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www.persistentsys.com © 2012 Persistent Systems Ltd
Feb
ruary
3, 2012
1
Technology Driving Growth
Anand Deshpande
February 3, 2012
www.persistentsys.com © 2012 Persistent Systems Ltd
Feb
ruary
3, 2012
2
Computers as we know
them are history!
www.persistentsys.com © 2012 Persistent Systems Ltd
The technologies that
drive the consumer
web are moving to the
enterprise.
Feb
ruary
3, 2012
3
s
m o b i l e
c
i
a
c l o u d
a
t
a p p s
www.persistentsys.com © 2012 Persistent Systems Ltd
Feb
ruary
3, 2012
4
How many
toothbrushes
are sold in the
world last year?
www.persistentsys.com © 2012 Persistent Systems Ltd
Feb
ruary
3, 2012
5
How many
toothbrushes
are sold in the
world last year?
Source 1: 1.2 Billion
Source 2: 3.2 Billion
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Rethinking the user …
Feb
ruary
3, 2012
6
www.persistentsys.com © 2012 Persistent Systems Ltd
Mobile devices are getting main stream in
the Enterprise
Enterprises are opening up to
‘bring your own device’ culture
Tablet is becoming the ‘device of
choice’ for enterprises
iOS and Android are a ‘must
have’ to reach end customers.
Win7 … still in the wait and
watch mode.
Application Scenarios
Mobilized legacy
applications
New Enterprise Apps that leverage mobility
Building task specific
mobile apps
Tablets
Smartphones
Hardened
Handsets
Feb
ruary
3, 2012
7
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Tablets are driving a change in the
Enterprise
Primary Device
With Tablets as the primary device,
HTML5 will be the default environment
Feb
ruary
3, 2012
8
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Apps apps everywhere!
Feb
ruary
3, 2012
9
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Proliferation and wide deployment of 4G
networks will lead to the Internet of things
10
“Soon, almost every device will have a wireless chip and it will be the driver for Machine 2 Machine communications. Certain verticals such as medical equipment will see the earliest impact of these M2M connections.”
Dan Hesse
Chief Executive
Officer
Sprint Telecom
Feb
ruary
3, 2012
www.persistentsys.com © 2012 Persistent Systems Ltd
Putting Kinect Technology to Work
Feb
ruary
3, 2012
11
www.persistentsys.com © 2012 Persistent Systems Ltd
To summarize
• Mobile devices are getting mainstream. The CIOs have to support them.
• Tablets are driving mobile deployment. HTML5 will be the de-facto UI
standard.
• Video is the new voice.
• Mobile computing will provide the network layer for sensors.
• Sensors will generate large amounts of data. Must find ways to deal
with large volumes of data.
Feb
ruary
3, 2012
12
www.persistentsys.com © 2012 Persistent Systems Ltd
Feb
ruary
3, 2012
13
Technology Driving Growth
Anand Deshpande
February 3, 2012
www.persistentsys.com © 2012 Persistent Systems Ltd
What do the users want to do when they go
on-line?
Feb
ruary
3, 2012
14
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Feb
ruary
3, 2012
www.persistentsys.com © 2012 Persistent Systems Ltd
Facebook gets 2.7 billion clicks of its "like"
button every day
Feb
ruary
3, 2012
16
www.persistentsys.com © 2012 Persistent Systems Ltd
• Facebook is an advertising company. Of its total revenues of $3.7bn in
2011, 85% came from advertising. And that is down from 98% and 95%
in the previous two years.
• The company makes $1bn in pure profit.
• Facebook has a total of 845 million monthly users and 483 million daily
users.
• Of its monthly users, half have used Facebook on their mobile. (But
there are no ads on its mobile site, so it makes no money from them.)
• The majority of its money comes from the US, but the majority of the
users are outside the country.
Facebook IPO 2012
Feb
ruary
3, 2012
17
www.persistentsys.com © 2012 Persistent Systems Ltd
• Google going IPO made $1.67 billion, Facebook is projected to be at
$10 billion.
• Facebook’s IPO will be the biggest of any tech company in history, 6x
bigger than Google’s.
• Only 3 US companies have had $10+ billion IPO’s, AT&T, GM, and Visa–
• If Facebook raises $100 billion, Mark Zuckerberg will rake in $25 billion.
That’s equal to $50 from each of his daily users.
• Even though it’s 4th in daily visitors, Facebook is 1st in ad revenue –
• More than 1 in 10 people on Earth use Facebook
Facebook IPO
Feb
ruary
3, 2012
18
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Feb
ruary
3, 2012
19
Social Networking
in the Enterprise
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virtual “gifts” representing a “pat
on the back” encourages high
performance and fosters team
spirit
eMee: Employee Engagement Portal
Feb
ruary
3, 2012
20
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the “den” creates a sense of belonging and provides an
outlet for hobby groups and shared interests
Feb
ruary
3, 2012
21
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To summarize
• Social networking caused major revolution in the Arab world.
