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© 2013, Pentaho. All Rights Reserved. pentaho.com. Worldwide +1 (866) 660-7555
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BI for Big Data
Beyond the Hype
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Pentaho MissionThe Future of Analytics: Big Data Exploration without Boundaries
Modern, unified data integration and business analytics platform• Native integration into big data ecosystem
• Embeddable, cloud-ready analytics
Fast and Broad Innovation• Open source development model
Critical mass achieved• Over 1,000 commercial customers
• Over 10,000 production deployments
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Ian FyfeBig Data Solutions Engineering, Pentaho Ian brings over 20 years of experience in the business analytics software market with roles spanning consulting services, pre-sales engineering, product management and product marketing. Ian started his career by co-founding a business intelligence startup and has worked at Business Objects, Informix, Epiphany, PeopleSoft and Jaspersoft.
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Common Use Cases
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The Value of Big Data for our CustomersBig opportunities
Improve operational effectiveness• Machines/sensors: predict failures, network attacks
• Financial risk management: reduce fraud, increase security
Reduce data warehouse cost• Integrate new data sources without increased database cost
• Provide online access to ‘dark data’
Drive incremental revenue• Predict customer behavior across all channels
• Understand and monetize customer behavior
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Example Use Cases Today
Transactional• Fraud detection
• Financial services / stock markets
Sub-Transactional• Weblogs
• Social/online media
• Telecoms events
Non-Transactional• Web pages, blogs etc
• Documents
• Physical events
• Application events
• Machine events
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Click Stream AnalyticsFrom buying patterns to revenue
Business Challenge• Monetize buying patterns hidden in billions of
data points
• Quickly analyze multi-channel click stream data
Pentaho Benefits• Reduced ETL time to analyze blended data
from Hadoop, Hbase & data warehouse
• Use of big data analytics to grow revenue from targeted campaigns
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Device Data AnalyticsBig Data for Fortune 100 Enterprise Storage provider
Business Challenge• Affordably scale machine data from storage
devices for customer support app
• Predict device failure
• Enhance product performance
Pentaho Benefits• Easy to use ETL & analysis for Hadoop, Hbase,
& Oracle data sources
• 15x cost improvement
• Stronger performance against customer SLA’s
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HealthcareEmbedded Pentaho to better patient care & compliance through analysis of unstructured digital pen data stored in CouchDB
Online RetailerUnderstanding the buying patterns of 5 million users from click stream data stored in Hadoop & HBase
GamingBetter monetization of premium game features through analyzing large volumes of player data - stored in MongoDB & Infobright
Social CommerceBetter campaign performance through monitoring social media, page clicks and email marketing data stored in HP Vertica
Travel & EntertainmentHelping thousands of travel partners like expedia.co.uk and thomascook.fr improve promotional targeting using Hbase and Hadoop
Mobile & Digital MediaEmbedded Pentaho to measure massive volumes of mobile and event data generated from mobile devices stored in MongoDB
Innovative Organizations Use Pentahoto Unlock Value from Big Data Stores
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Pentaho Embedded AnalyticsNew Revenue Stream in Eight Weeks
Business Challenge• Gain new revenue source from add-on
module with reporting, analysis & dashboards
• Get to market fast to differentiate
Pentaho Benefits• Easy to embed & brand
• Broad capabilities result in new revenue stream
• Increased functionality & compelling visualizations
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Embedded AnalyticsPentaho Uniquely Positioned to Win
Dashboard Framework
Dashboard Designer
Why We Win in Embedded:• Architectural ‘sweet spot’ for Pentaho
platform• Flexible pricing, adaptable to fit partner
pricing• Open source and innovation• Fastest time-to-market for embedded
analytics
Continued Leadership:• Cloud & multi-tenancy ease-of-use• Simplified REST services for ISVs• BI Platform SDK enhancements – deep
solution examples, tutorials and training• Continued focus on standards and
extensibility
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Big Data Technologies BI Strengths and Weaknesses
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The Current Solutions
10,000
2005 20152010
5,000
0
Current Database Solutions are designed for structured data.
• Optimized to answer known questions quickly
• Schemas dictate form/context
• Difficult to adapt to new data types and new questions
• Expensive at petabyte scale
STRUCTURED DATA UNSTRUCTURED DATA
GIG
ABYT
ES O
F DA
TA C
REAT
ED (I
N B
ILLI
ON
S)
10%
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Main Big Data Technologies
Hadoop NoSQL Databases Analytic Databases
Hadoop• Low cost, reliable
scale-out architecture• Distributed computing
Proven success in Fortune 500 companies
• Exploding interest
NoSQL Databases• Huge horizontal scaling
and high availability• Highly optimized for
retrieval and appending• Types
• Document stores• Key Value stores• Graph databases
Analytic RDBMS• Optimized for bulk-load
and fast aggregate query workloads
• Types• Column-oriented• MPP• In-memory
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© 2010, Pentaho. All Rights Reserved. www.pentaho.com.
Hadoop Core Components
HADOOP DISTRIBUTED FILE SYSTEM (HDFS)
❯ Massive redundant storage across a commodity cluster
MAPREDUCE❯ Map: distribute a computational problem
across a cluster❯ Reduce: Master node collects the answers
to all the sub-problems and combines them
MANY DISTROS AVAILABLE
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Major Hadoop Utilities
Apache Hive
Apache Pig
Apache HBase
Sqoop
Oozie
Hue
Flume
Apache Whirr
Apache Zookeeper
SQL-like language and metadata
repository
High-level language for
expressing data analysis programs
The Hadoop database. Random,
real -time read/write access
Highly reliable distributed
coordination service
Library for running Hadoop in the
cloud
Distributed service for collecting and aggregating log and event data
Browser-based desktop interface
for interacting with Hadoop
Server-based workflow engine
for Hadoop activities
Integrating Hadoop with
RDBMS
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Hadoop & Databases
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“The working conditions can be are shocking”
ETL Developer
Big Data Platform Challenges
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Challenges
1. Somewhat immature2. Lack of tooling3. Steep technical learning curve4. Hiring qualified people5. Availability of enterprise-ready products and
tools6. High latency (Hadoop)7. Running inside the cluster
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Challenges
WOULD YOU RATHER DO THIS?
Scheduling
Modeling
Ingestion / Manipulation / Integration
… OR THIS?
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Investigating BI & Big Data Solutions
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Questions to AskBusiness Drivers1. Mandate to reduce EDW costs?
2. Clear use case that you need to solve?
3. Do you have access to technical skill set?
Technical 1. Do you have more than one kind of big data store, for example Hadoop as well as HBase,
MongoDB or Cassandra?
2. Would you prefer to use the same tool for big data stores in addition to your traditional relational data stores?
3. Are you ok waiting minutes or even hours to access your big data?
4. Are you ok using a spreadsheet-like interface to access and analyze your data?
5. Do you need complete BI capabilities, including reporting, interactive visualization, and predictive analytics?
6. Do you need to enrich your big data with data from outside of the big data platform?
7. Is the big data you want to analyze bigger than the amount of memory you have available?
http://blog.pentaho.com/tag/ian-fyfe/
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Demo
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Data IngestionManipulationIntegration
Enterprise & Ad Hoc Reporting
Data DiscoveryVisualization
Predictive Analytics
Complete Big Data Analytics &
Visual Data Management
RelationalHadoop NoSQL Analytic Databases
Pentaho Big Data Analytics
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Open
Discussion
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Thank You
blog.pentaho.com
@Pentaho
Facebook.com/Pentaho
Pentaho Business Analytics
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