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OCTOBER 18,2016 SAN FRANCISCO BAY AREA, CA #DenodoDataFest RAPID, AGILE DATA STRATEGIES For Accelerating Analytics, Cloud, and Big Data Initiatives.

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O C T O B E R 1 8 , 2 0 1 6 S A N F R A N C I S C O B A Y A R E A , C A

#DenodoDataFest

RAPID, AGILE DATA STRATEGIESFor Accelerating Analytics, Cloud, and Big Data Initiatives.

Joshua Wise, IT Enterprise Architect, Intel

October, 2016

Modern Data Architectures:

Deploying Data Virtualization at an

Enterprise Scale

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This presentation is for informational purposes only. INTEL MAKES NO WARRANTIES, EXPRESS OR IMPLIED, IN THIS SUMMARY.

Intel and the Intel logo are trademarks of Intel Corporation in the U.S. and/or other countries.

* Other names and brands may be claimed as the property of others.

Copyright © 2016, Intel Corporation. All rights reserved.

Legal Notices

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2016 Intel IT Vital Statistics>6,319 IT employees

71 global IT sites

>104,000 Intel employees1

170 Intel sites in 72 Countries

61 Data Centers(91 Data Centers in 2010)

>160,000 servers with 143PB of storage

>1,000,000 cores @ 25% YOY Growth

80% of servers virtualized

(42% virtualized in 2010)

>215,000+ Devices>50,100 handheld devices

160+ mobile applications developed

Source: Information provided by Intel IT as of Jan 20161Total employee count does not include wholly owned subsidiaries that Intel IT

does not directly support

Foundation for Data Architecture

• Intel implemented its modern ERP system in

1996 and has evolved it since

• Intel’s modern EDW implemented in 2001

• Application proliferation around stable core

Modern Challenges

• Globally distributed data across heterogeneous

tools & technologies

• Highly agile infrastructure

• SaaS adoption has skyrocketed

• IT customer expectation of lower TCO & TTM

Evolution of the Data Core at Intel

Intel’s Data Virtualization Journey

Enterprise Reusable Services

BU Specific Services

Master Data Services

Project Specific Services

Hdp.

Enterprise Data Warehouse

Other Data Sources

ERPOther

DS

API Management

User/Application Consumption

Machine to Machine Consumption

Intel began Data Virtualization journey in 2013

• 5 initial BU explores prior to IT go live

• Success with horizontal IT driven approach

Crawl, walk, run

• Initial usage focused on read-only use cases

• Evolution to full read/write

• Move to source data directly from ROOs

Governance

• Require the use of the logical data model built on

business friendly names. Exceptions only with

justification and representation.

• Building with the end consumer in mind

Project teams bring their OLTP and BI data

requirements to:

• Consume reusable views

• Build new aggregate views as required

BI Capability focuses on project requirements and

data blueprints to deliver a data foundation that

drives:

• Consolidated data bundles

• Reusable views

• Required technical capabilities and building

blocks

BI Enablement via Logical Data Warehouse

Enterprise Reusable Services

BU Specific Services

Master Data Services

Project Specific Services

Hdp.

Enterprise Data Warehouse

Other Data Sources

ERPOther

DS

API Management

User/Application Consumption

Machine to Machine Consumption

BI

Cap

ab

ility

DV as M&A Playbook Component

• Fast data integration

• Easy transformation and mapping

• Flexible output channels

A recent integration project had requirements to:

• Send acquisition worker data from the Intel HR data set with

translated and transformed values, preserving acquisition cost

centers, employee IDs and usernames and manager

information.

• Distribute new self-service entitlements to downstream

acquisition applications.

• Distribute directory identities to the acquisition directory.

• Allow for user driven reconciliation of acquisition user names.

Data Virtualization in support of M&A

M&A HR DW

MD Mapping Table

HR Data

Denodo VDP

SvcManagement DB Worker DB

HR DW

M&A Worker View

Intel Worker View

Intel Departements

Intel Worker LocationM&A Translator

Company Cd Mapping

Cost Center Mapping

M&A CC Extract

M&A Cost Ctr Detail

Intel Directory

Users

Groups

iPaaS

Worker Orchestration

ICAPP SQL DBaaS

Working Storage

24 Hour Trigger

ICAPP PaaS

ID Re concilliation

User Driven UI

DV as HR Services Layer

• Single point of entry for HR data consumption

• Scalable to on-premise and cloud data sources

• Seamless support for data source migrations

HR IT’s Worker Capability Migration:

• HR IT recently migrated and consolidated their HR

application layer and moved to consolidated data

warehouse environment.

• As an early adopter of data virtualization, HR IT was

able to easily repoint their business views/interfaces to

the new integrated views, preserving their logical layer

and preventing service disruption due to the migration.

• Data virtualization has also allowed HR IT to easily

integrate cloud applications to fill the gaps in its services

portfolio.

HR use of DV as Logical Layer

HR DW1 HR DW2 HR DW3

Worker Business View

HR DW4

Base ViewBase ViewBase ViewBase View

Int. ViewIntegrated View

HR Apps HR Apps HR Apps New HR App

HR Data Consumers

Intel’s Data Virtualization CapabilityDV at Intel

• 650 internal users trained on DV tools and capability in

2x4-hour in-house built training session.

• 16/26 logical business areas now using data

virtualization.

• 1263 distinct data services in the path to production

from 309 data sources.

• All IT targets for business adoption have been

exceeded.

Central Tenets

• Intel is focused on reuse

• Time to market is a key value proposition

• Training is required and governance is enforced

Key Learnings

• Intel IT culture is not naturally suited for reuse.

• Security, as with any middleware, must be designed in

and factored for.

• Clear guidance around DV vs other capabilities must be

agreed upon and communicated.

Standards

• Enterprise data model aligned

• SOA and ETL compliance

• Light weight governance

• API registered services

Service

• Certified ITS data handling

• Robust, HA, DR infrastructure

• Rapid fix/feature deployments

• Fast and easy connectivity

Support

• 24x7 SE support

• CE project design support

• Training, PB, Wiki, Videos

• Monthly COP meet-ups

Create Platform Engagement at All Levels

• Executive Messaging

Create critical success indicators, measure

progress to plan, communicate milestones

• Customer Messaging

Innovate your platform and capabilities,

communicate your wins and showcase your

customers

• Vendor Messaging

Influence through regular engagements,

request platform enhancements, report

internally and externally on vendor support

Influence for Growth

0

200

400

600

800

1000

2013 2014 2015 2016 2017

Growth of Data Services

Goal Actual Projected

Learn more about Intel IT’s Initiatives at

www.intel.com/IT

Sharing Intel IT Best Practices With the World

Panel

M O D E R A T E D B Y :

Joshua Wise

Enterprise Architect, Intel

Mark Eaton

Enterprise Architect, Autodesk

Arif Rajwani

Managing Partner, SimplicityBI

Ravi Shankar

Chief Marketing Officer, Denodo