• Consumer Social Networking has started driving commerce.
More compelling than search based advertisements.
• What we have learned from consumer social networking will move to
the enterprises.
Feb
ruary
3, 2012
22
www.persistentsys.com © 2012 Persistent Systems Ltd
Feb
ruary
3, 2012
23
Technology Driving Growth
Anand Deshpande
February 3, 2012
www.persistentsys.com © 2012 Persistent Systems Ltd
Cloud computing is the platform for next
generation of IT innovation.
Feb
ruary
3, 2012
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Feb
ruary
3, 2012
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What is driving the adoption of cloud
computing?
Economics.
Feb
ruary
3, 2012
26
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What is driving the adoption of cloud
computing?
• Illusion of infinite resources
• No up-front cost
• Fine-grained billing (e.g. hourly)
• Utility Computing: Pay-as-you-go computing
promises substantially reduced cost.
Economics.
Feb
ruary
3, 2012
27
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Unused resources
We are grossly over-provisioned
• Capacity includes:
• Computer Servers
• Storage
• Software Licenses
• Network bandwidth
• Energy
• Air Conditioning
• Rent
• Maintenance Costs
• Operator Staff
Static data center
Demand
Capacity
Time
Re
so
urc
es
Slide Credits: Berkeley RAD Lab Feb
ruary
3, 2012
28
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Heavy penalty for under-provisioning:
Poor quality of service – lost customers.
Lost revenue
Lost users
Reso
urc
es
Demand
Capacity
Time (days) 1 2 3
Reso
urc
es
Demand
Capacity
Time (days) 1 2 3
Reso
urc
es
Demand
Capacity
Time (days) 1 2 3
Slide Credits: Berkeley RAD Lab
Feb
ruary
3, 2012
29
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Ideally, want optimal provisioning of
capacity across all resources.
Static data center
Data center in the cloud
Demand
Capacity
Time
Reso
urc
es
Demand
Capacity
Time
Reso
urc
es
Slide Credits: Berkeley RAD Lab
Reso
urc
es
Demand
Capacity
Time (days) 1 2 3 Pay-per-use
business models Feb
ruary
3, 2012
30
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By operating at scale, improving utilization,
simplifying operations, standardizing, increasing
reliability, reducing energy and cooling
• hardware costs can be reduced 33-70 percent
• maintenance costs can be reduced up to 50 percent
• support costs can be reduced by as much as 33 percent
• floor space/facility costs can be reduced 33-50 percent
http://www-935.ibm.com/services/us/its/html/green-datacenter-svcs-landing.html Feb
ruary
3, 2012
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Advantages of Cloud Computing
Agility Cost Device and
Location
Independence
Scalability
Multi-tenancy Security Maintenance Metering
Feb
ruary
3, 2012
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Challenges for Cloud Computing
Privacy Compliance Legal Open source
Open standards Security Availability and
performance
Sustainability
and siting
Feb
ruary
3, 2012
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Cloud Computing: Why Now?
Business factors
• Minimal capital
expenditure
• Pay-as-you-go billing
model
Economies of Scale in
the Data Center
• Experience of operating
data centers efficiently
Technology factors
• Pervasive broadband
Internet
• Maturity in Virtualization
Technology
Clean Slate Approach
• Multi-tenancy
• Challenging the status-
quo
Business challenges will accelerate the adoption of cloud computing.
Feb
ruary
3, 2012
34
www.persistentsys.com © 2012 Persistent Systems Ltd
To summarize
• Enterprises will move to the cloud – this is inevitable.
• The speed of enterprises’ movement to the cloud will depend on the
peer group and will be driven by CEOs/CFOs comparing savings on the
balance sheets of their peers.
• This is not a technical decision.
• Unfortunately, the vendors and the eco-system to migrate to the cloud
are not entirely ready.
• The cost of migrating/running legacy systems is not accurately factored
in and will be a big impediment.
Feb
ruary
3, 2012
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www.persistentsys.com © 2012 Persistent Systems Ltd
Feb
ruary
3, 2012
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Technology Driving Growth
Anand Deshpande
February 3, 2012
www.persistentsys.com © 2012 Persistent Systems Ltd
Infrastructure is moving to the cloud … applications are next! Data will move with the applications.
Feb
ruary
3, 2012
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Data on the cloud will
enable new data-centric
business models.
