HITACHI @ KIT

Hitachi Outlook –Digital Transformation within existing Big Data environments

Jürgen A. KrebsCTO, Central Region

August 2016

AGENDA

� Hitachi

� Market & Trends

� Hitachi Analytics Approach

� Q&A

Deep Innovation Resources

Others

Financial Services

Digital Media and Consumer Products

Automotive Systems

High Functional Materials and Components

Construction Machinery

Electronic Systems and Equipment

Social Infrastructure and Industrial Systems

Power Systems

Information and Telecommunication Systems

US$3.4BINNOVATION BUDGET

� Founded in 1910

� US$80B FY15

� 1056 subsidiaries

� 335,000 employees approx.

� #1 worldwide for patent applications in big data analysis foundation technology

� #89 in the 2015 FORTUNE® Global 500

How We Achieve Social Innovation Through Big DataMachine data is in our DNA. We think like users because we are users.

ROBOTICSI.T.INFRASTRUCTURE

AUTOMOTIVESYSTEMS

WIND TURBINES

MINING EQUIPMENTRAILWAY CONTROL SYSTEMS AND TRAINS

WEARABLESPROGRAMMABLE CONTROLS

WATER TREATMENT

BATTERY SYSTEMS

SENSORSMEDICAL IMAGINGGAS TURBINES

SOCIAL INFRASTRUCTURE PUBLIC SAFETY MEDICAL DIAGNOSTICS

IoT is the Integration of Two Worlds

Physical (OT) Digital (IT) IoT World

Internet of Things can transform businesses, industries and cities for better outcomes,

more productivity, sustainability, quality of life, …

Hitachi‘s Way to Digital Transformation

Digital TransformationTransform Customer

ExperienceMonetize customer insight.

Transform Work and Operations

Reduce costs and risk.

Transform Business Models

Innovate to compete.

AnalyticsMobilityGovernanceManagement Cloud

Workforce MobilityCompliance

Modernize IT Apps and

InfrastructureAnalytics Enterprise

Cloud

STRUCTURE

Digital TransformationUse of digital technology to enable fundamental innovation and disruption

Digital TransformationUse of digital technology to enable fundamental innovation and disruption

Management & Consumption

IT infrastructure platform to free-up IT budget and drive innovation

Management & Consumption

IT infrastructure platform to free-up IT budget and drive innovation

Data Governance & Mobility

Availability, usability, integrity, and security of enterprise data

Data Governance & Mobility

Availability, usability, integrity, and security of enterprise data

Data AnalyticsEnabling new, transformational,

business insights from isolated data silo’s

Data AnalyticsEnabling new, transformational,

business insights from isolated data silo’s

Big

C

onve

rsat

ions

Sol

uito

nP

lays

Flash Consumption Models

Sync+Share

RetentionArchive & RetentionOrchestrated

Data Protection

SAP Analytics PlatformPrivate

Cloud Oracle Object NAS

Market Outlook

NOW Still on CLOUD & Virtualisation

Big Data Analytics & In Memory

NOW Still on CLOUD & Virtualisation

Big Data Analytics & In Memory

Long Term COTS & What‘s next

>2020 Market Leading Architectures

Long Term COTS & What‘s next

>2020 Market Leading Architectures

Mid Term Software Defined on the rise

2017 - 2019 Hyper Converged & Hyperscale Platforms

Polyglot Frameworks (hadoop, Spark, Storm)

OPEX Driven Investments

Mid Term Software Defined on the rise

2017 - 2019 Hyper Converged & Hyperscale Platforms

Polyglot Frameworks (hadoop, Spark, Storm)

OPEX Driven Investments

The New Role of IT

FAST AGILE SECURE

PROVIDE I.T. AS-A-SERVICE

KNOWLEDGE ADVISORINTEGRATED

BUSINESS INSIGHT

INTEGRATED BUSINESS INSIGHT

I.T.I.T. O.T.O.T.

INTEGRATED ANALYSIS

INTEGRATED ANALYSIS

INTEGRATED EXPERTISE

INTEGRATED EXPERTISE

DATA BROKER & SERVICE PROVIDER

DATA MOBILITY

DATA MOBILITY ANY TYPE ANY SITE

GAP

WHAT HINDERS DIGITAL TRANSFORMATION?

