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Business Intelligence Functional Approach Chris Frederick University of Notre Dame

Business Intelligence Functional Approach Chris Frederick University of Notre Dame. Traditional BI: A pictorial summary. What you get. What you want. What happened?. Customer Unsatisfied Delivery late and incomplete Key issues: Insufficient collaboration Low accountability

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Business Intelligence Functional Approach Chris Frederick University of Notre Dame

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  1. Business Intelligence Functional ApproachChris FrederickUniversity of Notre Dame

  2. Traditional BI: A pictorial summary

  3. What you get What you want

  4. What happened? • Customer Unsatisfied • Delivery late and incomplete • Key issues: • Insufficient collaboration • Low accountability • User doesn't know all the requirements up front • Bad data • No shared data definitions (lack of data governance) • Overly Complex and hard to maintain • Tools are too difficult

  5. Waterfall didn’t work

  6. Be Agile A scrum board

  7. Are we getting the right information into peoples hands? Write user “stories” that deliver business value.

  8. Three days later…

  9. Priorities change Actual Report Original User Story

  10. Breakthrough: In-Memory BI The measure of its usefulness involves how easily and quickly you can ask, refine, and reframe questions of the data.

  11. “Hot” In-Memory BI tools Microsoft PowerPivot for Excel

  12. Work with partners who are “shovel ready” • Highly motivated • Available - can commit people resources • Well understood business problem

  13. co-locate(get out of the server room!) Daily Stand ups are the best!

  14. The product owner gives the demo. • IT does not give the demo. • Invite a broad range of campus BI users. • About two demos per project feels about right. Schedule Live BI Demos

  15. Learn in the least costly manner Data Gov. Burned In? Data Gov. Complete? Relational Data Warehouse (star schema) Data Governance Process No Yes No New Idea! Enterprise BI Team BI (in-memory) Personal BI (in-memory) Yes (Key Stakeholders) (campus-wide fine-grain access) (Key Stakeholders & their team) Increasing Data Quality and Access 1x 2x – 4x 8x Cost of

  16. What you get

  17. Questions?cfreder2@nd.edu

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