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Grab some
coffee and
enjoy the
pre-­show
banter
before the
top of the
hour!
The Briefing Room
Ahead of the Stream: How to Future-Proof Real-Time Analytics
Twitter Tag: #briefr The Briefing Room
Welcome
Host:
Eric Kavanagh
eric.kavanagh@bloorgroup.com
@eric_kavanagh
Twitter Tag: #briefr The Briefing Room
  Reveal the essential characteristics of enterprise
software, good and bad
  Provi...
Twitter Tag: #briefr The Briefing Room
Topics
August: REAL-TIME DATA
September: HADOOP 2.0
October: DATA MANAGEMENT
Twitter Tag: #briefr The Briefing Room
The Value of Future-Proofing
Ø  Storm is hot
Ø  Spark is hotter
Ø  More innovati...
Twitter Tag: #briefr The Briefing Room
Analyst: Robin Bloor
Robin Bloor is
Chief Analyst at
The Bloor Group
robin.bloor@bl...
Twitter Tag: #briefr The Briefing Room
Impetus
  Founded in 1991, Impetus offers a variety of products
and services across...
Twitter Tag: #briefr The Briefing Room
Guest: Anand Venugopal
Anand Venugopal
Product Head - StreamAnalytix, Impetus Techn...
© 2015 Impetus Technologies - Confidential10
Webinar: Future-Proof Your Streaming Analytics Architecture
Robin Bloor,
Prin...
© 2015 Impetus Technologies - Confidential11
IMPETUS INTRODUCTION
Mission critical
technology
solutions since
1996
Global ...
© 2015 Impetus Technologies - Confidential12
REAL-TIME STREAMING ANALYTICS PLATFORM
Why ?
Build vs.
Buy ?
What to
buy ?
Fr...
© 2015 Impetus Technologies - Confidential13
TOPICS COVERED TODAY
Business need
for streaming
analytics
Industry
verticals...
© 2015 Impetus Technologies - Confidential14
WHY STREAMING ANALYTICS ?
Because it is now
possible! Batch
only is old
Custo...
© 2015 Impetus Technologies - Confidential15
WHY ? à BATCH VS. REAL-TIME BUSINESS PROCESS
SENSE Days ANALYSE Weeks ACT
SE...
© 2015 Impetus Technologies - Confidential16
WHY ? à CONTEXT AWARE: POSITIVE CUSTOMER EXPERIENCE
Multi-channel
engagement...
© 2015 Impetus Technologies - Confidential17
TYPICAL USE CASES FOR STREAMING ANALYTICS
•  Predictive Maintenance
•  Clinic...
© 2015 Impetus Technologies - Confidential18
BUILD Vs BUY ?
•  Needs time, skills,
budget
•  Upfront costs and long
term m...
© 2015 Impetus Technologies - Confidential19
Architecture Considerations
© 2015 Impetus Technologies - Confidential20
t
now
Hadoop works great back here RT-Ax works
here
BLENDED VIEW – HISTORICAL...
© 2015 Impetus Technologies - Confidential21
LAMBDA ARCHITECTURE : BIG AND FAST DATA COMBINED
Batch Layer
All data
Pre-com...
© 2015 Impetus Technologies - Confidential22
AN INTEGRATED APPROACH BLENDING CURRENT AND NEXT
GENERATION TECH
Landing and
...
© 2015 Impetus Technologies - Confidential23
Streaming Platform Options
and StreamAnalytix approach
© 2015 Impetus Technologies - Confidential24
“DEFAULT” APPROACHES TO STREAMING ANALYTICS
•  No leverage of open source
•  ...
© 2015 Impetus Technologies - Confidential25
THE 3RD APPROACH: BEST OF BOTH WORLDS
StreamAnalytix mitigates the
disadvanta...
© 2015 Impetus Technologies - Confidential26
StreamAnalytix – GIVES YOU A FUTURE PROOF OPTION
STORM SPARK OTHERS
NOW
Time
© 2015 Impetus Technologies - Confidential27
Future proof – Enterprise Grade – Open source based – Streaming Analytics pla...
© 2015 Impetus Technologies - Confidential28
StreamAnalytix Screenshots
© 2015 Impetus Technologies - Confidential29
CONFIGURABLE MESSAGE DEFINITION
© 2015 Impetus Technologies - Confidential30
CONFIGURATION FIELD DEFINITION
© 2015 Impetus Technologies - Confidential31
CONFIGURABLE ALERT DEFINITION
© 2015 Impetus Technologies - Confidential32
SAMPLE DATA PIPELINE (USING DATAFABRIC )
Supported	
  Ingest	
  Channels	
  
