Transcript Impetus Technologies Inc.

Real Time Streaming Analytics
Case Study
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© 2014 Impetus Technologies
Agenda
Why rapid growth and
demand for real-time
analytics
Q&A
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© 2014 Impetus Technologies
StreamAnalytix –
Product Overview
Real World Case Study
Business Problem, Solution
Architecture and Outcomes
Brief Intro
• Big Data Solutions & Services company
• Unique in depth, expertise – started Big Data implementations in 2008
• Proven with customer success
• IP and Products
• We deliver - Business Impact from Big Data Solutions
• Technology expertise
• Data Science
• Business Analytics
• Serving Fortune 1000 companies since 1996
• Large-scale and mission critical software platforms
• HQ: Los Gatos, CA; 1500 people
• Offshore operations in 3 cities in India
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Drivers for Real-time Streaming Analytics
Mobile Devices and Apps
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Fleet Operations & Logistics
Security
Energy Industry
IT Operations
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Drivers for Real-time Streaming Analytics
You and I :
The ‘CUSTOMER’
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© 2014 Impetus Technologies
Drivers for Real-time Streaming Analytics
Business
Operations
Business
Analytics
Real-time
Streaming Analytics
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Real-time Business Analytics – The “Batch Gap”
The batch workflow is too slow
Views are out of date
Just a few hours of data.
Data absorbed into Batch Views
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Now
Time
Not yet
absorbed.
Blended View – Historical and NOW
Blended View
view
now
t
Hadoop works great back here
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Storm works
here
Big Data and Fast Data Combined
Batch Layer
Serving Layer
Batch view
All data
Incoming
Data
Pre-computed
information
Batch view
Batch re-compute
Merge
Query
Speed Layer
Real time view
All data
Pre-computed
information
Real time
increment
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Real time view
Enterprise Class Real time Streaming Analytics Platform
A Product developed and offered by
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At a Glance
StreamAnalytix is a software platform that enables enterprises to analyze and
respond to events in real-time at Big Data scale. It is designed to rapidly build and
deploy streaming analytics applications for any industry vertical, any data format,
and any use-case
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StreamAnalytix Block Diagram
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Case Study – Hosted Contact Center Solution
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Case Study– Hosted Contact Center Solution
IVR
Agent
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Queue
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Case Study– Hosted Contact Center Solution
Problem Statement
•
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Reactive –
Customer service
complaints on “what
happened to my call ?”
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Proactive –
Business teams want
to understand
dominant call paths
Diagnostics
- Easier
- Faster
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Lower “Queue” time
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Proactive Abandoned call
analysis
Hang up on IVR/hold
Case Study – Hosted Contact Center Solution
Technical Requirements
Log Aggregation
• Stream raw log events from multiple
remote servers
• Filter incoming log events – before
storage
• Index/search of log events
Auto Correlate logs in real-time
IVR Dominant Path
• Correlate log events arriving at
different time intervals based on
System ID, Channel ID, Call ID
• Visualize the complete call path
for a particular id
Real-Time Dashboard and Alerts
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Ability to show counters on the existing Log Monitoring dashboard. For eg. #of inbound calls per tenant
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SLA based alarms – ability to generate alarms based on SLA threshold values over a moving time window per tenant.
© 2014 Impetus Technologies
Case Study – Hosted Contact Center Solution
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Case Study – Hosted Contact Center Solution
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Case Study – Hosted Contact Center Solution
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© 2014 Impetus Technologies
Case Study – Hosted Contact Center Solution
Outcome, Next steps
• Successfully solved key problems
• Next steps
– Call log aggregation, Indexing and
Search
– Real-time call path picture
– Dominant path analytics
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– Sentiment analysis in real time
(chat)
– Audio to text: Sentiment
analytics on transcript
– Rich real-time dash-boarding
and live counters
?
Q&A
(Use the chat/Q&A panel)
Email us at [email protected]
www.StreamAnalytix.com
Request: On-premise and Cloud based trial and/or Proof of concept
Meet us at Spark Summit in New York City this week!
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Recent Webcast Recap– Archived on the Website
Real-time Streaming
Analytics: Business Value,
Use Cases, and Architectural
Considerations
Real-time Streaming
Analytics for
Enterprises based on
Apache Storm
Impetus.com/webinar
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