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Agile Business
Intelligence
Applying Best Practices in Software
Development
to BI, Analytics, and Data Driven Decisions
● Agile Background
● Agile and BI
● Trends and applications
Overview
● Started in 2001
● Origins in DARPA and Toyota
○ Waterfall Software Development
○ Lean Manufacturing
● Agile Manifesto written in 2001
Individuals and interactions over processes and tools
Working software over comprehensive documentation
Customer collaboration over contract negotiation
Responding to change over following a plan
What Is Agile?
Source: http://en.wikipedia.org/wiki/Waterfall_software_development
Waterfall Software Development
Waterfall's Failures
● Iterations - months to years
● Customer lock in
● Requirements rarely met
● There's just one little secret...
Waterfall's Failures
● Iterations - months to years
● Customer lock in
● Requirements rarely met
● There's just one little secret...
“Agile” was mentioned in the original paper
(back in 1970)!
Why Agile Wasn't Feasible Then
● Testing was expensive
○ Needed more hardware
○ Tooling?
● Automation was costly
○ Needed more hardware
○ Software would be custom
● Hardware and software were prohibitive
○ Mainframes cost $4.6 million
○ Little to no integration
Cost source: http://mjperry.blogspot.com/2007/08/ibm-mainframe-computer-in-1970-pictured.html
Source: http://en.wikipedia.org/wiki/Agile_software_development
Why Agile?
● Customer satisfaction
● Business/IT Interaction
● Fail early, fail often
● Working software = progress
● Team ownership - self organized
● Faster adaptation
Source: http://en.wikipedia.org/wiki/Agile_software_development
Who to Involve?
● BI team (5-6 people)
● Scrum Master - guide of the team
● Project Manager - guide of the business
● Business Stakeholder - Requestor of work
What Type of Agile?
Source: http://www.leadingagile.com/agile-training/
Where to Start?
● Project (Scrum)
○ Great for piloting agile
○ Team is consistent
○ Find what works in your team
● Support (Kanban)
○ Great for mature agile teams
○ Team is consistent, but roles will change
○ Less structure than Scrum
Implementation Pitfalls
Pitfall 1: The Balancing Act
“We need the time to
improve, streamline,
etc.” “Get it out the door
and with the
customer!”
Pitfall 1: The Balancing Act
“We need the time to
improve, streamline,
etc.” “Get it out the door
and with the
customer!”
Pay off debt, find ways
to prevent it.
Release as fast as
possible, without too
much compromise to
quality
Pitfall 2: Working with the same
tools
● Most BI Tools are not able to support:
○ Continuous Integration
○ Test Driven Development
○ True Version Control
○ Collaboration and fast iterations
● agile <> Agile
Pitfall 3: In Teams We Don’t Trust
● Business Team wants full control
● BI not treated as software development
● BI Team doesn’t involve Business Team
Implementation Tips
Where to Start?
● Find a Stakeholder (the bridge builder)
● Find a Scrummaster (the negotiator)
● Pick agile tools
● Pilot Agile in a small group
Where to Grow
● Test Driven Development
● Automation/Continuous Integration
● Agile Data Warehouse Modeling
○ Hyper-normalized
■ Anchor modeling
○ Hyper-generalized
■ Data Vault

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Agile Business Intelligence

  • 1. Agile Business Intelligence Applying Best Practices in Software Development to BI, Analytics, and Data Driven Decisions
  • 2. ● Agile Background ● Agile and BI ● Trends and applications Overview
  • 3. ● Started in 2001 ● Origins in DARPA and Toyota ○ Waterfall Software Development ○ Lean Manufacturing ● Agile Manifesto written in 2001 Individuals and interactions over processes and tools Working software over comprehensive documentation Customer collaboration over contract negotiation Responding to change over following a plan What Is Agile?
  • 5. Waterfall's Failures ● Iterations - months to years ● Customer lock in ● Requirements rarely met ● There's just one little secret...
  • 6. Waterfall's Failures ● Iterations - months to years ● Customer lock in ● Requirements rarely met ● There's just one little secret... “Agile” was mentioned in the original paper (back in 1970)!
  • 7. Why Agile Wasn't Feasible Then ● Testing was expensive ○ Needed more hardware ○ Tooling? ● Automation was costly ○ Needed more hardware ○ Software would be custom ● Hardware and software were prohibitive ○ Mainframes cost $4.6 million ○ Little to no integration Cost source: http://mjperry.blogspot.com/2007/08/ibm-mainframe-computer-in-1970-pictured.html
  • 9. Why Agile? ● Customer satisfaction ● Business/IT Interaction ● Fail early, fail often ● Working software = progress ● Team ownership - self organized ● Faster adaptation Source: http://en.wikipedia.org/wiki/Agile_software_development
  • 10. Who to Involve? ● BI team (5-6 people) ● Scrum Master - guide of the team ● Project Manager - guide of the business ● Business Stakeholder - Requestor of work
  • 11. What Type of Agile? Source: http://www.leadingagile.com/agile-training/
  • 12. Where to Start? ● Project (Scrum) ○ Great for piloting agile ○ Team is consistent ○ Find what works in your team ● Support (Kanban) ○ Great for mature agile teams ○ Team is consistent, but roles will change ○ Less structure than Scrum
  • 14. Pitfall 1: The Balancing Act “We need the time to improve, streamline, etc.” “Get it out the door and with the customer!”
  • 15. Pitfall 1: The Balancing Act “We need the time to improve, streamline, etc.” “Get it out the door and with the customer!” Pay off debt, find ways to prevent it. Release as fast as possible, without too much compromise to quality
  • 16. Pitfall 2: Working with the same tools ● Most BI Tools are not able to support: ○ Continuous Integration ○ Test Driven Development ○ True Version Control ○ Collaboration and fast iterations ● agile <> Agile
  • 17. Pitfall 3: In Teams We Don’t Trust ● Business Team wants full control ● BI not treated as software development ● BI Team doesn’t involve Business Team
  • 19. Where to Start? ● Find a Stakeholder (the bridge builder) ● Find a Scrummaster (the negotiator) ● Pick agile tools ● Pilot Agile in a small group
  • 20. Where to Grow ● Test Driven Development ● Automation/Continuous Integration ● Agile Data Warehouse Modeling ○ Hyper-normalized ■ Anchor modeling ○ Hyper-generalized ■ Data Vault