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Journey To Becoming a Data-Driven Enterprise:
Pivotal Big Data Suite Technical Overview
Feras Alsamawi
Senior Field Engineer
Pivotal
2© Copyright 2015 Pivotal. All rights reserved.
Agenda
•  Big Data Challenges
•  The Value of Data
•  Pivotal Big Data Suite
•  The Open Data Platform
•  Big Data Architectures
© Copyright 2015 Pivotal. All rights reserved.
THE POWER OF 1
R
X
Increasing
Freight Utilization Rail
Predictive
Maintenance Healthcare
Predictive
Diagnostics Power
Driving Outcomes That Matter
One Percent Improvement Equals
$27B
Industry Value by
Reducing System
Inefficiency
$63B
Industry Value by
Reducing Process
Inefficiency
$66B
Industry Value with
Efficiency Improvements
In Gas-fired Power
Plant Fleets
Source: General Electric
4© Copyright 2015 Pivotal. All rights reserved.
BIG DATA
CHASM
70%
of data
generated by
customers
80%
of data stored
3%
prepared for
analysis
0.5%
being
analyzed
<0.5%
being
operationalized
4
THE DATA DIVIDE
5© Copyright 2015 Pivotal. All rights reserved.
Software Is Eating The World
Data Is Fueling Software
SOFTWARE IS EATING THE WORLD
6© Copyright 2015 Pivotal. All rights reserved.
JOURNEY TO A DATA-DRIVEN ENTERPRISE
Deploy analytic apps and
automate at scale
Perform advanced analytics
Discover insights
Modernize data
infrastructure
7© Copyright 2015 Pivotal. All rights reserved.
The value of Data
Time
Value of
Information
µs ms s hour day month year yr+
8© Copyright 2015 Pivotal. All rights reserved.
Traditional
Systems
The value of Data
Time
Value of
Information
µs ms s hour day month year yr+
9© Copyright 2015 Pivotal. All rights reserved.
Speed Layer
Traditional
Systems
Pivotal’s λ Architecture
Serving Layer
“Big Data”
Time
Value of
Information
µs ms s hour day month year yr+
Spring XD
Pivotal HD
Pivotal GemFire
Batch
Layer
10© Copyright 2015 Pivotal. All rights reserved.
WHY PIVOTAL FOR BIG DATA ?
Complete
platform
SQL on Hadoop
leadership
Deployment
options
Open source
Flexible licensing
Advanced data
services
Pivotal Data Engineering Pivotal LabsPivotal Data Science
11© Copyright 2015 Pivotal. All rights reserved. 11© Copyright 2013 Pivotal. All rights reserved.
Big Data Suite Components
12© Copyright 2015 Pivotal. All rights reserved.
HDFSData Lake
Expert System /
Machine Learning
In-Memory
Real-Time Data
Continuous Learning
Continuous Improvement
Continuous Adapting
Data Stream Pipeline
Multiple Data Sources
Real-Time Processing
Store Everything
Pro-Active, Self-Improving, Machine Learning
Systems
13© Copyright 2015 Pivotal. All rights reserved.
Ingest Transform Sink
SpringXD
GemFire
Data Stream Needs an Agile, Scalable and
Fast Solution
HAWQ GPDB
Data
Lake
14© Copyright 2015 Pivotal. All rights reserved.
Ingest Transform Sink
SpringXD
Distributed
Computing
In-Memory
Real-Time Data
Spring XD Orchestrates and Automates all the
Steps on Data Stream Pipelining
Expert System /
Machine Learning
Extensible
Open-Source
Fault-Tolerant
Horizontally Scalable HAWQ GPDB
Data
Lake
15© Copyright 2015 Pivotal. All rights reserved.
Ingest / SINK Process Analyze
•  No coding required
•  Dozens of built-in
connectors
•  Seamless integration with
Kafka, Sqoop
•  Create new connectors
easily using Spring
•  Call Spark, Reactor or
RxJava
•  Built-in configurable filtering,
splitting and transformation
•  Out-of-box configurable jobs
for batch processing
•  Import and invoke PMML
jobs easily
•  Call Python, R, Madlib and
other tools
•  Built-in configurable
counters and gauges
Spring XD
State of the Art Data Pipeline Automation
16© Copyright 2015 Pivotal. All rights reserved.
Ingest Transform Sink
SpringXD
Distributed
Computing
GemFire Provides Scalable, Low-Latency
Data Access, Storage and Event Processing
Expert System /
Machine Learning
GemFire
Extensible
Open-Source
Fault-Tolerant
Horizontally Scalable HAWQ GPDB
Data
Lake
17© Copyright 2015 Pivotal. All rights reserved.
