Impetus webcast ‘Real-time Streaming Analytics: Business Value, Use Cases and Architectural Considerations’ available at http://bit.ly/1i6OrwR The webinar talks about- • How business value is preserved and enhanced using Real-time Streaming Analytics with numerous use-cases in different industry verticals • Technical considerations for IT leaders and implementation teams looking to integrate Real-time Streaming Analytics into enterprise architecture roadmap • Recommendations for making Real-time Streaming Analytics – real – in your enterprise • Impetus StreamAnalytix – an enterprise ready platform for Real-time Streaming Analytics

1. Real-time Streaming
Analytics
Business Value, Use Cases and
Architectural Considerations
Big Data Solutions and Services Partner for Enterprises
Anand Venugopal – Sr. Director Business Development
Big Data Solutions
1
Yue Cathy Chang – Sr. Director Business Development
Alliances and Partnerships

2. Picture your house
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3. What if this was happening now
to your home ?
3 Recorded version available at http://bit.ly/1i6OrwR

4. When do you want to know ?
4
Later
or
Now ?
Recorded version available at http://bit.ly/1i6OrwR

5. Your best buddy from school
You haven’t met in years
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Recorded version available at http://bit.ly/1i6OrwR

6. Is in Vegas same time as you
Your
buddy
Your
buddy
YouYou
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Recorded version available at http://bit.ly/1i6OrwR

7. When do you want to know ?
After you return
or
NOW ?
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Recorded version available at http://bit.ly/1i6OrwR

8. • Whether individual or Business
• Important things are always happening NOW
• NOW is the ONLY time life REALLY happens
• Maximize data value  process and act sooner!
Life is happening NOW
Real-time insight preserves or
creates value
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9. Topics we will cover today
Why ?
Business Value
What ?
Is Real-time Streaming Analytics and what it is not
How?
Architectural considerations
Use cases
Who and
Where ?
What next ?
Recommendations
9
Recorded version available at http://bit.ly/1i6OrwR

10. What it is NOT
• Quick-response interactive analytics on static data
• Batch processing
• Could be close but still NOT – Micro Batch processing
What is Real-time Streaming
Analytics ?
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Recorded version available at http://bit.ly/1i6OrwR

11. • Data analyzed in motion – as it arrives
• Routine: Monitoring, Counting, Alerting, Reporting
• Complex Decision Making with Predictive analytics
• Every incoming event is distinctly processible
• Receive, Inspect, Analyse, Store, Distribute
• Events may be stored later or in parallel
• Immediate actions possible after processing
What is Real-time Streaming
Analytics ?
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Recorded version available at http://bit.ly/1i6OrwR

12. Real time vs. Batch analytics
Sec
/
ms
Sec
/
ms
Sec
/
ms
Sec
/
ms
BATCHBATCH
Real timeReal time
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Recorded version available at http://bit.ly/1i6OrwR

13. 13

14. Topics we will cover today
Why ?
Business Value
What ?
Is Real-time Streaming Analytics and what it is not
How?
Architectural considerations
Use cases
Who and
Where ?
What next ?
Recommendations
14
Recorded version available at http://bit.ly/1i6OrwR

15. Business Value
Diminishes with the age of data
The drop is non-linear
$$$ ?
Before
• Predictive analytics based on current
events
• Value depends on accuracy
$$
NOW
• Real-time
• Certainty is high – REAL
• Value based on quick
response
$$$
Later
• Descriptiv
e
• Diagnostic
• Least
value
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Value
of
Data
Age of
Data

16. • Routine business operations (Real time systems)
• Cutting preventable losses
• Finding and monetizing missed opportunities
• More revenue
• Cost savings
• Creating new opportunities
• New Business models (Products, Services, Revenue)
Business Value from RTSA
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Recorded version available at http://bit.ly/1i6OrwR

17. Topics we will cover today
Why ?
Business Value
What ?
Is Real-time Streaming Analytics and what it is not
How?
Architectural considerations
Use cases
Who and
Where ?
What next ?
Recommendations
17
Recorded version available at http://bit.ly/1i6OrwR

18. Routine Operations
(RT systems)
• Manufacturing – Control Systems (Closed loop)
• IT - Systems & Network Monitoring
• Field Assets Monitoring and Alerting
• Trucks, Oil rigs, Vending machines, Radio towers
• Financial Transactions Processing
• Authentications, Validations, Fraud
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Recorded version available at http://bit.ly/1i6OrwR

19. Cutting Preventable Losses
• MH 370 – Loss of lives and assets
• GM – Manufacturing defects
• Target – Major Security breach
• Stock Exchange Meltdown
Many headline stories are failures in
routine operations and were preventable losses
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Recorded version available at http://bit.ly/1i6OrwR

