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James Serra, Microsoft
PDW Technology Solution Professional
JamesSerra3@gmail.com
JamesSerra.com
 Business Intelligence Consultant, in IT for 28 years
 Owner of Serra Consulting Services, specializing in end-to-end Business
Intelligence and Data Warehouse solutions using the Microsoft BI stack
 Worked as desktop/web/database developer, DBA, BI and DW architect
and developer, MDM architect, PDW developer
 Been perm, contractor, consultant, business owner
 Presenter at PASS Business Analytics Conference and PASS Summit
 MCSE for SQL Server 2012: Data Platform and BI
 SME for SQL Server 2012 certs
 Contributing writer for SQL Server Pro magazine
 Blog at JamesSerra.com
 SQL Server MVP
 Author of book “Reporting with Microsoft SQL Server 2012”
Agenda
 Why BI?
 Why is BI so difficult?
 How BI Projects Get Started
 How BI Projects Fail
 How BI Project Succeed
 Key Takeaways
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James Serra, Microsoft
PDW Technology Solution Professional
Email me at: JamesSerra3@gmail.com
Follow me at: @JamesSerra
Link to me at: www.linkedin.com/in/JamesSerra
Visit my blog at: JamesSerra.com
• http://bit.ly/15BM9lR
• http://bit.ly/10rN9GD
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http://bit.ly/15BMjKa
• http://bit.ly/xl4mGM
•
http://bit.ly/16y84M3
• http://slidesha.re/16y8SR6
• http://slidesha.re/16y8VMw
• http://slidesha.re/16y94j6

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Best Practices to Deliver BI Solutions

Notes de l'éditeur

  1. If your company is planning to build a data warehouse or BI solution, you need to be aware that BI projects have high failure rates. Gartner says between 70% to 80% of corporate business intelligence projects fail. And with “big data” adding more complexity you can expect even more failures. However, the major causes of these failures are well known and can be avoided by implementing a set of best practices.I have worked on dozens of end-to-end BI projects and have seen my share of successes and failures. I will talk about the reasons BI projects fail and share best practices and lessons learned so your BI project will fall into the “successful” category.
  2. This is a topic that I have been looking forward to talking about. It’s the first time I have presented it, but it allows me to use all the experience I have gathered over the years and share it.I have done dozens of BI/DW projects and have seen what works and what does not work.
  3. Starting with an end date and working backwards– rushing thru design, architecture, technical requirements, data cleanup
  4. Not setting up time to “validate the numbers”– if the first time they see data and the numbers are wrong, you will have a hard time winning them back
  5. Don’t just recreate the existing reports, but add value – solve a business problem