INVENTING THE FUTURE HITACHI DATA SYSTEMS BIG DATA ROADMAP MICHAEL HAY

Transcription

1 INVENTING THE FUTURE HITACHI DATA SYSTEMS BIG DATA ROADMAP MICHAEL HAY CTO AND VP, GLOBAL SOLUTIONS STRATEGY AND DEVELOPMENT CHIEF ENGINEER, INTEGRATED PLATFORM ITPD

2 WEBTECH EDUCATIONAL SERIES INVENTING THE FUTURE: HDS BIG DATA ROADMAP As more companies grow their business in global markets, they discover the need to capture new opportunities in a matter of days rather than months to have competitive advantage and to capture new market share. Their machines are producing terabytes of various data types video, audio, Microsoft SharePoint, sensor data, Microsoft Excel files and leaders are searching for the right technologies to capture this data and help provide a better understanding of their business. The HDS big data product roadmap will help customers build a big data enterprise plan that ingests data faster and correlate meaningful data sets to create intelligence that s easy to consume and helps leaders make the right business decisions. Join this webcast to learn about Hitachi s product roadmap to big data.

3 DEEP INNOVATION RESOURCES Founded in 1910 US$118B FY subsidiaries 324,000 employees More than 760 PhDs INNOVATION BUDGET #38 in the 2012 FORTUNE Global 500

4 2003 HITACHI DATA SYTEMS (HDS) PORTFOLIO

5 OUR JOURNEY 2013 SOLUTIONS DRAG SOFTWARE ACCELERATION SOLUTIONS Acquisitions of BlueArc, Cofio Launch of verticals SOFTWARE DRAGS HARDWARE FILE AND CONTENT VIRTUALIZATION 2009 Redesign of midrange hardware, packaged as solution IMPROVED SOFTWARE 2007 Acquisition of Archivas for content software HDS WAS A STORAGE HARDWARE VENDOR COMPETING ON PRICE 2003 Redesigned and expanded software suite

6 HDS INTEGRATED STRATEGY INFORMATION Analytics Integration Information Virtualization Integrated Information-as-aservice CONTENT Search, discover, repurpose Link to vertical/si markets Content-on-demand Text Archiving-as-a-service INFRASTRUCTURE Virtualization, mobility Integrated management Data center convergence Content Virtualization Infrastructure and platform-as-a-service Data, Storage, File, Server, Network Virtualization HIGHER VALUE HIGHER MARGIN HIGHER STICKINESS Infrastructure Converged solution stacks Rapid and on-demand provisioning and deployment Data Intelligence Data lifecycle management Index, search, and discover independent of application Information Analytics Data reuse for new business Data analytics independent of application and media

7 BIG DATA OPPORTUNITY IS EVERYWHERE Every industry, every geo, companies big and small Sentiment Analysis Risk Analysis Churn Analysis Fraud Detection Network Monitoring One to One Marketing Geomation Farming Location-Based Advertising Oil Exploration Satellite Images Asset Tracking On-Demand Maintenance Traffic Flow Optimization Seismic Monitoring Life Sciences Research

8 OUR PORTFOLIO UCP DIRECTOR INSTANCE MGMT. COMMAND SUITE UNIFIED COMPUTE PLATFORM PRO SYSTEMS MANAGEMENT INFRASTRUCTURE UCP SELECT UCP for SAP HANA UCP for Oracle UCP for MS Exchange UCP for MS SQL UCP for VMware Etc. COMPUTE PLATFORMS IP AND STORAGE NETWORKING CONTENT SEARCH HDDS SMART INGEST HDI HDD-MS CLOUD/OBJECT HCP NAS/FILE HNAS BLOCK/UNIFED STORAGE PLATFORMS

9 OVERALL HITACHI VISION AND STRATEGY FOR BIG DATA BIG DATA JOURNEY Market Requirements: Mainstream Use Cases Managing data growth Metadata driven content Image, audio, video analytics High performance DB analytics analysis Data science mainstream Extending traditional analytics with Hadoop Machine data Real time adoption Complex data mashups Hitachi Portfolio Infrastructure layer Big Data ISV ecosystem Content layer Smart ingest (e.g. JDSU, HDI) UCP for SAP HANA UCP for Oracle, Microsoft Vertical solutions Hitachi Clinical Repository Expanded Big Data services Big Data services Scale-out architectures Hadoop ref. architecture Social innovation Rich media analytics Advanced analytics orchestration Expanded vertical solutions TODAY EVOLVING TOMORROW

10 TRENDS AND PORTFOLIO DIRECTIONS

11 THE EXA-SCALE ERA IS ON ITS WAY We are planning for 100EB systems by Advanced Customer

12 THE TECH GOLDFISH BOWL THEORY In economics, Jevons paradox (sometimes Jevons effect) is the proposition that technological progress that increases the efficiency with which a resource is used tends to increase (rather than decrease) the rate of consumption of that resource. Seems counter to rational thinking, yet if you look at human behavior we tend not to delete anything. With all of that data now available, there is a movement contemplating how to transform unused data into an appreciating asset: Big Data! The Hadoop people are right, but not in the way they think.

