The document discusses best practices for big data and business intelligence (BI). It recommends focusing on business objectives, identifying needed data, using the right tools like Hadoop and fast databases, planning mixed architectures, distributing data widely, and tailoring delivery to audiences. It also demonstrates database performance benchmarks and visualization tips. The presentation aims to help organizations effectively use big data to drive value and action.

1. Big Data and BI
Best Practices

2. Your presenters Year
| Last
Yellowfin CEO, Glen Rabie
General Manager, Actian Vectorwise,
Fred Gallagher

3. About Actian and Yellowfin
Making Business Intelligence easy Taking Action on Big Data
History of 100GB TPC-H Performance Benchmarks
Composite Queries Per Hour (Non-Clustered)
500,000.00
400,000.00
QphH@100GB
300,000.00
200,000.00
100,000.00
-
Non-Vectorwise Vectorwise

4. Data is
the new
oil
David McCandles
Data Journalist

5. The rise and rise of Big Data

6. There has always been Big Data…
Its just that now we can actually capture and mine it
effectively.
Canadian Tar Fields

7. Not all Big Data is created Equal
Planet Google and friends are the outliers
Large Telco The Norm
.

8. Do you have a Big Data problem?

9. Big Data for Everyone
• Big data is not just for data scientists and bespoke
projects
• Its for decision makers and data consumers
• It needs to be anchored in the real world
Analyst
Consumers

10. Who is benefitting from Big Data?

11. Who is benefitting from Big Data?

12. Why bother with Big Data?
of organizations collect
60% more data than they can
effectively use
(MIT Sloan Management Review)

13. Why bother with Big Data?
of organizations see
70% Big Data as a big
business opportunity
(Harris Interactive)
of organizations investing
70% in Big Data initiatives
expect ROI within 1 year
(Harris Interactive)

14. Why bother with Big Data?
of organizations that
84% actively leverage Big Data
say they can now make
better decisions
(Avanade)

15. Best Practices in
Big Data
Fred Gallagher, Actian Corporation

16. What is Big Data?

17. Best Practice #1
Focus on what
you want to achieve

18. It’s all about driving value

19. Big Data Levers
1. Personalization
2. Social
3. Search
4. Find opportunities
5. Actionable Insights

20. Best Practice #2
Identify the data you have
vs
The data you need

21. Does your data match what you want
to achieve?

22. What data do you need?

23. Best Practice #3
Use the right Big Data
tool for the job

24. Big Data and Hadoop

25. Big Data Eco-system
Social
Media Analytic
Hadoop
Databases
Storage
BIG
Search DATA NewSQL
“as-a-service”
NoSQL
Document
Operational BigTable
Database Key Value
Graph

26. Best Practice #4
Use a fast database

27. Slow Query Performance is the
#1 issue in BI
BI Survey 10: Why BI Projects Fail?
1. Query Performance Too Slow
TDWI Best Practices Report
“45% Poor Query Response the top problem that will eventually
drive users to replace their current data warehouse platform.”
Gartner Magic Quadrant Data Warehousing
70% of data warehouses experience performance
constrained issues of various types

28. User Expectations
Web-Based
Business Intelligence
Users expect results in
less than 10 seconds
Mobile BI
Users expect results in less
than 3 seconds

29. Use a fast database
Traditional Database Analytical Database Clustered Database

30. Consider the hidden costs
Spend Less on Hardware
Get faster results on smaller
hardware configurations.
Spend Less Time
Database Tuning
Faster deployment and BI
projects. No more aggregates,
cubes, complex schemas, etc

31. Best Practice #5
Plan for a mixed
architecture

32. Hadoop and BI architecture
Hadoop
Transactional
Fast Database BI Tool
External

33. Best Practice #6
Ensure mass distribution of
your data

34. Big Data for Everyone
Visualizations
Alerts
Access Anywhere

35. Best Practice #7
Tailor data delivery to
each audience

36. Give your audience what they want
Demographics Interactive Reports Statistics
KPIs Maps Collaboration

37. Visualization is powerful
Looks like Pac-man Does not look like Pac-man
169 41
Looks like Pac-man
Does not look like
Pac-man

38. Big Data Visualization Tips
• More data requires more focus
• Interactivity is essential
• Select the right metrics
• Provide context
• Support and prompt action

39. Demonstration

40. Big Data and BI Best Practices
1. Focus on what you want to achieve
2. Identify the data you have vs The data you
need
3. Use the right Big Data tool for the job
4. Use a fast database
5. Plan for a mixed architecture
6. Ensure mass distribution of your data
7. Tailor data delivery to each audience

41. Conclusion
Questions

42. | Last Year
More Information
Yellowfin
www.yellowfinbi.com
Vectorwise
www.actian.com/products/vectorwise @YellowfinBI
@ActianCorp
Yellowfin LinkedIn User Group
Vectorwise LinkedIn User Group