Advancing Real-timeBIG DATA analytics solutions

ON the Intel® Xeon® processor E7 v4 familyCarmine Stragapede

D i r e t t o r e G e n e r a l e

I n t e l C o r p o r a t i o n I t a l i a S p A

@ C a r m i n e S t r a g a

The New center of possibility

A BIG DATA EXAMPLE

HANDLE 10 GB of raw data every 15 minutes

ANALYSE AND STREAM LIVE A DASHBOARD REPORT

INGEST 4MILLIONS OF DATA ROWS IN A SECOND

a n a l y t i c sI S U B I Q U I T O U S

M a r k e t i n g

S a l e s B a n k i n g

I n s u r a n c e

R e t a i l

E n e r g y

T e l e c o m

I o T

M a n u f a c t u r i n g

T r a n s p o r t

BIG DATA: Big Drivers for Big Profits

MONETIZATION:

COST CONTROL: HW/SW Platform, Usability & Learning Efforts

New Revenue Streams Generation & Loss Prevention

SOME BIG DATA SW PLATFORM WISHES

SINGLE DATA STORAGE POINT

DISTRIBUTED REAL TIME DATA COLLECTION

ENDLESS DATA ANALISYS, REPORTING AND visual rendering

MORE, BIG DATA SW PLATFORM WISHES

Online multiple domains data correlation

EXPLORATION OF HUGE DATA SETS

LIVE DASHBOARDS

Structured

Poly Structured / Unstructured

Batch

Real-Time

RDBMS, SQL

Scalable Streaming

Scalable No SQL

In-MemoryDescriptive Analytics

Diagnostic Analytics

Predictive Analytics

Prescriptive Analytics

Cognitive Analytics

Machine Learning

HPC

Business Intelligence

Analytics approaches abound

Hadoop

Deep Learning

Libraries

Graph-DB

Visualization

IoT

analytics is creating advantage

Education technology provider TeacherMatch uses data analytics

to streamline teacher hiring by predicting the likely classroom

effectiveness and impact on student growth of prospective

teachers

Spain’s leading bank, CaixaBank, uses big data analytics to adapt

and improve communication with their customers and offer

products and services that better

meet customer needs

Apparel company Levi Strauss & Co.

uses analytics to improve the in-store experience by making sure customers and sales-people can

find the products they need, when they need them

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

Companies that use data analytics are12X more l ikely to have

top-quart i le f inancial performance 5X more l ikely to make

decis ions faster than their competit ion

1. Source: Gartner, Survey Analysis: Practical Challenges Mount as Big Data Moves to Mainstream, September 2015

Expensive & slow to get actionable insights

Data is too hard to connect, secure & use

Complicated Analytics solution stacks

barriers to adoption

Reduce time & cost to get actionable insightsIntel offers a complete, cost-effective

technology portfolio to address diverse analytics needs.

Tackling barriers to adoption

Break down data siloes and obstacles

Create Easier-to-use Analytics solution stacksIntel is investing deeply in the software and

solutions ecosystem to make analytics easier for IT to deploy and use efficiently.

Intel is collaborating closely with industry leaders to break down data barriers and

expose the power of analytics

softwareoptimization

Intel capitalinvestments

Open Source Contributions

Improving usability

Open Network Insight

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

Tackling analytics challenges:

Breaking down data barriers

Trust & Access ControlC r e a t i n g a s e c u r e ,

s h a r e d c l o u d a n a l y t i c s s y s t e m t o i m p r o v e c a n c e r d i a g n o s i s &

t r e a t m e n t

Multiple data SourcesC r e a t i n g a m u l t i - n o d e

c l o u d s y s t e m t o a n a l y z e d a t a a b o u t

s e p s i s r i s k f r o m m u l t i p l e s o u r c e s

Ease of deploymentU s i n g o p e n s o u r c e

s o l u t i o n s t o d e p l o y p o w e r f u l e l e c t r i c a l g r i d

a n a l y t i c s t o o l s m o r e r a p i d l y , t o m o r e u s e r s

PARTNERING TO CREATE MODELS FOR COMPLEX DATA CHALLENGES

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

Tackling analytics challenges:

Scale OutLargest data sets

Hadoop, Spark, HPC, High-performance Data Analytics, Modeling & Simulation,Machine/Deep Learning

Intel® Xeon® Processor E5 Family

Intel® Xeon® Processor E7 Family

Intel® Xeon® Phi™ Products

Powering all analytics workloads

Scale UpLargest

in-memoryReal-Time Analytics

…plus FGPA for algorithm speed up for targeted analytics workloads

Tackling analytics challenges:

Scale-up: Real-time analytics is growing

A n a l y z i n g t r a n s a c t i o n s f o r r e a l - t i m e

f r a u d d e t e c t i o n

A n a l y z i n g & r e s p o n d i n g t o

e l e c t r i c a l u s a g e i n r e a l - t i m e

R e a l - t i m e m o n i t o r i n g o f

t r a f f i c f o r r o u t e o p t i m i z a t i o n

A n a l y z i n g n e t w o r k t r a f f i c i n r e a l t i m e t o p r o v i d e o p t i m a l q u a l i t y o f s e r v i c e

banking Electric grid transportation telecom

As a leading Italian rail transport operator, Trenitalia carries 2 million long distance and commuter passengers a day – and unexpected maintenance not only costs money, but can cause frustrating delays for passengers.

Trenitalia implemented a condition-based maintenance (CBM) strategy powered by SAP HANA + the Intel® Xeon® processor E7 family, analyzing data coming from thousands of on-board sensors in real-time.

The solution helped Trenitalia reduce maintenance costs by an estimated 8-10%, improve processes and offer a better customer experience.

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

Goal:

Solution:

Impact:

“ With real-time insights into what’s happening on our rail lines, we’re able to save up to 130M Euro in maintenance costs each year, and deliver a better, more predictable experience for our customers.”

Marco Caposciutti, Head of Technical Division, Trenitalia

INTEL® XEON® PROCESSOR E7 v4 FamilyScalable

Performance

2X more analytics queries£

v s . t h e p r e v i o u s g e n e r a t i o n

support for up to 64 sockets ¥

Up to

Advanced Reliability

Intel® Run Sure

Technologysystem uptime

application availabilitydata integrity

Industry-Leadingmemory capacity

Up to

24TB memory support¤

2X the previous generation

real-t ime analyt ics

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. Configurations: See Appendix I. For more complete information about performance and benchmark results, visit www.intel.com/E7v4records.

real-time BIG DATA analytics IS A NEED ACROSS ALL MARKETS

NEED FOR DATA SCIENTISTS AND VERTICAL MARKETS EXPERTISE

INTEL IS ENABLING OPEN BIG DATA computing PLATFORMS