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Copyright © 2015, Oracle and/or its affiliates. All rights reserved.
Welcome
Accelerating the Pace of Transformation
Copyright © 2015, Oracle and/or its affiliates. All rights reserved.
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Copyright © 2015, Oracle and/or its affiliates. All rights reserved.
P&G’s Big Data Evolutionto the Oracle Public Cloud
Terry McFaddenPrincipal Information Architect, P&G
Jeff KnudsenEnterprise Architect, Oracle
P&G’s Big Data Evolution to the Cloud
• P&G Overview
• The Case for Big Data: Why P&G Started the Big Data Journey
• How We Got Started
• Original Big Data “proof points”
• Initial Findings and POC Results
• Initial P&G Big Data Cloud Efforts
• How Are We Doing?
• Where Are We Going?
About Procter and Gamble…
• 178 Years old this year
• Countries of operation: ~70
• Countries where are brands are sold: ~180
• Consumers served by our brands: 5 billion (approximate)
• Last FY Revenue: $76.28 billion
Business Description: The Procter & Gamble Company (P&G) is a leading
manufacturer and marketer of branded consumer packaged goods across the world.
P&G manufactures, markets and distributes premium quality, branded beauty, health,
fabric, home, baby, family, and personal care products.
The Case for Big Data:Why P&G Started the Big Data Journey
• Business teams needed access to more data ( sales, market measurements,
demographics, weather, social etc.) with more granularity to help drive deeper
insights.
• Challenges delivering significantly better explanatory insight – “why is this
happening”.
• Wanted to quickly acquire and integrate multiple structured and unstructured data
sources quickly, at volume.
• Needed the ability to be able to integrate a variety of NEW data types. Traditional
approaches not working.
• Growing data volumes = growing storage costs. Intervention needed!
Business Challenges / Opportunities
How We Got Started
• No need to build traditional canonical data models.
• We concluded the Hadoop ecosystem was the right add.
• Buy vs. build: P&G saw no business value in building their own Hadoop
infrastructure.
• P&G liked Oracle’s Big Data Appliance, and fit with other Oracle (e.g. P&G’s
Exadata systems connect to BDA via Infiniband).
• Low cost storage option changes thinking at multiple levels.
• The BDA’s ability to start small and scale as P&G’s Big Data requirements grow.
Why Big Data / Why Oracle
Original Big Data Use Cases
• Category Management / Proof of Platform
• Initiative Launch: Sense and Respond for live new product launches
• Customer Facing Operations – high value questions
• Other Hard questions - “Why is THIS happening”
• Ability to quickly load and integrate structured, unstructured, and semi-structured data
– P&G was able to load and integrate 25+ structured and unstructured data sources in 2+ weeks
– Data sources included conventional and unconventional data sources, market signals, item sales, market share, surveys, social, demographics, weather, and more traditional sources
Conceptual Framing: The Data Factory
Conceptual Framing:
The Data Factory
Physical Frames:
An Engineered Systems Landscape
This continues to evolve:• We DO want to exploit PUBLIC CLOUD for flexibility, scale, cost where possible.
• We DO have data types that have restrictions requiring a “private cloud” approach.
• We MUST balance this dichotomy, for security, cost, and manageability. Factors
include:
• Key features P&G seeks include (not unlike others):
– Cost benefits from multi-tenancy, where we can leverage it.
– Standard Cloud service management and control restrictions.
– Metering, clear cost accounting and elasticity.
– Efficiently coordinate across Public and Private cloud topology.
P&G: Thoughts on Big Data and Cloud Architecture
Big Data Efforts: Learning Intent
Summary of Initial Big Data Cloud activities:
• Testing to understand ease of standing up a Cloudera Hadoop environment.
• Testing to understand network issues, security issues, and data transfer,
loading, integration.
• Testing to understand application development in that ecosystem.
• Testing to understand price performance considerations for a given
workload.
• Overall assessment of scale, flexibility, true elasticity
• Assessment of strategic directions, ecosystem benefits, financials
P&G & the Oracle Big Data Public Cloud
• P&G was experimenting with other Big Data/Public Cloud offerings, but concluded
Oracle deserved a closer look.
• In November of 2014 P&G and Oracle agreed to experiment with a Big Data Cloud
platform for P&G by April 2015.
• Oracle worked directly with P&G to help establish the service.
• Oracle agreed to setup a temporary Big Data Cluster by April 1st, 2015 with the
understanding that P&G would move to the Public Cloud platform when it is GA.
• Oracle turned-over the Big Data Public Cloud Server to P&G on April 1st, 2015.
• Oracle has since expanded it to accommodate growth in August, 2015.
• P&G is now migrating this pilot to the Oracle production environment.
Factors That Influenced our Thinking
Commercial,
Strategic &
Technical factors
...are key determinants
http://www.theregister.co.uk/2015/06/23/ellison_aws_price_war_amazon/
How Are We Doing?
• There have been some challenges, but Development has been very proactive in
helping P&G work through issues.
• ANY new service stand-up should be expected to have growing pains.
– Technical and operational “learnings” should be built into your time lines
– Commercial flexibility on BOTH sides makes life easier for all
• Overall, Oracle delivered what they said, when they said they would. The value
equation was there.
• Strong team behind the service. Talent was brought in.
• We stood up a new to our world app, exposed 150TBs of never seen before data,
that gives us new insight into the marketplace.
• Oracle is growing their ecosystem in intriguing ways. It’s no longer just about the
technology – a bigger potential is emerging.
Where Are We Going?
Summary & Futures:
• We see the potential for Big Data cloud services, as game changers.
• New data capabilities (e.g. Data as a Service emerging in the cloud) add synergy.
• New combinations of Iaas, PaaS, Saas, BPaaS from integrated providers.
• Explosion of data “outside the enterprise”.
• IoT is the offshore Tsunami headed toward Big Data land.
– Consumer devices
– Manufacturing
– Municipal
We are about to have MORE data, and MORE compute, than any time in history. We have worthy problems. We WILL have worthwhile answers.
Copyright © 2015, Oracle and/or its affiliates. All rights reserved.
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