Turning Data into Business Insights with Analytics on IBM iIan JarmanBusiness Unit ExecutiveIBM STG Lab Services

Doug MackDB2 for i Analytics ConsultantIBM STG Lab Services

The World of Big Data & Analytics is Rapidly Expanding

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Untapped Resource Empower Everyone Increased Value

Share of server and storage spending

on big data and analytics by 2016

Growth of unstructured big data

analytics spending2013 – 2017

Spending of analytics solutions focused

on traditional enterprise 2013 – 2017

35% 22% 90%

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Why are big data and analytics getting so much attention?

Designed for Big Data

* Source: 2H13 IBM GMV Survey

Gain actionable insights from big data & analytics

Insurance

• 360˚ View of Domain or Subject

• Catastrophe Modeling• Fraud & Abuse

Banking

• Optimizing Offers and Cross-sell

• Customer Service and Call Center Efficiency

Telco

• Pro-active Call Center• Network Analytics• Location Based

Services

Energy & Utilities

• Smart Meter Analytics• Distribution Load

Forecasting/Scheduling• Condition Based

Maintenance

Media & Entertainment

• Business process transformation

• Audience & Marketing Optimization

Retail

• Actionable Customer Insight

• Merchandise Optimization

• Dynamic Pricing

Travel & Transport

• Customer Analytics & Loyalty Marketing

• Predictive Maintenance Analytics

Consumer Products

• Shelf Availability• Promotional Spend

Optimization• Merchandising

Compliance

Government

• Civilian Services• Defense & Intelligence• Tax & Treasury Services

Healthcare

• Measure & Act on Population Health Outcomes

• Engage Consumers in their Healthcare

Automotive

• Advanced Condition Monitoring

• Data Warehouse Optimization

Life Sciences

• Increase visibility into drug safety and effectiveness

Chemical & Petroleum

• Operational Surveillance, Analysis & Optimization

• Data Warehouse Consolidation, Integration & Augmentation

Aerospace & Defense

• Uniform Information Access Platform

• Data Warehouse Optimization

Electronics

• Customer/ Channel Analytics

• Advanced Condition Monitoring

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Processors flexible, fast execution of

analytics algorithms

Memory large, fast workspace to

maximize business insight

Data Bandwidth bring massive amounts of information

to compute resources in real-time

4X threads per core vs. x86

4Xmemory bandwidth vs. x86

2.4X more I/O bandwidth than POWER7

POWER8 is optimized for big data & analytics

Optimized for a broad range of data and analytics:

Industry Solutions

Chip Memory Flash/SSD DiskCache

Size, distance and duration matter for big data and analytics

50X faster insights2

24:1consolidation3

IBM FlashSystem

Next Generation In-Memory

75% less storage1

Power Systems can deliver insight to the point of impactwith big data & analytics accelerators

POWER8 with CAPI Flash Accelerators

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1- Source: COCC Cast Study http://bit.ly/1iQemuu2- Based on IBM internal tests comparing DB2 BLU with a comparably tuned competitor configuration executing a materially identical 2.6TB operational analytics workload in a controlled laboratory environment. Test measured 60 concurrent user report throughput executing identical Cognos BI report workloads. Report per hour (RPH) metric calculated for each category of reports as total completed reports/hours to completion of all reports in the category. Competitor configuration: HP DL380p, 24 cores, 256GB RAM, Traditional Database, SuSE Linux 11SP3 (Database) and HP DL380p, 16 cores, 384GB RAM, Cognos 10.2.1.1, SuSE Linux 11SP3 (Cognos). IBM configuration: IBM S824, 24 cores, 256GB RAM, DB2 10.5, AIX 7.1 TL2 (Database) and IBM S824, 16 cores, 384GB RAM, Cognos 10.2.1.1, SuSE Linux 11SP3 (Cognos). Results may not be typical and will vary based on actual workload, configuration, applications, queries and other variables in a production environment.3- CAPI claim is not final as testing is still in progress. Compare is versus commodity x86 servers.

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IBM can help build your big data & analytics solution

All Data

Key Business

Processes

Unstructured Data

Structured Data Industry Solutions

Business & Predictive Analytics

Research

Demonstration

Commercialization

Cross-industry Applications

IBMResearch Project

2006

Jeopardy!Grand

ChallengeFeb 2011

Watson for

HealthcareAug 2011

Watson Industry

Solutions

Watson for Client

Engagement

Expansion

IBM is putting Watson to work

Big data analytics with IBM Solution for Hadoop

Speed MattersHigher ingest rates delivers 37% faster insights than competitive Hadoop solutions with 31% fewer data nodes.1

Availability MattersBetter reliability and resiliency with 73% fewer outages and 92% fewer performance problems over x86.2

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+

Power 7R2 Servers DS3700 Storage

Powered by

A storage-dense integrated platform optimized to simplify and accelerate unstructured big data & analytics

Integrated platform solution for Hadoop ready for

analytics software

1) Based on STG Performance testing comparing to Cloudera/HP published benchmark2)CLAIMS: Solitaire Interglobal Paper - Power Boost Your Big Data Analytics Strategy – http://www.ibm.com/systems/power/solutions/assets/bigdata-analytics.html?LNK=wf

Cognos BI with BLU Acceleration

Power Systems

Analytic Data Mart

(BLU Tables)

Poor performing Oracle or Teradata

warehouse

Create tables, Load and Go! Instant performance boost Handles terabytes of data No indexes/aggregates to create

and tune

Cognos BI with BLU Acceleration

on POWER8

EDW Application OLAP Application

Easily create and load a BLU Acceleration in-memory mart

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Cognos and DB2 BLU AccelerationMove up to POWER8 and gain 50X faster insights

