This document discusses the transition from traditional business intelligence (BI) to big data. It notes that BI focuses on structured transactional data and answering questions about the past, while big data leverages both structured and unstructured behavioral data from diverse sources to answer questions about the future. The document outlines technologies like Hadoop, NoSQL databases, and cloud computing that enable organizations to capture and analyze large, dynamic datasets. It also discusses the roles of data scientists and new types of visualizations and devices that support deriving insights from big data.

1. The Road for Enterprise Data
From Traditional BI to Big Data
@LynnLangit
Practioner, Author, Instructor

2. BI = ‘Current State’ Questions
• What did we sell?
Collecting • When did we sell it?
Transactional
data • Where did we sell it?
• What did we sell with it?

3. BTW…Do you use Data Mining?

4. BI Data Landscape
Storage
Processing
Query
Presentation

5. Mix-in #1 -- the Cloud and…
• Host Data in the Cloud
• Process & Query Data in the Cloud
– Click to query and (data) mine
– Return the data locally
– Use Self-service BI visualizers
• Mash-up Cloud data
– Combine with local data

6. NoSQL and the Cloud
• The Elephant in the room…Hadoop
• Over 120+ types of noSQL databases
– http://nosql-database.org/

7. Can’t We All Play Together?

8. Data in the Cloud - Microsoft

9. Windows Azure DataMarket

10. Amazon AWS

11. Google App Engine Data

12. New on Google – MySQL++

13. Comparing RDBMS and MapReduce
Reference: Tom White’s Hadoop: The Definitive Guide
Traditional RDBMS MapReduce
Data Size Gigabytes (Terabytes) Petabytes (Hexabytes)
Access Interactive and Batch Batch
Updates Read / Write many times Write once, Read many times
Structure Static Schema Dynamic Schema
Integrity High (ACID) Low
Scaling Nonlinear Linear
DBA Ratio 1:40 1:3000

14. BTW…NoSQL is 50x CHEAPER

15. BigData = ‘Next State’ Questions
• What could happen?
Collecting • Why didn’t this happen?
• When will the next new thing
behavioral happen?
data • What will the next new thing
be?

16. Splunk

17. Mining Log Files

18. Presenting the results

19. Freebase

20. Mix-in #2 - Data Scientists
• Who asks the ‘right’ questions now?
• Who understands the languages?
• Who can understand the results?

21. Is Data Science your next Career?

22. Becoming a Data Scientist
• Conferences
– Strata
– Data Scientist
Summit
– CloudCamps
• Practice
– here

23. Mix-in #3 - Presentation
• New Devices – iPad, Kindle Fire
• New User Experiences – touch, Kinect
• EVERYTHING on the phone

24. HortonWorks, Cloudera…

25. Karmasphere Studio
for Amazon Elastic MapReduce

26. More PowerPivot

27. Cloud-based Data Mining
Predixion

28. QlikView

29. QlikView on iPad

30. BI >BigData ‘To Do List
Store some (more) data on the cloud
• Relational and non-relational
• Transaction AND Behavioral
Process some data in the cloud
• Try data mining
• Learn about Data Science
Update your client tools
• New UI (touch, gestures)
• Click to Query
• New form factors (phone, tablet)

31. Hadoop Connector to Excel - Demo

32. www.TeachingKidsProgramming.org
• Do a Recipe  Teach a Kid (Ages 10 ++)
• Microsoft SmallBasic  Free Courseware (recipes)

33. Keep up with Big Data
Follow me @LynnLangit
RSS my blog
www.LynnLangit.com
Hire me
• To help build your BI/Big Data solution
• To teach your team next gen BI