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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. View this webcast to learn about Hitachi’s product roadmap to big data. For more information on HDS Big Data Solutions please visit: http://www.hds.com/solutions/it-strategies/big-data/?WT.ac=us_mg_sol_bigdat
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INVENTING THE FUTURE HITACHI DATA SYSTEMS BIG DATA ROADMAP
MICHAEL HAY CTO AND VP, GLOBAL SOLUTIONS STRATEGY AND DEVELOPMENT CHIEF ENGINEER, INTEGRATED PLATFORM STRATEGY @ ITPD
© 2012 & 2013 , Hitachi Data Systems,
Corp. & Hitachi Ltd. All rights reserved
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.
INVENTING THE FUTURE: HDS BIG DATA ROADMAP
WEBTECH EDUCATIONAL SERIES
DEEP INNOVATION RESOURCES
INNOVATION BUDGET
Founded in 1910
US$118B FY11
900 subsidiaries
324,000 employees
More than 760 PhDs
#38 in the 2012 FORTUNE® Global 500
2003 HITACHI DATA SYTEMS (HDS) PORTFOLIO
OUR JOURNEY
HDS WAS A STORAGE
HARDWARE VENDOR
COMPETING ON PRICE Redesigned and expanded software suite
Acquisition of Archivas for content software
2011-12
2003
2007
2009 Redesign of midrange hardware,
packaged as solution
Launch of verticals
SOFTWARE
DRAGS
HARDWARE
IMPROVED SOFTWARE
VIRTUALIZATION
FILE AND CONTENT
SOLUTIONS 2010
SOLUTIONS
DRAG
SOFTWARE
Acquisitions of BlueArc,
Cofio
2013
ACCELERATION
Infrastructure
Converged solution stacks
Rapid and on-demand provisioning and deployment
HDS INTEGRATED STRATEGY
HIGHER VALUE HIGHER MARGIN HIGHER STICKINESS
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
INFORMATION
Information Virtualization
Analytics
Integration Integrated
Information-as-a-
service
Text CONTENT
Content Virtualization
Search, discover, repurpose
Link to vertical/SI markets
Content-on-demand
Archiving-as-a-service
INFRASTRUCTURE
Data, Storage, File, Server, Network Virtualization
Virtualization, mobility
Integrated management
Data center convergence
Infrastructure and
platform-as-a-service
Life Sciences
Research
Location-Based
Advertising
One to One
Marketing
On-Demand
Maintenance
Satellite
Images
Every industry, every geo, companies big and small
BIG DATA OPPORTUNITY IS EVERYWHERE
Fraud
Detection
Churn
Analysis
Risk
Analysis
Sentiment
Analysis
One to One
Marketing
Geomation
Farming
Location-Based
Advertising
Oil
Exploration
Network
Monitoring
Asset
Tracking
On-Demand
Maintenance
Traffic Flow
Optimization
Seismic
Monitoring
Satellite
Images
Fraud
Detection
Churn
Analysis
Risk
Analysis
Sentiment
Analysis
CONTENT INFRASTRUCTURE
IP AND STORAGE NETWORKING
SYSTEMS MANAGEMENT
SMART INGEST HDI | HDD-MS
COMMAND SUITE
UCP DIRECTOR
CLOUD/OBJECT HCP
UCP SELECT
NAS/FILE HNAS
SEARCH HDDS
BLOCK/UNIFED STORAGE PLATFORMS
UNIFIED COMPUTE
PLATFORM PRO
COMPUTE PLATFORMS
INSTANCE MGMT.
UCP for SAP HANA | UCP for
Oracle | UCP for MS Exchange |
UCP for MS SQL | UCP for
VMware | Etc.