NetworkNetwork

StorageStorage

ServerServer

Virtual MachineVirtual Machine

Operating SystemOperating System

Database

Middleware

Application

I.T. PARADIGMBUSINESS PARADIGM

DIGITAL TRANSFORMATIONDIGITAL TRANSFORMATIONRETHINK

OPERATIONS AND

PROCESSES

Accelerate cost efficiency and time to market

IMPROVE CUSTOMER

EXPERIENCE

Increase loyalty and

grow revenue

ADOPT NEW BUSINESS MODELS

Unlock new revenue

streams and reach new markets

The Next Revolution

� Big Data spending growth 30%. IT budget spending for analytic tools and apps

� Big Data intensive apps 80% of new cloud apps will be big data intense.

� Big Data Rich services . Value-added content providers will drive developers activity

� Industry Platforms to disrupt 6 of the top 20 market leaders in most industries

Responsibility for Managing the Complexity of IT is Shifting from the Customer to the Vendor

IT ComplexityIT Complexity

Bus

ines

s N

eeds

Bus

ines

s N

eeds

IT Complexity

Bus

ines

s N

eeds Business

Expectations

IT Ability to Respond

Move From the “How” to the “What”

• There is an increasing gap as technology vendors continue to add features and complexity to their products faster than customer are able to adopt the rate of change

• IT is shifting its focus from building and maintaining systems to delivering an outcome to the business processes of their enterprise

• Customers need to move from “How” a product can be used for cloud to “What” cloud solution the business needs

HDS3

Folie 12

HDS3 consumption gapHitachi Data Systems; 22.02.2016

Is IT a Cost Center or an Innovation Center?

“If the CIO focuses on IT as a cost center and his goal is to reduce infrastructure cost without increasing busin ess value , then he should turn IT over to the finance department.”

Are CIO’s Becoming Extinct?Hubert Yoshida Blog 23 Nov 2015 - Hu’s Place

Lead Business Transformationor Become Irrelevant

Understanding the Digital Enterprise

Digital Startup Digital Enterprise

Market OpportunityMarket OpportunityNew Services to Existing Customer BaseOptimize existing assets and maximize

return on intellectual propertyDeliver business value from historical

customer data, Build on brand

First to marketDefine new market segment

Application LandscapeApplication Landscape

Modern, cloud-ready applicationsRun everything in the public cloud

No legacy development debtLittle historical customer data

Mix of traditional and cloud-ready apps Consume blend of public cloud and

private to deliver differentiated servicesHistorical customer data is an asset

Storage

Storage As A Service

How can I run diverse workloads on one integrated platform?

UNIFIED COMPUTE PLATFORM DIRECTOR REST API and CLI

ComputeConnectivity

Compute As A ServiceNetwork As A Service

RESOURCE PARTITION #1

Hypervisor: VMware / Hyper-V

Bare Metal Windows & Linux

Windows & Linux VMsBare Metal Docker +

Kubernetes

Storage(Dedicated to UCP or Use Existing Assets)

Res

ourc

e P

artit

ion

# 1

Sto

rage

for

Lega

cy S

erve

rs

Res

ourc

e P

artit

ion

# 2

File

Ser

vice

s

Res

ourc

e P

artit

ion

# 3

Con

tent

and

Arc

hive

Ser

vice

s

Storage As A Service

Infrastructure as a Service

Containers

DB Server Web ServerMiddleware

AppDev ToolsAppDev ToolsAdvanced App AutomationAdvanced App Automation CookbooksCookbooks

Platform as a Service

Cloud Native AppsConventional Apps

DevOps & CI / CD ToolsDevOps & CI / CD Tools

Containers

Hitachi R&D

2100+ Labs Researchers Worldwide

Mining Optimization

Power Grid OptimizationImage SearchTraffic Analysis

Augmented RealityFacial Recognition

Oil Field Analysis

Robotics

People Flow Analysis

Object Recognition

Human Behavior Analysis

The Analytics and Data RevolutionBigger and Better Insight Drives Bigger and Better Outcomes

DA

TA E

VO

LUT

ION

ANALYTICS EVOLUTION

TRANSACTIONAL (TX)FINANCIAL APPS, BUSINESS APPS

HUMANEMPLOYEES, CUSTOMERS…

THINGSINDUSTRIAL/SOCIAL INFRASTRUCTURE, MOBILE DEVICES….