20. Cutting Preventable Losses (2)
• Medical / Clinical – Complex analytics in ICU
• Disaster Warning Systems: Chile / Sandy
• Brokerage - Fraudulent or Risky Trades
• Preventive Maintenance – Machines, Plants
• Customer Churn
• Brand Reputation on Social Media
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Recorded version available at http://bit.ly/1i6OrwR

21. Missed Opportunities - Revenue
• Customer Service always happens in real-time
• Listening and Learning from customers (Social)
• Context sensitive inventory – Products, Ads
• Recommend - Upsell – Cross-sell
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Recorded version available at http://bit.ly/1i6OrwR

22. Missed Opportunities - Efficiency
• Operational Efficiency of systems or processes
• Network Optimization for cost, quality of service
• Dynamic capacity management
• Dynamic re-routing of traffic, cargo
• Insurance Adjudication – Drone image analysis
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Recorded version available at http://bit.ly/1i6OrwR

23. New Opportunities
• Tractors are becoming soil sensors
• Information service to farmers
• Nike – becoming a healthcare company ??
• Quantified self movement
• Telecom giants selling data and insights
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Recorded version available at http://bit.ly/1i6OrwR

24. Business Value of RTSA Summary
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Recorded version available at http://bit.ly/1i6OrwR

25. Topics we will cover today
Why ?
Business Value
What ?
Is Real-time Streaming Analytics and what it is not
How ?
Architectural considerations
Use cases
Who and
Where ?
What next ?
Recommendations
25
Recorded version available at http://bit.ly/1i6OrwR

26. Architectural Considerations
(1/3)
ALWAYS
ACCURATELY
APPROPRIATELY
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Recorded version available at http://bit.ly/1i6OrwR

27. Real time + Batch Analytics
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Recorded version available at http://bit.ly/1i6OrwR

28. Real time + Batch Analytics
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Recorded version available at http://bit.ly/1i6OrwR

29. Real time + Batch Analytics
29
Recorded version available at http://bit.ly/1i6OrwR

30. Real time + Batch Analytics
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Recorded version available at http://bit.ly/1i6OrwR

31. Real time + Batch Analytics
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Recorded version available at http://bit.ly/1i6OrwR

32. Real-time streaming
analytics pipeline and flow
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Recorded version available at http://bit.ly/1i6OrwR

33. Real-time streaming
analytics pipeline and flow
Scale and Robustness
Reliability - Guarantees
Publish-Subscribe
Flexibility – Dynamic
Integration with Batch
Loose Coupling
Visualization
Ease of Administration
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Recorded version available at http://bit.ly/1i6OrwR

34. StreamAnalytix
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Recorded version available at http://bit.ly/1i6OrwR

35. •Proprietary platforms
• Vendor lock-in
• No leverage of open source movement
•Do it yourself
• Open source stitch up
• Integration and maintenance nightmare
• Significant delays in time-to-market
Approaches to Stream Analytics
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Recorded version available at http://bit.ly/1i6OrwR

36. • An “App Server” for real-time apps
• Based on best-of-breed Open source
• Focus on your Business logic leave infrastructure to the platform
• Handle all the 3V’s of Big Data in one platform
• Seamless integration with Hadoop, NoSQL or any other DB
• Rapidly operationalize pre-built analytical models or new ones
• Significant time to market acceleration
• Impetus provides full product support and professional services
Introducing ‘StreamAnalytix’
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Recorded version available at http://bit.ly/1i6OrwR

37. Topics we will cover today
Why ?
Business Value
What ?
Is Real time streaming anaytics and what it is not
How?
Architectural considerations
Use cases
Who and
Where ?
What next ?
Recommendations
37
Recorded version available at http://bit.ly/1i6OrwR

38. • Important things are always happening NOW
• Maximize data value  process and act sooner!
• There is value – find it  Improve Ops, Cut losses, Find missed &
new opportunities
• Architecture: Sense  Analyse  Act  Sense
RECAP
38
Real time insight preserves and
creates business value
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39. • Get Real time streaming analytics in your roadmap
• Talk to experienced peers and consultants
• Start now with opportunities search, solution architecture and
vendor conversations
• Instrument (SENSE) everything – find gaps and fill
• Prove value with “faster batch” with current infra is possible
• Establish mechanisms to ACT on the insights
• Close the loop – Sense and Analyse effectiveness
• DO IT
RECOMMENDATIONS
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Recorded version available at http://bit.ly/1i6OrwR

40. Topics we will cover today
Why ?
Business Value
What ?
Is Real time streaming anaytics and what it is not
How?
Architectural considerations
Use cases
Who and
Where ?
What next ?
Recommendations
40

41. Big Data Solutions and Services partner for Enterprises
Request a demo of StreamAnalytix
bigdata@impetus.com
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Recorded version available at http://bit.ly/1i6OrwR
@impetustech