GemFire
•  In-Memory Enterprise Data Grid
•  Horizontally Scalable, Consistent, Highly
Available
•  Event handling
•  Continuous Queries
•  Enterprise Data Geo Distribution
In-memory Real Time Data
18© Copyright 2015 Pivotal. All rights reserved.
Ingest Transform Sink
SpringXD
Distributed
Computing
Pivotal Provides SQL Based
Advanced Analytics
GemFire
Extensible
Open-Source
Fault-Tolerant
Horizontally Scalable
Data
Lake
HAWQ GPDB
19© Copyright 2015 Pivotal. All rights reserved.
HAWQ
•  Massively Parallel Processing
RDBMS on HADOOP
•  ANSI SQL on Hadoop
•  Extremely high performance for
analytics (not like Hive)
•  Stores all data directly on
HDFS
•  Functions in MADlib, R/
Python/Java, Perl, pgsql or C
languages
Advanced SQL analytics in Hadoop
Combining SQL with Hadoop is key for analytics
SQL remains #1 choice for Data Science
20© Copyright 2015 Pivotal. All rights reserved.
Data Streaming Reference Architecture
Data Feeds Transactional Apps Analytic Apps
Data Stream Pipeline
Distributed
Computing
Real-Time Data
Expert Systems &
Machine Learning
Advanced
Analytics
HDFSData Lake
21© Copyright 2015 Pivotal. All rights reserved.
Data Streaming Reference Architecture
Data Feeds Transactional Apps Analytic Apps
Data Stream Pipeline
HDFSData Lake
GemFire HAWQ GPDB
SpringXD
BUILT FOR THE SPEED OF BUSINESS
23© Copyright 2015 Pivotal. All rights reserved.
Financial Compliance
BUSINESS PROBLEM
•  Ensure compliance with Dodd-Frank and Basel
Committee regulations
•  Identify underlying risk and fraud while reducing the
compliance department’s overburdened
Emails Chats Trades
Transactions Policy Securities
Phone Calls Watch Lists …
Financial compliance
Data Lake
Data
integration
Data clean
up
Modeling
Classification
and ranking
Analyst user interfaces
Feedback
Analytics
Analyst feedback
Data integration: e.g., append
trade information with email and
chat communications
Data cleanup: e.g.,
identify newsletters and
spam emails
Modeling:
•  Predictive modeling to flag
messages and trades
•  Graph and cohort analysis
Analyst feedback
Reviewed fraud instances
included in periodic model
refreshes
SOLUTION
Ÿ  A data lake platform coupled with cutting edge data
science techniques
Ÿ  Flexible user interface to promote an adaptive,
continuously learning compliance framework
24© Copyright 2015 Pivotal. All rights reserved.
Pivotal Topic & Sentiment Analysis Engine
External
Tables
PXF
HDFS
Source: http Sink: hdfs
Parallel Parsing
of JSON
(PL/Python)
HAWQ
Nightly Cron Jobs
Topic Analysis
through MADlib pLDA
Unsupervised
Sentiment Analysis
(PL/Python)
D3.js
Spring XD
Twitter Decahose (~55 million tweets/day)
25© Copyright 2015 Pivotal. All rights reserved. 25© Copyright 2013 Pivotal. All rights reserved.
IoT Architectures
– The connected Car
26© Copyright 2015 Pivotal. All rights reserved.
The Connected Car Architecture
INGESTION
JSON / HTTP
STREAM PROCESSING
Spring XDTransformEnrich
DATA LAKE
Pivotal HDSink
ADVANCED ANALYTICS
HAWQ
REAL-TIME DATA INSIGHTS
GemFire
MOBILE SERVICES
MICROSERVICES
Pivotal CF Dashboard Analytics App Simulator
IoT APPS
Rabbit MQ
PUSH
27© Copyright 2015 Pivotal. All rights reserved.
Horizontally Scalable
Fault Tolerant
Extensible
Open-Source
STREAM PROCESSING
Spring XD
Rabbit MQ
DATA LAKE
Pivotal HD
ADVANCED ANALYTICS
HAWQ
ENRICHER PREDICTIVE ANALYTICS
+ Timestamp
& GUID
+ MPG, rangE
& route
MOBILE
APP
JSON
REAL-TIME DATA INSIGHTS
GemFire
CAR
SENSOR
Sink
Tap
DASHBOARD
28© Copyright 2015 Pivotal. All rights reserved.
