Chances are, your role in IT has been changing as the needs of the business have changed. But the forces outside your company are now driving that change at an ever increasing pace. This environment means that you have a great opportunity to partner with your business colleagues to truly innovate rather than just do "break/fix". Understanding what business intelligence is and how it can help your business is a great place to start. The world of business intelligence (BI) goes beyond what most think of as just "reporting". It has nuances and complexities that require a combination of skills and people. Fo​​​r example, are you ready to help your company understand the difference between analytical reporting and prescriptive reporting? What about "Big Data" and Data Mining? As a SharePoint Professional, you want to be aware of what is possible.​

1. John White

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4. The Challenge for IT

5. IT Commoditization
 Better understanding breeds greater repeatability
 Greater repeatability requires less skill
 Outsourcing > co-location > VM Hosting > IAAS/PAAS/SAAS
 Cloud Computing

7. Growth in the cloud market is outrunning prior forecasts, according to Forrester
Research Inc. (FORR), which projects a rise from $58 billion last year to $72 billion this
year. The market is on course to be about 20 percent bigger by 2020 than estimated
earlier, Forrester said in a report to be published today.
Cloud computing has reached “hypergrowth” as businesses replace standard licensed
software from companies such as Oracle Corp., SAP AG and Microsoft Corp.
Bloomberg, April 2014

8. "We estimate that for every dollar spent on [Amazon Web Services], there is at least $3
to $4 not spent on traditional IT, and this ratio will likely expand further. In other words,
AWS reaching $10 billion in revenues by 2016 translates into at least $30 to $40 billion
lost from the traditional IT market."
Baird Equity Research Technology, April 2013

9. BI can’t be commoditized
 BI technologies are the tools
 Data is the raw material
 Insight is the product
 Many have tried

10. BI Fundamentals

11. What is BI?
 Reporting?
 Cubes?
 Big Data?
 Data Science
Business intelligence (BI) is the transformation of raw data into meaningful and useful information for
business analysis purposes. ….BI technologies provide historical, current and predictive views of business
operations. Common functions of business intelligence technologies are reporting, online analytical
processing, analytics, data mining, process mining, complex event processing, business performance
management, benchmarking, text mining, predictive analytics and prescriptive analytics.
-Wikipedia

12. A Series of fundamentals
 Useful data extraction
 Temporal Context
 Data description (knowledge extraction)
 Correct tooling

13. Useful data extraction
 In Place reporting
 Real Time vs Real Enough time
 Data Warehousing and ETL
 CRISP - Cross Industry standard for data mining

14. Temporal context
 Past (reporting)
 Present (monitoring)
 Future (predictive analytics)

15. Data description
Automatic data extraction
Structured vs unstructured
Manual metadata input
 Data mashups
Modelling

16. Correct tooling
 Operational/Prescriptive Reporting
 Analytical Reporting
 Dashboarding
 Predictive analytics
 Pattern Matching

17. Getting Started

18. Know the business
 Business knows the data
 You know the technology (and some data)
 Business user data tool of choice – Excel
 IT user tool of choice – SQL Server
 Business gets frustrated, leads to governance violations
 Need to come together for value
 PowerPivot a middle ground

19. Moving ahead
 Gather your data
 Work with familiar tools
 Go for quick wins and build on them
 Excel/PowerPivot is a great place to start
 Keep the goals clear

20. Minimum Viable
Product

22. Think BI

23. Other “BI” data driven systems
 SharePoint search driven content
 Credit card fraud
 Google placed ads
 Cortana

24. Example – Document Relevance
 The Challenge
 Production relevant documents
 The Solution
 Explicit relevance
 Warehouse document metadata with SSIS
 Mashup with SQL Server
 Surface in SharePoint with SSRS

25. Example – Yammer analytics
 Social data is out there
 Social networking has value, but how much?
 Existing tools focus on vanity metrics
 Easy to grab
 False sense of progress
 i.e. 30,000 new signups this month!
 Nothing answered the real burning questions

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