© 2015 Impetus Technologies - Confidential33
SAMPLE DATA PIPELINE (USING DATAFABRIC )
Supported	
  Processors	
  
© 2015 Impetus Technologies - Confidential34
SAMPLE DATA PIPELINE (USING DATAFABRIC )
Supported	
  Emi8ers/	
  
Output	
  ...
© 2015 Impetus Technologies - Confidential35
CUSTOM CODE DEVELOPMENT/INTEGRATION
Download	
  
Sample	
  
Project	
  
Custo...
© 2015 Impetus Technologies - Confidential36
UPLOADING WORKFLOW
Configurable	
  Workflow	
  Upload	
  
(Ac3vi3	
  BPM	
  sup...
© 2015 Impetus Technologies - Confidential37
MONITORING A PIPELINE
© 2015 Impetus Technologies - Confidential38
DASHBOARD (SAMPLE)
© 2015 Impetus Technologies - Confidential39
USER MANAGEMENT
© 2015 Impetus Technologies - Confidential40
FROM WHOM TO BUY ? IMPETUS
?	
  
Right	
  size	
   Independent	
   Services	
...
© 2015 Impetus Technologies - Confidential41
Call Center Solution
© 2015 Impetus Technologies - Confidential42
HOSTED CALL CENTER SOLUTION
•  Call “Stitching” in real-time
•  IVR dominant ...
© 2015 Impetus Technologies - Confidential43
© 2015 Impetus Technologies - Confidential44
© 2015 Impetus Technologies - Confidential45
© 2015 Impetus Technologies - Confidential46
ACCESS FREE VERSION OF STREAMANALYTIX
StreamAnalytix Lite
A production-ready ...
© 2015 Impetus Technologies - Confidential47
Log Monitoring App
© 2015 Impetus Technologies - Confidential48
LOG-MONITORING DASHBOARD
© 2015 Impetus Technologies - Confidential49
LOG-MONITORING DASHBOARD
© 2015 Impetus Technologies - Confidential50
SYSTEM MONITORING(CPU,MEM,DISK)
© 2015 Impetus Technologies - Confidential51
SEARCH
© 2015 Impetus Technologies - Confidential52
Real Time Social Media Analytics
© 2015 Impetus Technologies - Confidential53
CREATING NEW SEARCH FROM DATA SOURCE
© 2015 Impetus Technologies - Confidential54
REAL-TIME SENTIMENTS AND CLASSIFICATION
© 2015 Impetus Technologies - Confidential55
REAL-TIME TOPIC CATEGORIZATION
© 2015 Impetus Technologies - Confidential56
Thank you.
Questions??
inquiry@streamanalytix.com
www.StreamAnalytix.com
Cont...
Twitter Tag: #briefr The Briefing Room
Perceptions & Questions
Analyst:
Robin Bloor
Of Lakes and Streams
Robin Bloor, PhD
The Division
Analytics and streaming analytics
are not at all the same
The Biological Analog
u  Our human control system works at
different speeds:
•  Internal systems – enteric nervous system...
A While Ago…
The Hadoop Disruption
Then Spark Disrupts Hadoop
u  Spark has become the de facto vehicle for
many distinct Hadoop projects because of its
in-m...
Spark and Storm
u  Along with Spark comes with Shark (a Hive-
compatible version of Spark)
u  Storm provides batch and s...
My Current View
Streaming is more about DATA/
SOFTWARE ARCHITECTURE than
anything else
u  There’s clearly a trend to low latency
analytics. How do you see this developing?
u  Aside from predictive analytics ...
u  What is your current largest customer in terms of
streaming volume, and what is the application?
u  Do you find yours...
Twitter Tag: #briefr The Briefing Room
Twitter Tag: #briefr The Briefing Room
Upcoming Topics
www.insideanalysis.com
August: REAL-TIME DATA
September: HADOOP 2.0...
Twitter Tag: #briefr The Briefing Room
THANK YOU
for your
ATTENTION!
Some images provided courtesy of Wikimedia Commons
an...
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Ahead of the Stream: How to Future-Proof Real-Time Analytics