FOR FURTHER INFO…
•  Pivotal Data Product Info, Docs and Downloads @ http://pivotal.io/big-data
•  Pivotal Blog @ http://blog.pivotal.io
•  Pivotal Data Science Blog @ http://blog.pivotal.io/data-science-pivotal
•  Pivotal Academy @ https://pivotal.biglms.com
•  Or reach out to your local Pivotal Account Executive…
Digital Transformation Forum
Disrupt or Be Disrupted
19 OCTOBER · BMW WELT EVENT CENTRE · MUNICH

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Pivotal Digital Transformation Forum: Journey to Become a Data-Driven Enterprise

  • 1. Journey To Becoming a Data-Driven Enterprise: Pivotal Big Data Suite Technical Overview Feras Alsamawi Senior Field Engineer Pivotal
  • 2. 2© Copyright 2015 Pivotal. All rights reserved. Agenda •  Big Data Challenges •  The Value of Data •  Pivotal Big Data Suite •  The Open Data Platform •  Big Data Architectures
  • 3. © Copyright 2015 Pivotal. All rights reserved. THE POWER OF 1 R X Increasing Freight Utilization Rail Predictive Maintenance Healthcare Predictive Diagnostics Power Driving Outcomes That Matter One Percent Improvement Equals $27B Industry Value by Reducing System Inefficiency $63B Industry Value by Reducing Process Inefficiency $66B Industry Value with Efficiency Improvements In Gas-fired Power Plant Fleets Source: General Electric
  • 4. 4© Copyright 2015 Pivotal. All rights reserved. BIG DATA CHASM 70% of data generated by customers 80% of data stored 3% prepared for analysis 0.5% being analyzed <0.5% being operationalized 4 THE DATA DIVIDE
  • 5. 5© Copyright 2015 Pivotal. All rights reserved. Software Is Eating The World Data Is Fueling Software SOFTWARE IS EATING THE WORLD
  • 6. 6© Copyright 2015 Pivotal. All rights reserved. JOURNEY TO A DATA-DRIVEN ENTERPRISE Deploy analytic apps and automate at scale Perform advanced analytics Discover insights Modernize data infrastructure
  • 7. 7© Copyright 2015 Pivotal. All rights reserved. The value of Data Time Value of Information µs ms s hour day month year yr+
  • 8. 8© Copyright 2015 Pivotal. All rights reserved. Traditional Systems The value of Data Time Value of Information µs ms s hour day month year yr+
  • 9. 9© Copyright 2015 Pivotal. All rights reserved. Speed Layer Traditional Systems Pivotal’s λ Architecture Serving Layer “Big Data” Time Value of Information µs ms s hour day month year yr+ Spring XD Pivotal HD Pivotal GemFire Batch Layer
  • 10. 10© Copyright 2015 Pivotal. All rights reserved. WHY PIVOTAL FOR BIG DATA ? Complete platform SQL on Hadoop leadership Deployment options Open source Flexible licensing Advanced data services Pivotal Data Engineering Pivotal LabsPivotal Data Science
  • 11. 11© Copyright 2015 Pivotal. All rights reserved. 11© Copyright 2013 Pivotal. All rights reserved. Big Data Suite Components
  • 12. 12© Copyright 2015 Pivotal. All rights reserved. HDFSData Lake Expert System / Machine Learning In-Memory Real-Time Data Continuous Learning Continuous Improvement Continuous Adapting Data Stream Pipeline Multiple Data Sources Real-Time Processing Store Everything Pro-Active, Self-Improving, Machine Learning Systems
  • 13. 13© Copyright 2015 Pivotal. All rights reserved. Ingest Transform Sink SpringXD GemFire Data Stream Needs an Agile, Scalable and Fast Solution HAWQ GPDB Data Lake
  • 14. 14© Copyright 2015 Pivotal. All rights reserved. Ingest Transform Sink SpringXD Distributed Computing In-Memory Real-Time Data Spring XD Orchestrates and Automates all the Steps on Data Stream Pipelining Expert System / Machine Learning Extensible Open-Source Fault-Tolerant Horizontally Scalable HAWQ GPDB Data Lake
  • 15. 15© Copyright 2015 Pivotal. All rights reserved. Ingest / SINK Process Analyze •  No coding required •  Dozens of built-in connectors •  Seamless integration with Kafka, Sqoop •  Create new connectors easily using Spring •  Call Spark, Reactor or RxJava •  Built-in configurable filtering, splitting and transformation •  Out-of-box configurable jobs for batch processing •  Import and invoke PMML jobs easily •  Call Python, R, Madlib and other tools •  Built-in configurable counters and gauges Spring XD State of the Art Data Pipeline Automation