Feb
ruary
3, 2012
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5 Exabytes of information was created
between the dawn of civilization
through 2003, but that much
information is now created every 2
days, and the pace is increasing
Eric Schmidt,
Google CEO,
at the Techonomy Conference,
August 4, 2010 (1 exabyte = 1018 bytes )
Feb
ruary
3, 2012
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Enterprise’s data is
Feb
ruary
3, 2012
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BIG DATA:
Why this BUZZ di?
Feb
ruary
3, 2012
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• Relational Databases have successfully created a $100 Billion dollar/year
industry. Relational databases manage 100s of TB of structured data in
the enterprise well.
• Beyond structured data, today’s enterprise must manage large, ever growing quantities of unstructured data and public data to derive
insights. This data is not being leveraged for decision making.
• Data management techniques created and perfected by Internet
Companies are ready for enterprise use.
• This confluence of distributed internet-based data management systems
with relational systems is making it possible to derive insights from large
volumes of diverse data sources in the enterprise.
Summary: Internet Technologies are
coming to the Enterprise
Feb
ruary
3, 2012
42
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• Enterprises traditionally have two data stacks:
• Data Stack 1.0: Operational Data Store
• Data Stack 2.0: Enterprise Data Warehouse
• Despite the two data stacks, more than 70% of enterprise data is not
“accessible” for analytics and decision making.
• This is because large amount of enterprise data is:
• Unstructured – variety
• Large Quantities – volume
• Real-time – velocity
• Time to establish Data Stack 3.0
• Data Stack 3.0: Big Data Stack
Summary: Time to setup Data Stack 3.0
Feb
ruary
3, 2012
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• Transaction processing capabilities ideally
suited for transaction-oriented operational
stores.
• Data types – numbers, text, etc.
• SQL as the Query language
• De-facto standard as the operational store
for ERP and mission critical systems.
• Interface through application programs
and query tools
Data Stack 1.0:
Relational Database Systems for
Operational Store
Feb
ruary
3, 2012
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• Operational data stores store on-line
transactions
• Many writes, some reads.
• Large fact table, multiple dimension tables
• Schema has a specific pattern – star
schema
• Joins are also very standard and create
cubes
• Queries focus on aggregates.
• Users access data through tools such as
Cognos, Business Objects, Hyperion etc.
Data Stack 2.0: Enterprise Data Warehouse
for Decision Support
Feb
ruary
3, 2012
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Data Stack 2.0:
Enterprise Data Warehouse Systems
Standard Enterprise Data Architecture
Data Warehouse
Engine
Optimized Loader Extraction
Cleansing
(ETL)
Analyze
Query
Metadata Repository
Relational
Databases
Legacy
Data
Purchased
Data
ERP
Systems
Relational Databases
Application Logic
Presentation Layer
Data Stack 1.0:
Operational Data Systems
Feb
ruary
3, 2012
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One in two business executives believe that they do not have sufficient information across their organization to do their job
Source: IBM Institute for Business Value
Despite the two data stacks ..
Feb
ruary
3, 2012
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This is because only a small
fraction of the
• data in enterprise and
• data from public data
sources
is managed by the
enterprise data stacks!
Feb
ruary
3, 2012
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Beyond the Operational Systems, data
required for decision making is scattered
within and beyond the enterprise
ERP Systems
CRM Systems
Enterprise
Data Warehouse
Structured
Data Sources
Email Systems Collaboration/
Wiki Sites
Document Repositories
Project artifacts
Employee Surveys
Customer Call
Center Records
Unstructured
Data Sources
Cloud
Data Sources
Public
Data Sources
CRM Systems
Expense
Management
System
Organizational
Workflow
Sensor
Data
Vendor
Collaboration
Systems
Supply Chain
Systems
Weather forecasts
Demographic Data
Maps
Location and
Presence Data
Economic Data
Social Networking
Data
Feeds
Feb
ruary
3, 2012
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What comes first -- Structure or data?
Schema/
Structure Data
Traditional Database Architectures have traditionally taken the schema
first approach.
How do you even start putting structure to your unstructured data?
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ruary
3, 2012
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Time to create a
new data stack for
unstructured data.
Data Stack 3.0.
Feb
ruary
3, 2012
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Time-out!
Internet companies
have already
addressed the same
problems.
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ruary
3, 2012
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• Every month, over half a billion different people check
their email, post photos, chat with their friends, and do a
myriad other things on Yahoo! sites.
• 250 million tweets every day on Twitter ! (100 million at the
beginning of the year)
• 400 million web searches on Google every day
• Over a billion updates on Facebook every month.
Internet Companies have to deal with large
volumes of unstructured real-time data.
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ruary
3, 2012
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• Hosted service
• Large cluster (1000s of nodes) of low-
cost commodity servers.
