© 2013, Pentaho. All Rights Reserved. pentaho.com. Worldwide +1 (866) 660-7555 1 BI for Big Data Beyond the Hype.

© 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

US and Worldwide: +1 (866) 660-7555 | Slide


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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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23© 2012, Pentaho. All Rights Reserved. pentaho.com. Worldwide +1 (866) 660-7555

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

JOIN THE CONVERSATION. YOU CAN FIND US ON:

© 2013, Pentaho. All Rights Reserved. pentaho.com. Worldwide +1 (866) 660-7555 1 BI for Big Data Beyond the Hype.

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