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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