1. Business Intelligence Technology and Career Options Paul Boal Director - Data Management Mercy (www.mercy.net)www.mercy.net April 7, 2014

2. Opening Questions  What kinds of jobs does someone do in the area of business intelligence?  What does someone working in business intelligence do?  What are common tools used in business intelligence? 2

3. What do you do in Business Intelligence? 3

4.  Data Governance  Data Architecture, Analysis, and Design  Database Management  Data Security  Data Quality  Master Data Management  Data Warehousing  Reporting  Metadata Management 4 Data analyst Business analyst Data modeler Data architect Report writer BI developer ETL developer Data scientist

5. What do you do in Business Intelligence?  Interview users  Understand business problems  Model the business  Analyze data  Integrate data  Write reports and interfaces  Drive data quality improvement  Build dashboards  Share insights  Make the organization smarter… Solve Business Problems

6. The (sometimes) thankless part…  Data management isn’t important…  First priority is delivering services/products…  Reporting is easy… 6

7. Mercy Data Warehousing / Mercy Insight Here’s how easy it is…

8. COMMON CHALLENGES  Getting access to source data  Working with application teams  Data quality and data stewardship  Master data management  User Expectations  Applying AGILE principles 8

9. Challenge: Getting Access to Data  Vendor Contract Obstacles  Flexibility of vendor to allow access / support  Cost of building extracts  Technical Obstacles  Legacy systems, programming/system skills  Cloud solutions (the bad ones)  Knowledge Gaps  Knowledge of source system data  Cultural Obstacles  Application team controls access too tightly  Development teams are timid about database access 9

10. Challenge: Application Teams  Development Style  You tell me exactly what you want and I'll build it.  Give me the business logic and I'll build it.  Analytical Hubris  This is the way it works; come to find out the data doesn't match.  I assumed that you wanted it like that other extract.  Fear of a down-stream dependency  e.g.  Kronos PR530  The PICA code 10

11. Challenge: Data Quality & Master Data Management  Not analyzing or profiling data contents  Using terms rather than ideas  Building in rules that are too strict  Missing formal data governance policies  Lack of clear data stewardship  Data seen only as operational 11 http://ocdqblog.com

12. Challenge: User Expectations  Sometimes, users expect computers to be able to solve problems for them;  Sometimes, users don't want the system to do anything for them.  Rationalize data integration / data warehousing  80% gathering information together  20% analyzing and decision making  Web 2.0 versus Enterprise Applications  Enterprise solutions versus departmental control  System Performance 12

13. Being the Expert 12

14. Challenges in Getting Value from Data  Data Usage Survey  195 data users across Mercy (of 380 surveyed) analysts, informaticists, statisticians, report writers  Top Challenges  Finding the data they need  Performance of the systems they use to access data  Integrity of the data they have access to  Integrating data from multiple sources  Target  80% using data and %20 getting data 1  Current Efficiency Gap 13

15. Challenge Applying AGILE Agile Manifesto Individuals and interactions over processes and tools Working software over comprehensive documentation Customer collaboration over contract negotiation Responding to change over following a plan Works great for interactive web apps Challenging for data-centric / analytics 15

16. STAYING FIT  Organizations / Conferences  TDWI TDWI  B-Eye-Network B-Eye-Network  TDAN TDAN  DAMA DAMA  Analysts: Gartner, ForresterGartner  MeetUp (Data Science, Hadoop, R, Open Data)Data ScienceHadoopROpen Data  Blogs  I'll email you my Google Reader list: paul.boal@gmail.compaul.boal@gmail.com  Twitter  BI Twitter List BI Twitter List  Open Source and Developer Tools  Talend, Pentaho, Jaspersoft, BIRT, Infobright  Oracle, Teradata, IBM 14

17. Demonstrations 15

18. Business Objects Universe 16

19. Business Objects WebI 17

20. Dashboards 17

21. Data Exploration 17

22. Tools / Resources  Open Source BI  Pentaho – reporting, analytics, integration, dashboards, mining Pentaho  Talend – integration, data quality, master data Talend  Jaspersoft – reporting, analytics, integration, dashboards Jaspersoft  Actuate BIRT – reporting Actuate BIRT  Open Source Stats/Mining  R – statistics R  Weka – machine learning Weka  ProM – process mining ProM  Databases  MySQL, Oracle, Teradata, SQL Server, Infobright, Hadoop  Teradata University Network Teradata University Network  Internships 19