OUR PORTFOLIO
BIG DATA JOURNEY
OVERALL HITACHI VISION AND STRATEGY FOR BIG DATA
Extending traditional analytics
with Hadoop
Rich media analytics
Expanded vertical solutions
Advanced analytics
orchestration
Smart ingest (e.g. JDSU, HDI)
Hadoop ref. architecture
Big Data ISV ecosystem
UCP for SAP HANA
Infrastructure layer
Content layer
UCP for Oracle, Microsoft
Hitachi Clinical Repository Expanded Big Data services
Managing data growth
High performance DB analytics
Real time
Metadata driven content
analysis
Machine data Data science mainstream
adoption
Image, audio, video analytics
Complex data mashups
TODAY EVOLVING TOMORROW
Social innovation
Vertical solutions
Market Requirements: Mainstream Use Cases
Hitachi Portfolio
Big Data services Scale-out architectures
TRENDS AND PORTFOLIO DIRECTIONS
© 2012 & 2013 , Hitachi Data Systems,
Corp. & Hitachi Ltd. All rights reserved
THE EXA-SCALE ERA IS ON ITS WAY
“We are planning for 100EB systems by 2020.” Advanced Customer
THE TECH GOLDFISH BOWL THEORY
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.
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.
WIDE AREA DATA SERVICES PLATFORM
f
private
CORE @ SITE 2
Apps & Ingestors
Object Store
Hitachi
Content
Platform
CORE @ SITE 1
HD
DS
/Se
arc
h
CORE @ SITE 3
Apps & Ingestors
Scale-Up NAS
Hitachi
Network
Attached
Storage
private
public
SMART
INGEST
Hitachi Data Ingestor
SMART INGESTION
APPLICATIONS
metadata warehousing
Object
Store
Hitachi
Content
Platform
Scale-
Up NAS
Hitachi
Network
Attached
Storage
NFS File
Server
3rd –
Party
SMART
INGEST
Hitachi Data Ingestor
CONSOLIDATED
RACK
THE EVOLUTION OF THE STACK
syste
ms m
anagem
ent
network
storage
compute
os/vm
application
DIY
today 2011-2013
Beyond Converged
2014-Future
RACK
CENTRALIZED
Converged Stacks/Offerings
RACK RACK RACK
Cu
sto
me
r O
R
Co
mm
on
ES
M s
tack
CONSOLIDATED
RESTful
GUI
CLI
BUT WHY TAKE THIS APPROACH?
© 2012 & 2013 , Hitachi Data Systems,
Corp. & Hitachi Ltd. All rights reserved
THE FUTURE OF BIG DATA
HITACHI – BIG DATA DRIVES BIG INNOVATION
Machine data is in our DNA
We think more like users
BIG DATA DRIVES BIG INNOVATION TODAY
Hitachi
Transportation
Bullet Trains
Demand based maintenance
Early warning improves
safety
More efficient asset utilization
Telemetry from seismic
sensors
Efficient capture of time
series data
Hitachi Power
Power
Stations
Operational data from
sensors
Insight for fleet managers
Competitive differentiation
Hitachi
Construction
Excavators
BIG DATA ANALYTICS – VARIETY DOMINATES
RE
LE
VA
NT
TE
CH
NO
LO
GIE
S
RE
LE
VA
NT
TE
CH
NO
LO
GIE
S
BIG DATA ANALYTICS – ARCHITECTURES
MODERN 3-TIER APPLICATION
database
application
presentation
COMPONENTS FOR FUTURE BIG DATA, ANALYTICS APPS
search
analytic studio
kvs Complex
event
processing
visualization
dwh hive
Extract,
Transform,
Load
machine learning Graph
database many more
ANALYTICS ORCHESTRATION AND THE ANALYTICS STUDIO
UCP Orchestration Resource management (e.g. provisioning)
+ Analytics Orchestration VISION (Machine readable documents to auto-deploy multi-step analytics applications)
The Analytics Studio VISION (A Visio-like interface for humans to create complex multi-step
analytics processes and applications.)
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
FOOD FOR THOUGHT
© 2012 & 2013 , Hitachi Data Systems,
Corp. & Hitachi Ltd. All rights reserved
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
IN-MEMORY PREDICTIVE ANALYTICS FOR TELCO ENVIRONMENTS
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
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.
EMIEW2 – APPLIED AUDIO AND VISUAL OBJECT RECOGNITION
QUESTIONS AND DISCUSSION
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 www.hds.com/webtech for:
Links to the recording, the presentation and Q&A (available next week)
Schedule and registration for upcoming WebTech sessions
UPCOMING WEBTECHS
THANK YOU
