1. Business Intelligence
3/28/2013

3. How Large is a Petabyte?
= 4 x

4. What is “Big Data”
• Volume
– Transactions
– Social Media
– Mobile Phone
– Web Traffic

5. What is “Big Data”
• Volume
• Variety
– SQL Databases
– TXT Log Files
– Graph Databases
• Velocity

6. What is “Big Data”
• Volume
• Variety
• Velocity
– Rate of Collection
– Need for Agility

7. Primary BI Systems
1. Reporting systems
2. Data-mining systems
3. Knowledge
Management
Systems
4. Expert Systems

8. Reporting Systems
• Integrate data from
multiple systems.
• Calculate and
summarize data.
• Sorting, grouping,
summing, averaging,
comparing
• Present data as
meaningful information.

9. Reporting Systems
• Sybase Infomaker
• Crystal Reports
• Microsoft SQL Reporting
Services

10. Data Mining Systems
• Use sophisticated
statistical techniques,
regression analysis,
and decision tree
analysis.
• Discovers hidden
patterns and
relationships.
• Can be used as the
basis for predictions.

11. Data Mining Systems
• MS Business
Intelligence
Development Studio
• SAS Enterprise
Miner
• WEKA

12. Knowledge Management
Systems
• Collect and share
human knowledge.
• Best practices
• Employee training
• Process
documentation
• Collaboration &
Communication

13. Knowledge Management
Systems
• Sharepoint Server
• Kwiki, TikiWiki,
Twiki, Zwiki
• Google Docs
• Google Sites
• Evernote

14. Expert Systems
• Uses rules and logic
(i.e. IF > THEN)
• Automates and
standardizes
decision making.
• Examples: Medical,
HR, Finance,
Stocks, Games
• IFTTT

15. BI Comparison Table

16. Business Intelligence Problems
• Raw data usually unsuitable for
sophisticated reporting or data
mining
• Dirty data (misspelled, wrong type,
missing, duplication, inconsistent)
• Multi-dimensionality
• Wrong granularity (summary vs.
detail)

17. Data Warehousing
• Extract and clean data from
various operational systems
and other sources
• Store and catalog data for BI
processing
• Extract, clean, prepare data
• Stored in data-warehouse
DBMS

18. Data Warehousing

19. Data Mart
• Created to address particular needs
• Smaller than data warehouse
• Users may not have data management
expertise
• Data extracted from data warehouse for a
functional area

20. BI & MRV
MRV could:
• Develop a plan to organize storage of data and how
management might use it;
• Use a reporting system to provide information about
how much repeat business each guide generates;
• Identify high value customers and customer referrals;
• Analyze equipment inventory usage to guide future
equipment purchases.