13 HDDS/Search WIDE AREA DATA SERVICES PLATFORM SMART INGEST SMART INGEST Hitachi Data Ingestor Hitachi Data Ingestor private APPLICATIONS SMART INGESTION f public Object Store Apps & Ingestors SITE 2 Hitachi Content Platform 3 rd Party NFS File Server metadata warehousing Hitachi Network Attached Storage Scale- Up NAS SITE 1 Hitachi Content Platform Object Store private Hitachi Network Attached Storage Scale-Up NAS Apps & Ingestors SITE 3

14 Customer OR Common ESM stack systems management THE EVOLUTION OF THE STACK today Future DIY RACK application os/vm Converged Stacks/Offerings RACK RACK RACK RESTful GUI CLI Beyond Converged RACK compute network storage CONSOLIDATED CONSOLIDATED CENTRALIZED

15 BUT WHY TAKE THIS APPROACH?

16 HITACHI BIG DATA DRIVES BIG INNOVATION THE FUTURE OF BIG DATA Machine data is in our DNA We think more like users

17 BIG DATA DRIVES BIG INNOVATION TODAY Hitachi Transportation Bullet Trains Demand based maintenance Early warning improves safety More efficient asset utilization Hitachi Power Power Stations Telemetry from seismic sensors Efficient capture of time series data Hitachi Construction Excavators Operational data from sensors Insight for fleet managers Competitive differentiation

18 RELEVANT TECHNOLOGIES RELEVANT TECHNOLOGIES BIG DATA ANALYTICS VARIETY DOMINATES

19 BIG DATA ANALYTICS ARCHITECTURES MODERN 3-TIER APPLICATION COMPONENTS FOR FUTURE BIG DATA, ANALYTICS APPS presentation search kvs visualization Complex event processing application dwh analytic studio Extract, Transform, Load hive database many more Graph database machine learning

20 ANALYTICS ORCHESTRATION AND THE ANALYTICS STUDIO The Analytics Studio VISION (A Visio-like interface for humans to create complex multi-step analytics processes and applications.) + Analytics Orchestration VISION (Machine readable documents to auto-deploy multi-step analytics applications) UCP Orchestration Resource management (e.g. provisioning)

21 DECISION ASSISTS USING EVENT PROCESSING GOAL: Help brokers recommend to clients buy/sell decisions based upon corporate social sentiment IMPLEMENTATION: Multiple technologies orchestrated in vsphere

22 FOOD FOR THOUGHT

23 IN-MEMORY PREDICTIVE ANALYTICS FOR TELCO ENVIRONMENTS Granular views into network, content and subscriber experience Move from reactive to predictive problem management The combination of JDSU PacketPortal and Hitachi streaming data platform Leverage Big Data class technologies for penetrating insight

24 BUSINESS MICROSCOPE A home improvement store was evaluated using a human attached sensor platform and in-store sensors Resulted in increased revenues after observations and reconfiguration of staff Facial matching techniques derived from EMIEW2 from CCTV feeds could replace/augment sensor platforms

25 EMIEW2 APPLIED AUDIO AND VISUAL OBJECT RECOGNITION EMIEW2 developed as part of Hitachi's efforts to create a service robot with diverse communication functions that could safely coexist with humans. The new iteration combines research being explored for Hitachi content and information layers to illustrate these technologies in action. EMIEW2 uses both visual object detection and recognition to identify and find objects.

26 QUESTIONS AND DISCUSSION

27 UPCOMING WEBTECHS Cloud/Object Store Hitachi Cloud Strategy, Enabling Technologies, and Solutions, Part 1, May 21, 9 a.m. PT, noon ET Environmental Pressures are Driving an Evolution in File Storage, Part 2, May 23, 9 a.m. PT, noon ET Big Data Webcast Series continues Hitachi Data Systems Hadoop Reference Architecture, June 12, 9 a.m. PT, noon ET Check for: Links to the recording, the presentation and Q&A (available next week) Schedule and registration for upcoming WebTech sessions

28 THANK YOU