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Business seems to move faster by the day, with the most cutting edge companies taking advantage of real-time data streams for heavy duty analytics. But with so much innovation happening in so many places, how can companies stay ahead of the game? One answer is to future-proof your analytics architecture by using an abstraction layer that can translate your business use-case or work-flow to one of many leading innovative technologies to address the growing number of use cases in this dynamic field.

Register for this episode of The Briefing Room to hear veteran Analyst Dr. Robin Bloor, as he explains how a data flow architecture can harness a wide range of streaming solutions. He'll be briefed by Anand Venugopal of Impetus Technologies, who will showcase his company's StreamAnalytix platform, which was designed from the ground up to leverage multiple major streaming engines available today, including Apache Spark, Apache Storm and others. He'll demonstrate how StreamAnalytix provides enterprise-class performance while incorporating best-of-breed open-source components.

View the archive at: https://bloorgroup.webex.com/bloorgroup/lsr.php?RCID=925d1e9b639b78c6cf76a1bbbf485b2b

Published in: Technology
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Ahead of the Stream: How to Future-Proof Real-Time Analytics

  1. 1. Grab some coffee and enjoy the pre-­show banter before the top of the hour!
  2. 2. The Briefing Room Ahead of the Stream: How to Future-Proof Real-Time Analytics
  3. 3. Twitter Tag: #briefr The Briefing Room Welcome Host: Eric Kavanagh eric.kavanagh@bloorgroup.com @eric_kavanagh
  4. 4. Twitter Tag: #briefr The Briefing Room   Reveal the essential characteristics of enterprise software, good and bad   Provide a forum for detailed analysis of today s innovative technologies   Give vendors a chance to explain their product to savvy analysts   Allow audience members to pose serious questions... and get answers! Mission
  5. 5. Twitter Tag: #briefr The Briefing Room Topics August: REAL-TIME DATA September: HADOOP 2.0 October: DATA MANAGEMENT
  6. 6. Twitter Tag: #briefr The Briefing Room The Value of Future-Proofing Ø  Storm is hot Ø  Spark is hotter Ø  More innovation coming Ø  But keep in mind the latency
  7. 7. Twitter Tag: #briefr The Briefing Room Analyst: Robin Bloor Robin Bloor is Chief Analyst at The Bloor Group robin.bloor@bloorgroup.com @robinbloor
  8. 8. Twitter Tag: #briefr The Briefing Room Impetus   Founded in 1991, Impetus offers a variety of products and services across the big data ecosystem StreamAnalytix is its open source real-time streaming capability for big data analytics   The platform leverages multiple Apache components, including YARN, Spark, Storm and Kafka
  9. 9. Twitter Tag: #briefr The Briefing Room Guest: Anand Venugopal Anand Venugopal Product Head - StreamAnalytix, Impetus Technologies Anand Venugopal has been working with Fortune 1000 enterprises to deliver real business benefits and ROI from Big Data Solutions at Impetus. He has been helping IT and line-of-business executives in large enterprises understand and extract the enormous value embedded in their static and "in-motion" Big-Data assets. Before Impetus, since 1995 – Anand has been in techno-business evangelism roles in various industries including telecom, gaming, media and entertainment and hi-tech.
  10. 10. © 2015 Impetus Technologies - Confidential10 Webinar: Future-Proof Your Streaming Analytics Architecture Robin Bloor, Principal Analyst Aug 25, 2015 Twitter: @ Anand Venugopal, Product  Head  -­‐  StreamAnaly3x      Twi8er:  @streamanaly3x