THE PASTWHAT HAPPENED ?

BI AND REPORTING

THE PRESENTWHAT’S HAPPENING NOW ?

REAL TIME

THE FUTUREWHAT WILL HAPPEN ?

PREDICTIVE

CONTROL FUTUREWHAT SHOULD WE DO ?

PRESCRIPTIVE

Why is this a Big Data approach?

� Complexity with traditional tools generates a “Big” problem

� Not being solved with standard BI/ETL tools(Business Intelligence Extract Transfer Load)

� Understand and appreciate the challenges

Big Data or Big Problem?

The HDS Big Picture for Big Data (and IoT)

Data Lake

PDI

PDI

PDI

PDI

Enterprise Hyper-Converged Scale-Out

PDI in KVMs

� Archive� Regulatory

Compliance

� Analytics� Hadoop/Spark� NoSQL� Elastic Search

PBA

City Data eXchangeCity Data eXchange

CityAdmin

Copenhagen’s SmartCity Data Marketplace delivered by Hitachi

Mobility

"Green and ComfortableTransportation"

"Lower energy consumption"

- City of bikes- Mobility Management- Copenhagen Connecting

- Buildings- Transport- Street Lighting

Energy

"Carbon-neutral city"- Smart meter by 2020- Wind turbines- Biomass in power plant

Carbon Neutrality by 2025Carbon Neutrality by 2025

Data Suppliers Data Consumers

CDX (Data marketplace)City Open Data | Transportation | Parking | Sensor

Data | Energy Data | Water Usage Data | Event Data

| Weather / Environmental | Social Media | Citizens

City Departments | Retailers | Property Development |

Property Management | Transportation and Parking |

Insurance | Application Developers | Consulting Firms

Providing Data Marketplace to enable

integration of SmartCity data from/to Businesses/Citizens and City Government

Explore Data

Consumer Data

Supply Data

Enable the community

to Build Services

Public Data Sources

Private Data Sources

CDX City Data eXchange Toolkit –Data Explorer/Consumer

3rd Party Applications / Services

CitizensCity GovernmentCompanies

Industrial IoT: Two Example Use Cases

Schedule Optimization

Problem: bottlenecks, poor OEE

Solution: multi-variate analysis of scheduling constraints

Insight: optimal order schedule

Actions: dynamic scheduling

Outcomes: 10-20% increasedoperating efficiency, increasedcapacity, higher utilization

Quality Optimization

Problem: poor, inconsistent yields

Solution: multi-variate analysis of key factors driving output quality

Insight: optimal process inputs

Actions: dynamic process control

Outcomes: 30-60% reduction of poor quality, increased capacity, reduced scrap and re-work

Industrial IoT: Real-World Innovation

Schedule Optimization

Hitachi’s Omika factory reduced inventory by 14%, operating costs by 30% with dynamic scheduling optimization enabled by sensors, cameras, and advanced analytics.

A Hitachi distribution centre was able to increase efficiency by 8% through dynamic scheduling, by combining disparate data bases to perform advanced analytics.

Quality Optimization

A maker of high-performance polymer products was able to reduce poor process yields by over 50% through advancedstatistical analysis of processes.

A pharmaceutical manufacturer was able to overcome instabilityof biological ingredients throughadvanced process analytics, to sustain higher production yields.

AI-Based LEGO Robot on a Swing

Hitachi AI Technology

H

Control

Monitoring System Configuration LEGO Mindstorms (EV3) × Hitachi AI-H

Sensor: > Gyro & Knee Status

Control: > Stand/Sit Timing

Outcome: > Swing Amplitude

Learns from data, adaptively grows, and gets the results

• Outcome “Amplitude” & in/out defined by humans

• Without input of swing knowledge nor logic

• Added-on to existing LEGO system

AI-Based LEGO Robot on a Swing - Demonstration

No Human-Hypothesis / Logic Needed

• No Supervising Data Needed (cf. Supervised Learning)• No Reward Logic Needed (cf. Reinforcement Learning)• No Massive Data Injection Needed (cf. Deep Learning)

5 © Hitachi, Ltd. 2016. All rights reserved.