  • 16. 16© Copyright 2015 Pivotal. All rights reserved. Ingest Transform Sink SpringXD Distributed Computing GemFire Provides Scalable, Low-Latency Data Access, Storage and Event Processing Expert System / Machine Learning GemFire Extensible Open-Source Fault-Tolerant Horizontally Scalable HAWQ GPDB Data Lake
  • 17. 17© Copyright 2015 Pivotal. All rights reserved. GemFire •  In-Memory Enterprise Data Grid •  Horizontally Scalable, Consistent, Highly Available •  Event handling •  Continuous Queries •  Enterprise Data Geo Distribution In-memory Real Time Data
  • 18. 18© Copyright 2015 Pivotal. All rights reserved. Ingest Transform Sink SpringXD Distributed Computing Pivotal Provides SQL Based Advanced Analytics GemFire Extensible Open-Source Fault-Tolerant Horizontally Scalable Data Lake HAWQ GPDB
  • 19. 19© Copyright 2015 Pivotal. All rights reserved. HAWQ •  Massively Parallel Processing RDBMS on HADOOP •  ANSI SQL on Hadoop •  Extremely high performance for analytics (not like Hive) •  Stores all data directly on HDFS •  Functions in MADlib, R/ Python/Java, Perl, pgsql or C languages Advanced SQL analytics in Hadoop Combining SQL with Hadoop is key for analytics SQL remains #1 choice for Data Science
  • 20. 20© Copyright 2015 Pivotal. All rights reserved. Data Streaming Reference Architecture Data Feeds Transactional Apps Analytic Apps Data Stream Pipeline Distributed Computing Real-Time Data Expert Systems & Machine Learning Advanced Analytics HDFSData Lake
  • 21. 21© Copyright 2015 Pivotal. All rights reserved. Data Streaming Reference Architecture Data Feeds Transactional Apps Analytic Apps Data Stream Pipeline HDFSData Lake GemFire HAWQ GPDB SpringXD
  • 22. BUILT FOR THE SPEED OF BUSINESS
  • 23. 23© Copyright 2015 Pivotal. All rights reserved. Financial Compliance BUSINESS PROBLEM •  Ensure compliance with Dodd-Frank and Basel Committee regulations •  Identify underlying risk and fraud while reducing the compliance department’s overburdened Emails Chats Trades Transactions Policy Securities Phone Calls Watch Lists … Financial compliance Data Lake Data integration Data clean up Modeling Classification and ranking Analyst user interfaces Feedback Analytics Analyst feedback Data integration: e.g., append trade information with email and chat communications Data cleanup: e.g., identify newsletters and spam emails Modeling: •  Predictive modeling to flag messages and trades •  Graph and cohort analysis Analyst feedback Reviewed fraud instances included in periodic model refreshes SOLUTION Ÿ  A data lake platform coupled with cutting edge data science techniques Ÿ  Flexible user interface to promote an adaptive, continuously learning compliance framework
  • 24. 24© Copyright 2015 Pivotal. All rights reserved. Pivotal Topic & Sentiment Analysis Engine External Tables PXF HDFS Source: http Sink: hdfs Parallel Parsing of JSON (PL/Python) HAWQ Nightly Cron Jobs Topic Analysis through MADlib pLDA Unsupervised Sentiment Analysis (PL/Python) D3.js Spring XD Twitter Decahose (~55 million tweets/day)
  • 25. 25© Copyright 2015 Pivotal. All rights reserved. 25© Copyright 2013 Pivotal. All rights reserved. IoT Architectures – The connected Car
  • 26. 26© Copyright 2015 Pivotal. All rights reserved. The Connected Car Architecture INGESTION JSON / HTTP STREAM PROCESSING Spring XDTransformEnrich DATA LAKE Pivotal HDSink ADVANCED ANALYTICS HAWQ REAL-TIME DATA INSIGHTS GemFire MOBILE SERVICES MICROSERVICES Pivotal CF Dashboard Analytics App Simulator IoT APPS Rabbit MQ PUSH
  • 27. 27© Copyright 2015 Pivotal. All rights reserved. Horizontally Scalable Fault Tolerant Extensible Open-Source STREAM PROCESSING Spring XD Rabbit MQ DATA LAKE Pivotal HD ADVANCED ANALYTICS HAWQ ENRICHER PREDICTIVE ANALYTICS + Timestamp & GUID + MPG, rangE & route MOBILE APP JSON REAL-TIME DATA INSIGHTS GemFire CAR SENSOR Sink Tap DASHBOARD
  • 28. 28© Copyright 2015 Pivotal. All rights reserved. FOR FURTHER INFO… •  Pivotal Data Product Info, Docs and Downloads @ http://pivotal.io/big-data •  Pivotal Blog @ http://blog.pivotal.io •  Pivotal Data Science Blog @ http://blog.pivotal.io/data-science-pivotal •  Pivotal Academy @ https://pivotal.biglms.com •  Or reach out to your local Pivotal Account Executive…
  • 29. Digital Transformation Forum Disrupt or Be Disrupted 19 OCTOBER · BMW WELT EVENT CENTRE · MUNICH