  11. 11. © 2015 Impetus Technologies - Confidential11 IMPETUS INTRODUCTION Mission critical technology solutions since 1996 Global Leaders are our Big Data clients 1600 people – US, India, Global reach Unique mix of Big Data products and Services
  12. 12. © 2015 Impetus Technologies - Confidential12 REAL-TIME STREAMING ANALYTICS PLATFORM Why ? Build vs. Buy ? What to buy ? From whom to buy ? How to Integrate ?
  13. 13. © 2015 Impetus Technologies - Confidential13 TOPICS COVERED TODAY Business need for streaming analytics Industry verticals and use cases Architecture Streaming platform options StreamAnalytix approach and benefits Some announcements!
  14. 14. © 2015 Impetus Technologies - Confidential14 WHY STREAMING ANALYTICS ? Because it is now possible! Batch only is old Customer Experience Operational Intelligence
  15. 15. © 2015 Impetus Technologies - Confidential15 WHY ? à BATCH VS. REAL-TIME BUSINESS PROCESS SENSE Days ANALYSE Weeks ACT SENSE ANALYSE ACT Sec/ ms Batch Real time Sec/ ms
  16. 16. © 2015 Impetus Technologies - Confidential16 WHY ? à CONTEXT AWARE: POSITIVE CUSTOMER EXPERIENCE Multi-channel engagement in real-time Context Sensitive service Happy customers, Loyalty, Revenue, Profits, Growth
  17. 17. © 2015 Impetus Technologies - Confidential17 TYPICAL USE CASES FOR STREAMING ANALYTICS •  Predictive Maintenance •  Clinical care and patient management •  Sensor analytics •  Fleet operations •  Fraud and anomaly detection •  Gaming •  Churn Analytics •  Network traffic analysis and optimization •  Internet Advertising Verticals •  Customer experience •  Clickstream Analytics •  Context-sensitive offers and recommendations •  IT Log analytics •  Security Horizontals •  Internet of Things •  Mobile app analytics •  Call Center Monitoring and Analytics Combo
  18. 18. © 2015 Impetus Technologies - Confidential18 BUILD Vs BUY ? •  Needs time, skills, budget •  Upfront costs and long term maintenance costs •  Total flexibility and control •  Do you have the time to wait ? Build Vs   Buy •  Are ready options available that meet your needs ? •  Selection Criteria ? (Show Thumbnail of Ten considerations white paper)
  19. 19. © 2015 Impetus Technologies - Confidential19 Architecture Considerations
  20. 20. © 2015 Impetus Technologies - Confidential20 t now Hadoop works great back here RT-Ax works here BLENDED VIEW – HISTORICAL AND NOW Blended viewBlended viewBlended View
  21. 21. © 2015 Impetus Technologies - Confidential21 LAMBDA ARCHITECTURE : BIG AND FAST DATA COMBINED Batch Layer All data Pre-computed information Batch re-compute Speed Layer All data Pre-computed information Real time increment Batch view Serving Layer Batch view Merge Real time view Real time view All Incoming Data Query
  22. 22. © 2015 Impetus Technologies - Confidential22 AN INTEGRATED APPROACH BLENDING CURRENT AND NEXT GENERATION TECH Landing and ingestion Structured Unstructured External Social Machine Geospatial Time Series Streaming Provisioning, Workflow, Monitoring and Security Enterprise Data Lake Predictive applications Exploration & discovery Enterprise applications Real-Time applications Traditional data repositories RDBMS   MPP   Compliance, Governance, Information Lifecycle, Data Lineage, Enterprise Meta Data Management
  23. 23. © 2015 Impetus Technologies - Confidential23 Streaming Platform Options and StreamAnalytix approach
  24. 24. © 2015 Impetus Technologies - Confidential24 “DEFAULT” APPROACHES TO STREAMING ANALYTICS •  No leverage of open source •  Vendor lock-in •  Could be high cost •  Limited flexibility Proprietary Platforms •  Native Open source •  No Vendor Support •  Integration & maintenance nightmare •  Significant delays in time-to-market “Do it yourself”
