Hadoop is sparking a Big Data analytics revolution. But all the Hadoop insights in the world are worth nothing unless they lead to new, profitable action. To translate Hadoop insights into action in real time, more and more enterprises are combining Hadoop with the power of in-memory computing.  Join us as we outline the tremendous benefits of merging Hadoop with in-memory data management, the challenges of doing so, and tips for getting started.

1. In-Memory &
Hadoop:
Real-time
Big Data Intelligence
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2. Your speaker
Manish Devgan
Director of Product
Management
Terracotta
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3. What we’ll cover in this webcast
•
What’s Hadoop? (quick intro)
•
Hadoop’s weaknesses
•
Emerging best practices for combining
Hadoop and in-memory data management
•
Real-time intelligence example
•
Getting started with in-memory and Hadoop
•
Q&A
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4. What is Hadoop?
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5. What is
•
?
Hadoop is open-source software data management framework
used to draw insights from data
Components
HDFS*: Scalable &
distributed Storage
Benefits
Scalable
• Efficiently store and process large
data sets
• Data distributed across cluster
nodes
• Name node keeps track of location
Reliable
MapReduce: Parallel
Processing of data
Rich & Flexible
• Splits a task for processing based
on data locality and then
assembles results
• Comprises of Map() procedure for
filtering & sorting and Reduce()
procedure for summarizing
• Get redundant storage, with failover
across cluster
• Complimentary set of tools &
frameworks
• Store data in any format
Economical
• Deploy on commodity hardware
*Hadoop Distributed File System
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6. What is
•
?
With Hadoop, you can ask interesting questions about your data
and get answers economically
Questions Hadoop can help answer
How can I target promotions to my customers for better
sales?
How risky are each of my customers?
Which advertisement should I show to optimize return?
How relevant is a result for a given search?
When will my machinery likely have a malfunction?
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7. Hadoop’s Weaknesses
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8. Hadoop’s Weaknesses
•
No support for real-time insights
•
No support to facilitate interactive and exploratory data analysis
•
Challenging framework for computation beyond Map Reduce
•
Lacks tools for business analysts
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9. Emerging best practices
for combining Hadoop and
in-memory data management
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10. Combining Hadoop and In-memory Data Management
-
Businesses are looking for ways to mine real-time insights to
provide competitive advantages
-
Increased adoption of transactional system data for analytics is
blurring the line between OLTP and OLAP
-
New frameworks and products are bringing in-memory
technologies to the Hadoop ecosystem
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11. Real-time Data Integration with Hadoop
Real-time Data Apps
Web
Apps
Mobile
Apps
Dashboards
& Mashups
Transactional
Apps
Data Feeds
Operational
Intelligence
In-memory Data Management Platform
Real-time
data
Real-time
Insights
Data Sources
Events
Log Data
POS Data
Social Media
Sensors
Images/Video
s
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12. Real-time intelligence example
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13. BigMemory & Hadoop in financial services
Before: Custom ETL connector pushing batch data
BigMemory Store
Hadoop M/R
Short Term
Transaction
Data
Long Term
Transaction
Data
Rules &
Triggers
Credit
Reference
Data
Tagged
Accounts
Hadoop Cluster
HDFS to BigMemory
Processing
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14. BigMemory & Hadoop in financial services
Today: Streaming Data insights
BigMemory Store
BigMemoryHadoop
Connector
Insights
Short Term
Transaction
Data
Long Term
Transaction
Data
Rules &
Triggers
Credit
Reference
Data
Hadoop M/R
Tagged
Accounts
Hadoop Cluster
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15. Getting started with
in-memory and Hadoop
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16. How to get started with In-memory and Hadoop?
•
If you already have a Hadoop project, look for use cases where
you want real-time access to insights
•
Start with a small-to-medium sized (20-40 nodes) cluster with a
well-defined use case requiring fast access to data
•
Consider exploratory use cases where you’re doing iterative
analysis on a data set to get answers faster
© 2013 Terracotta Inc.
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17. In-Memory & Hadoop
Questions
Please type yours in the “Questions” panel or in the chat window.
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18. Connect with Terracotta
•
Download “BigMemory & Hadoop” white paper
− Visit:
•
Download “BigMemory-Hadoop Connector”
− Visit:
•
www.terracotta.org (Resources > White Papers)
www.terracotta.org/downloads/hadoop-connector
Contact Manish Devgan
− Email:
•
mdevgan@terracottatech.com
Follow us on Twitter
− @big_memory
•
Stay Tuned
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