Lumada IoT Core

Edge AnalyticsAnalytics & Simulation

Monitoring, SecurityVisualizationData Blending

IoT Solution Services

IoT ConnectivityHuman DataHuman Data

Video, image, audio and social media

Business DataBusiness DataEmail, docs, and structured data

Machine DataMachine DataRFID, sensors, and

machine logs

SMARTCITY

SMARTCITY

SMART INDUSTRY

SMART INDUSTRY

SMART ENERGYSMART

ENERGYSMART

HEALTHCARESMART

HEALTHCARE

OT IT

Hitachi’s Solution Strategy

What is the best place to store and manage my data?

VSPG1000 HCPHSP

CPU STRNET

CPU STRNET

CPU STRNET

CPU STRNET

CPU STRNET

CPU STRNET

CPU STRNET

SPINE

CPU STRNET

CPU STRNET

CPU STRNET

CPU STRNET

CPU STRNET

CPU STRNET

CPU STRNET

SPINE

METADATA

MANAGEMENT

CLUSTER

METADATA

MANAGEMENT

CLUSTER

POOLED STORAGE

ERASURECODED

SEARCH MOBILITY

EMBEDDED

LOW LATENCY MISSION CRITICALIn memory / transactional

applicationsVM’s and Bare Metall / LPARs

ON-DEMAND IT

GENERAL PURPOSE, DEVOPS

& ANALYTICSContainers, OpenStack,

LAMP, Hadoop, MapR, Spark,

Cassandra

POINT APPLICATION

ACCELERATIONVDI, Low Latency

DB, Custom Application

ARCHIVE & BACKUP

CLOUD & MOBILITYSearch, Meta-data driven,

Hybrid Cloud: Public/Private Brokerage -transparent and controlled

DATA LAKE

VSPGx00 HPPVSPFx00HFS

STORAGE APPLIANCE

CONSISTENT DATA SERVICES (SVOS)

NEARLINEBackup, Long-term retention

MORE APPLIANCE-LIKE MORE FLEXIBILITY

What is the best place to run my application?

UCP2000/4000/6000

HCPHSP

COMPUTE

NETWORK

UNIFIEDSTORAGE

CPU STRNET

CPU STRNET

CPU STRNET

CPU STRNET

CPU STRNET

CPU STRNET

CPU STRNET

SPINE

CPU STRNET

CPU STRNET

CPU STRNET

CPU STRNET

CPU STRNET

CPU STRNET

CPU STRNET

SPINE METADATA

MANAGEMENT

CLUSTER

METADATA

MANAGEMENT

CLUSTER

POOLED STORAGE

ERASURECODED

SEARCH MOBILITY

OR

CH

ES

TR

AT

ED

OR

CH

ES

TR

AT

ED

AU

TO

MA

TE

D

CONVERGED

LOW LATENCY MISSION CRITICALIn memory / transactional

applicationsVM’s and Bare Metall /

LPARs

UCP1000

HYPER-CONVERGED

GENERAL PURPOSE, DEVOPS & ANALYTICS

Containers, OpenStack, LAMP, Hadoop,

MapR, Spark, Cassandra

BRANCH, CLOUD-READY APPSVDI, Tier 2 VMs, Distributred

Embedded Small DBs

OBJECT

CLOUD & MOBILITYSearch, Meta-data driven, Hybrid Cloud: Public/Private Brokerage -

transparent and controlled

Accelerate the Shift to Self Service

Hitachi Content Platform Anywhere

Sync-n-Share

Content Mobility

Role-Based, Self-Service Catalogs

Application

Automated, App-Based Provisioning

Virtual Storage Platform

LOB Cloud

Bare Metal

Cloud Infrastructure Provisioning

HitachiCloud Automation Suite

„Wir blicken so gern in die Zukunft, weil wir das Ungefähre, was sich in ihr hin und her bewegt, durch stille Wünsche so gern in der Gegenwart zu unseren Gunsten heranleiten möchten.

Frei nachJohann Wolfgang von Goethe(1749 - 1832), deutscher Dichter der Klassik, Naturwissenschaftler und Staatsmann

Thank You

Questions and Discussion