  25. 25. © 2015 Impetus Technologies - Confidential25 THE 3RD APPROACH: BEST OF BOTH WORLDS StreamAnalytix mitigates the disadvantages of the "default" approaches and offers the benefits of both worlds to enterprises for streaming analytics. Abstraction of functional components like Ingest, CEP, Analytics, Visualization
  26. 26. © 2015 Impetus Technologies - Confidential26 StreamAnalytix – GIVES YOU A FUTURE PROOF OPTION STORM SPARK OTHERS NOW Time
  27. 27. © 2015 Impetus Technologies - Confidential27 Future proof – Enterprise Grade – Open source based – Streaming Analytics platform NEXT Unified Business Interfaces Common Utilities Smart Workflows
  28. 28. © 2015 Impetus Technologies - Confidential28 StreamAnalytix Screenshots
  29. 29. © 2015 Impetus Technologies - Confidential29 CONFIGURABLE MESSAGE DEFINITION
  30. 30. © 2015 Impetus Technologies - Confidential30 CONFIGURATION FIELD DEFINITION
  31. 31. © 2015 Impetus Technologies - Confidential31 CONFIGURABLE ALERT DEFINITION
  32. 32. © 2015 Impetus Technologies - Confidential32 SAMPLE DATA PIPELINE (USING DATAFABRIC ) Supported  Ingest  Channels  
  33. 33. © 2015 Impetus Technologies - Confidential33 SAMPLE DATA PIPELINE (USING DATAFABRIC ) Supported  Processors  
  34. 34. © 2015 Impetus Technologies - Confidential34 SAMPLE DATA PIPELINE (USING DATAFABRIC ) Supported  Emi8ers/   Output  Channels  
  35. 35. © 2015 Impetus Technologies - Confidential35 CUSTOM CODE DEVELOPMENT/INTEGRATION Download   Sample   Project   Custom  Java  Component   Development       Reuse  Exis3ng  Storm  Bolt  Code  
  36. 36. © 2015 Impetus Technologies - Confidential36 UPLOADING WORKFLOW Configurable  Workflow  Upload   (Ac3vi3  BPM  support  )  
  37. 37. © 2015 Impetus Technologies - Confidential37 MONITORING A PIPELINE
  38. 38. © 2015 Impetus Technologies - Confidential38 DASHBOARD (SAMPLE)
  39. 39. © 2015 Impetus Technologies - Confidential39 USER MANAGEMENT
  40. 40. © 2015 Impetus Technologies - Confidential40 FROM WHOM TO BUY ? IMPETUS ?   Right  size   Independent   Services   Track  record   of  Long  term   partnerships   and  value   Recent   success  stories  
  41. 41. © 2015 Impetus Technologies - Confidential41 Call Center Solution
  42. 42. © 2015 Impetus Technologies - Confidential42 HOSTED CALL CENTER SOLUTION •  Call “Stitching” in real-time •  IVR dominant path analytics •  Analyze behaviour of Call Centre infrastructure •  Business driven SLA based alerts in real-time •  Historical reports for future pricing models •  Trace complete call flow •  Advanced Search on Call facets •  Sentiments and alerts on email/chat conversations •  Individual events scattered in different media servers. •  Change the SLA alert definition and apply new definition in real-time without restart. •  Sequence of events to be maintained at processing, storage and query level. •  Media server logs contains only 1% of data which is relevant. Platform should have capability to filter the data at source level. Key Features Challenges Solved
  43. 43. © 2015 Impetus Technologies - Confidential43
  44. 44. © 2015 Impetus Technologies - Confidential44
  45. 45. © 2015 Impetus Technologies - Confidential45
  46. 46. © 2015 Impetus Technologies - Confidential46 ACCESS FREE VERSION OF STREAMANALYTIX StreamAnalytix Lite A production-ready version of StreamAnalytix for Developers to use a powerful visual tool-kit for developing real-time streaming analytics applications free of cost.  •  Limited Functionality •  Unlimited Scale •  Free for ever StreamAnalytix Developer Fully functional version of 'StreamAnalytix Enterprise' for Developers to quickly try out all the platform features by putting all their data at work to uncover new insights.   •  Full Functionality •  Restriction on scale •  Free for 1 year Enterprise Trial Fully loaded version of StreamAnalytix with a rich set of advanced visualization tools to easily develop & analyze real-life enterprise applications with minimal coding.  •  Full Functionality •  Unlimited Scalability •  60 days trial For more details visit at http://streamanalytix.com/download Platform Editions
