Data Center Group

Dr. Heiner Genzken, Intel Deutschland GmbHHannover, den 13. 6. 2018

Data Center Group

Insight From Data = The New Competitive Advantage

Source: Gartner 2017 survey of 2,500 CIOs.

If you woke up as an industrial company today, you will wake up as a software and

analytics company tomorrow.—Jeff Immelt, CEO, General Electric

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Data Center Group

AI Adoption in the Enterprise is Just Beginning

Source: Forrester Research – Artificial Intelligence: Fact, Fiction. How Enterprises Can Crush It; What’s Possible for Enterprises in 2017

58%of business and technology professionals said they're researching AI, but only…12%said they are currently

using AI systems.

In a recent Forrester Research survey…

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Data Center Group

Enterprise Analytics and Data Priorities

AccelerateInsights

Tame the Data Deluge

EnableEnterprise AI

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Data Center Group

Enterprise Analytics and Data Priorities

AccelerateInsights

Tame the Data Deluge

EnableEnterprise AI

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Data Center Group

Source: Seagate “Data Age 2025” July 2017Forbes Magazine: 20 Mind-Boggling Facts Every Business Leader Must Reflect On Now (Nov 1, 2015); ; Inside BigData: Exponential Growth of Data (Feb 16, 2017)

Yet less than 1% of all data

is ever analyzed and used

World’s data will grow10Xin 10 years

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Data Center Group

Applications

Modern Data Management Infrastructure

Data Hub Model Often Complements Existing Storage Architecture

Traditional Data Warehousing Model

Latency: Hours to Weeks

Multiple Data Sources

ODS ETL DW Analytics

Emerging Data Hub ModelAnalytic Tools

ApplicationsApplicationsApplications Self-Service Analytics Platform

Any Data Source

DW

Real Time

DW

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Scale-OutData Hub(s)

OLTP

ApplicationsApplicationsApplications

Data Center Group

Cost Delay MORELESSHIGHERLOWER

Intel® Optane™

Technology

High Performance Low Latency

Intel® 3D NAND

Technology

Low CostHigh Density

Intel® Technology Innovations Fill the Memory and Storage Gaps Match data to the right media for every enterprise need

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Data Center Group

Intel® Optane™ SSD DC P4800X

Software and workloads used in performance tests may have been optimized for performance only on Intel microprocessors. Performance tests, such as SYSmark and MobileMark, are measured using specific computer systems, components, software, operations and functions. Any change to any of those factors may cause the results to vary. You should consult other information and performance tests to assist you in fully evaluating your contemplated purchases, including the performance of that product when combined with other products. For more complete information, visit http://www.intel.com/performance. 1 See Notices and Disclaimers slide for detailed test configurations.*Other names and brands may be claimed as the property of others.

Breakthrough Performance

Predictably Fast Service

Responsive Under Load

UltraEndurance

Scale Workload and Reduce Cost on

MySQL* vs NAND SSDUp to10x

more transactions per second @ same service¹

Up to91%

lower cost per transaction¹

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Data Center Group

Enterprise Analytics and Data Priorities

AccelerateInsights

Tame the Data Deluge

EnableEnterprise AI

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Data Center Group

Intel’s Role in Accelerating Analytics & AIHolistic Strategy from Edge-Cloud to the Enterprise

¥Note: Intel® Data Analytics Acceleration Library, Intel® Math Kernel Library, Intel® Math Kernel Library for Deep Neural Networks, Intel® Machine Learning Scaling Library, BigDL: Distributed Deep Learning on Apache Spark*, MLib: Apache Spark’s Scalable Machine Learning Library*Other names and brands may be claimed as the property of others.

Co-OptimizingApplications

Optimized Libraries Intel® MKL¥ Intel® MKL-DNN¥ Intel® MLSL¥Intel® DAAL¥Intel® Distribution for Python*

Intel® Nervana™ GraphMovidius MvTensor LibraryMLib* BigDL

Open SourceEnabling

HARDWARE/SOFTWARE Networking

Lake Crest

Compute Memory & Storage Artificial Intelligence

Dedicated Solutions

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Data Center Group

Intel® Xeon® Scalable Processors Accelerating analytics across all usage models

Results have been estimated based on internal Intel analysis and are provided for informational purposes only. Any difference in system hardware or software design or configuration may affect actual performance. Software and workloads used in performance tests may have been optimized for performance only on Intel microprocessors. Performance tests, such as SYSmark and MobileMark, are measured using specific computer systems, components, software, operations and functions. Any change to any of those factors may cause the results to vary. You should consult other information and performance tests to assist you in fully evaluating your contemplated purchases, including the performance of that product when combined with other products. For more information go to http://www.intel.com/performance/data center. See Notices and Disclaimers slide for detailed test configurations.

Up to1.79X²

Up to2x²

Up to1.59X³

higher TPSvs previous generation

Intel® Xeon® processor E7-8890 v4

faster across large, complex data sets vs previous generation

Intel® Xeon® processor E5-2699 v4

more analytic queries per minute vs previous generation

Intel® Xeon® processor E5-2699 v4

TPCx-BigBench*

Large In-MemoryScale-Up Analytics

Largest Data SetsScale-Out Analytics

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Data Center Group

Customer Segmentation

Source: Doubling Down on Entertainment Marketing with Intel ® Processors

Results: Reduces processing time from six hours to 45 minutes, Expands capacity to more than 3 million records processed per hour, Enables fine-grained segmentation to improve marketing results.

Client: Caesars Entertainment

Challenge: Improve customer segmentation. Expand analysis to include unstructured and semi-structured data. Accelerate processing for analytics and marketing campaign.

Solution: Implement a new environment using Cloudera* Enterprise (Hadoop* cluster) running on the Intel® Xeon® Processor.

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Data Center Group

Enterprise Analytics and Data Priorities

AccelerateInsights

Tame the Data Deluge

EnableEnterprise AI

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Data Center Group

Intel Enabling End-to-End Artificial Intelligence

All products, computer systems, dates, and figures specified are preliminary based on current expectations, and are subject to change without notice

Data centerMany-to-many hyperscale for stream and massive batch data processing

Gateway1-to-many with majority streaming data

from devices

Edge1-to-1 devices with lower power and

often UX requirements

Ethernet & Wireless

Wireless and non-IP wired protocols Secure

High throughput Real-time

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Data Center Group

Analytics and AI Use Cases Span Industries

And other emerging usages…

Fraud DetectionCustomer 360/Location-based Contextual Experiences Cybersecurity Speech Recognition/Chat Bots

Algorithmic/HF TradingRobo-Advisors/Wealth Management Image/Face Recognition Usage-based Insurance

Precision Medicine/Research Smart Metering Autonomous Cars Catastrophe Modeling

Predictive Maintenance Supply Chain Optimization Crime Prevention/Public Safety Crop Health Monitoring

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Together we

Invent the Future