Row (Relational) Oriented vs. Columnar Databases

Model is flexible (highly normal) OLTP and some OLAP Scale up INSERT or DELETE is less work Indexing required Full rows easy to return Wide result sets All the data in memory is more difficult

but index only access is FAST

Data stays in relational model

Model is inflexible OLAP Scale out INSERT or DELETE is more work No indexing required Full rows not easy to return Narrow result sets All the data in memory

Data must be moved from relational to columnar database

Large enterprises DB2 for i can be a data source, or provide data

warehouse or data mart infrastructure Or for operational reporting with applications Cognos on Linux or AIX in LPAR

Mid-sized companies DB2 Web Query was designed to address

companies where full range of enterprise analytics solutions are not required

Budgets and staff are smaller

Business intelligence and analytics for IBM i

Grupo Martins use Cognos to increase revenue, boost telesales

Need

Distributor of 13,000 consumer goods products . to more than 750,000 retail outlets needed to improve insights to sales teams on upcoming promotions and product trends.

Solution

Power 780 server with DS8000 storage

IBM i and AIX

IBM Cognos BI V10

Grupo Martins sought to increase revenue and grow its business by improving performance management in sales and marketing

Results

Increased revenue by 17 percent as a result of accurate and speedy predictive analysis and recommended sales actions that boosted individual store purchases

Solution provides predictive outcomes for given prices and volumes to improve the accuracy of future sales and marketing models.

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Gebbers Farms integrated Cognos with IBM i data warehouse

Need

Needed a flexible and robust reporting solution that enabled them to analyze and integrate with their operational data

Solution

N2N industry solution on IBM i

Data warehouse in DB2 for i in an LPAR

Cognos 10 BI V10 on Windows

Grower and distributor of apples and cherries needed to integrate their BI solution with their existing operations, data and staff

Results

Built operational reports using Cognos and created a flexible data warehouse integrated with their existing infrastructure

Using their existing infrastructure enabled them to avoid hiring dedicated staff for their data warehouse

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DB2 Web Query helped Miller Zell reduce costs and complexity

Need

Needed to simplify Project Job Cost analysis for their store design concepts and in-store installation plans.

Solution

IBM Power 720 with IBM i

Oracle JD Edwards World

DB2 Web Query

Retail solutions provider wanted a BI solution that would reduce costs and complexity of their Windows-based portal

Results

Removed a Windows-based portal, eliminating the need for dedicated staff and enabling on-demand reporting

“We have a powerful team, but a small IT staff. Previously, we had a person dedicated to managing an open source portal. When we moved our BI environment to IBM i, we leveraged our current skills and infrastructure to deliver a dynamic BI platform.”

— Gina Strickland, Vice President, Information Technology, Miller Zell

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DB2 for i Query Acceleration Technologies Parallelism

DB2 Symmetric Multiprocessing parallelizes DB2 for i tasks, including queries and index builds Indexing Strategies

DB2 for i is very good at self tuning with automated index creation, but it can only be re-active, not pro-active and cannot create every optimal index

Encoded Vector Indexes – columnar database “like” Aggregation Strategies

Materialized Query Tables: Optimizer aware summary tables Encoded Vector Indexes with Aggregates (new in 7.1)

Adaptive Query Processing Self adjusts plan during run time Self learns by taking info and storing for later use

Big Data DB2 for i LIMITS Leadership

Management Tools iNav Database functions System wide Index Advice, Visual Explain, SQL Plan Cache, etc.

Application Extensions SQL Language Extensions DB2 Web Query

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10

11

1

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DB2 for i DB2 for i

Oracle Oracle

Microsoft SQLServer Microsoft SQLServer

Netezza Netezza

DB2 for AIX DB2 for AIX

Other Other

management system do you use for reporting? management system do you use for reporting? operational (production) databases, what database operational (production) databases, what database If you separate your reporting database from your If you separate your reporting database from your

DB2 Web Query for iGain faster insights and analysis from your business data

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Authoring Tool“Intuitive”

Authoring Tool“Intuitive” Reports & Graphs

“Flexible delivery”Reports & Graphs

“Flexible delivery”

Dashboards“Insightful”

Dashboards“Insightful”

OLAP“Extensible”

OLAP“Extensible”

Providing analytics and Query/400 Modernization for the IBM i Client Low cost solution with upgrade from Query/400 Leveraging DB2 for i advanced query optimization technologies

New in Version 2 or in the latest TR (Group PTF)

New Packaging Only 2 options: Express or Standard Edition Express is entry level, all users are named Standard adds Report Distribution, APIs, MS SQLServer

adapter and run time group licensing New Security Center

Role based authorizations Run Time Environment

Control library list processing at run time; create user exit (e.g., to maintain an audit log)

Simple Dashboards (on top of already existing dashboard builder) Personal Dashboards; Mobile Dashboards

Lots More! Single Sign On DB2 Family Access (DB2/z, DB2 for Linux/Unix/Windows) Easier integration with existing or customized apps with REST

web services application extension

New in Version 2 or in the latest TR (Group PTF)

DB2 Web Query contains over 100 different types of visualizations

Bar, Pie, Line, 3-D, Thermometers, gas gauges, stock reports, funnels, and more

New Visualizations include Heat Maps Bubble Charts Tag Clouds Streamgraph

Geo Maps• Interactive mapping out-of-the-box• 9 Layers of Zoom• Translated Countries• Adjust Heatscale and Opacity• Create customized maps

Thank You!