  47. 47. © 2015 Impetus Technologies - Confidential47 Log Monitoring App
  48. 48. © 2015 Impetus Technologies - Confidential48 LOG-MONITORING DASHBOARD
  49. 49. © 2015 Impetus Technologies - Confidential49 LOG-MONITORING DASHBOARD
  50. 50. © 2015 Impetus Technologies - Confidential50 SYSTEM MONITORING(CPU,MEM,DISK)
  51. 51. © 2015 Impetus Technologies - Confidential51 SEARCH
  52. 52. © 2015 Impetus Technologies - Confidential52 Real Time Social Media Analytics
  53. 53. © 2015 Impetus Technologies - Confidential53 CREATING NEW SEARCH FROM DATA SOURCE
  54. 54. © 2015 Impetus Technologies - Confidential54 REAL-TIME SENTIMENTS AND CLASSIFICATION
  55. 55. © 2015 Impetus Technologies - Confidential55 REAL-TIME TOPIC CATEGORIZATION
  56. 56. © 2015 Impetus Technologies - Confidential56 Thank you. Questions?? inquiry@streamanalytix.com www.StreamAnalytix.com Contact us for an On-premise OR Cloud based trial and/or Proof of concept Meet us at Strata Hadoop World in New York in September
  57. 57. Twitter Tag: #briefr The Briefing Room Perceptions & Questions Analyst: Robin Bloor
  58. 58. Of Lakes and Streams Robin Bloor, PhD
  59. 59. The Division Analytics and streaming analytics are not at all the same
  60. 60. The Biological Analog u  Our human control system works at different speeds: •  Internal systems – enteric nervous system •  Instant external reflex – spinal cord •  Fast external response – motor systems •  Considered response – the brain u  Swift external response is predictive analytics & triggers u  Considered response is analytics
  61. 61. A While Ago…
  62. 62. The Hadoop Disruption
  63. 63. Then Spark Disrupts Hadoop u  Spark has become the de facto vehicle for many distinct Hadoop projects because of its in-memory scale-out capability u  It can do streaming to a degree, but it is not ideal for very low latency applications u  For that you need to scale-up, not out, and a high level of optimization is necessary u  Nevertheless, it has its place
  64. 64. Spark and Storm u  Along with Spark comes with Shark (a Hive- compatible version of Spark) u  Storm provides batch and streaming (event processing capabilities) concurrently via the lambda architecture u  Lambda: batch layer, serving layer, speed layer u  Spark now also has lambda architecture and can thus behave in a similar manner u  Spark currently seems to be more fashionable
  65. 65. My Current View Streaming is more about DATA/ SOFTWARE ARCHITECTURE than anything else
  66. 66. u  There’s clearly a trend to low latency analytics. How do you see this developing? u  Aside from predictive analytics and typical CEP applications, are there any other application areas that you are encountering? u  Please describe a typical implementation, from adoption through development to implementation. u  How much integration work is necessary?
  67. 67. u  What is your current largest customer in terms of streaming volume, and what is the application? u  Do you find yourselves competing directly with Spark or Storm?
  68. 68. Twitter Tag: #briefr The Briefing Room
  69. 69. Twitter Tag: #briefr The Briefing Room Upcoming Topics www.insideanalysis.com August: REAL-TIME DATA September: HADOOP 2.0 October: DATA MANAGEMENT
  70. 70. Twitter Tag: #briefr The Briefing Room THANK YOU for your ATTENTION! Some images provided courtesy of Wikimedia Commons and http://arapisacz.blogspot.com/2009/10/floating-house-from-brad-pitt.html

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