR ANY DAMAGES ARISING OUT OF THE USE OF, OR OTHERWISE RELATED TO, THIS PRESENTATION OR ANY OTHER DOCUMENTATION. NOTHING CONTAINED IN THIS PRESENTATION IS INTENDED TO, OR SHALL HAVE THE EFFECT OF: • CREATING ANY WARRANTY OR REPRESENTATION FROM ROCKET SOFTWARE(OR ITS AFFILIATES OR ITS OR THEIR SUPPLIERS AND/OR LICENSORS); OR • ALTERING THE TERMS AND CONDITIONS OF THE APPLICABLE LICENSE AGREEMENT GOVERNING THE USE OF ROCKET SOFTWARE. ©2015 Rocket Software, Inc. All Rights Reserved.
  34. 34. 34 Trademarks and Acknowledgements The trademarks and service marks identified in the following list are the exclusive properties of Rocket Software, Inc. and its subsidiaries (collectively, “Rocket Software”). These marks are registered with the U.S. Patent and Trademark Office, and may be registered or pending registration in other countries. Not all trademarks owned by Rocket Software are listed. The absence of a mark from this page neither constitutes a waiver of any intellectual property rights that Rocket Software has established in its marks nor means that Rocket Software is not owner of any such marks. Aldon, CorVu, Dynamic Connect, D3, FlashConnect, Pick, mvBase, MvEnterprise, NetCure, Rocket, SystemBuilder, U2, U2 Web Development Environment, UniData, UniVerse, and wIntegrate Other company, product, and service names mentioned herein may be trademarks or service marks of others. ©2015 Rocket Software, Inc. All Rights Reserved.
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