• Very large amounts of data -- Indexing
billions of documents, video, images etc..
• Batch updates.
• Fault tolerance.
• Hundreds of Million users,
• Billions of queries every day.
Their data loads and pricing requirements
do not fit traditional relational systems
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ruary
3, 2012
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• It is the platform that distinguishes them from everyone else.
• They required:
• high reliability across data centers
• scalability to thousands of network nodes
• huge read/write bandwidth requirements
• support for large blocks of data which are gigabytes in size.
• efficient distribution of operations across nodes to reduce bottlenecks
Relational databases were not suitable and would have been cost
prohibitive.
They built their own systems
Feb
ruary
3, 2012
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New companies have
created business
models to support
and enhance this
software
Internet Companies have open-sourced the
source code they created for their own use.
Feb
ruary
3, 2012
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Open Source Rules !
Feb
ruary
3, 2012
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Hadoop
Infrastructure
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What about support !
Feb
ruary
3, 2012
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How does one go about the Big Data
Expedition?
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ruary
3, 2012
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Ingest new
data
Run Big Data
Algorithms
Generate
reports and
insight
How does one go on a Big Data Expedition
Feb
ruary
3, 2012
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Incrementally, Iteratively
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Data Stack 3.0 Architecture
Server
OLAP
BI Tools
Log
Serve
rs
Unstru
cture
d
data
source
s
Persistent Bigdata Library (PEBL)
Recomm
endation
Engines
Clusteri
ng
Algorit
hms
Graph
Algorit
hms
Cra
wle
rs and
Extra
ctors
DS 1.0
System
Big Data Platform
Map
Reduce
(PIG/jaql)
Text
Analytics
(AQL)
Hive
SQL
Statistics - R/
Predictive
Analytics
Ingest Process Visualize Feb
ruary
3, 2012
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DS 2.0
EDW ELT
Insights
Seque
nce
Algorit
hms
Stats
Algorit
hms
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With the data that is now available …
• What business problems can be solved in a more cost-effective way?
• What business problems can be solved with the data that we are
collecting but not leveraging?
• What questions are we afraid to ask because we believe it will be too
difficult to answer them or it would take too long to get the answer?
• What business questions are simply not being asked?
• How does this fit-in with the currently deployed infrastructure? What do
we need to do beyond what we have?
What use is Data Stack 3.0?
Feb
ruary
3, 2012
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Search Quality
• Typical Search Engine
• Web crawling in MR
• Analysis of web pages in MR
• Index creation is MR
• Search Quality algorithms like TF*IDF, Page Rank are MR
• Vertical applications based on search – Vacation Home
Web Crawling Analysis of web pages Inverted Index
Search
Runtime
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ruary
3, 2012
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What are they doing with big data:
Search Assist
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ruary
3, 2012
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Risk Modeling
• Identifying risk exposure from each customer. E.g. – a survey found that
• 2.2K (out of 100K) customers using CC at beer bars missed payments once
in 4 months
• In contrast only 530 customers using CC to pay dentist bill missed payments
once in 4 months
• Essentially – the enterprises have to analyze and co-relate the data
coming from multiple sources
• Usually such data needs to be loaded once (say previous 5 years data)
• No pure algorithm to find such conclusions – its manual skill
• But, analysts need to query the data in different ways
• Providing mechanism for generating fast reports helps!
Feb
ruary
3, 2012
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Sentiment Analysis/Customer Churn
Analysis
• Web2.0 – people tend to put lot of opinions on blogs, discussion forums
• Sentiment analysis – typical workflow
• The first 3 steps are perfect MR
Crawl typical
blogging
sites
Text mining Data
analytics DB load Reporting
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ruary
3, 2012
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Recommendation Engine
• “Customer who bought this item also bought….”
• “People you may know…”
• Enterprise collect data on users, past transactions, their interests
• They try to use this data for such recommendations
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ruary
3, 2012
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What are they doing with big data:
Recommendation
Feb
ruary
3, 2012
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What are they doing with big data:
Targeted Ad
Feb
ruary
3, 2012
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ruary
3, 2012
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Technology Driving Growth
Anand Deshpande
February 3, 2012
www.persistentsys.com © 2012 Persistent Systems Ltd
As applications move to the cloud they
will lose their tight hold on enterprise data.
Enterprise data will be available on the
cloud as a service independent
of the application.
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ruary
3, 2012
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Data is getting separated from Enterprise
Applications and is accessible on the cloud
through independent APIs.
Application
Data Data
App API
Traditional Application
Scenario
Application running in
the cloud Feb
ruary
3, 2012
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Cloud Vendors will aggregate enterprise
data. And make it available through APIs.
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ruary
3, 2012
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The impact of aggregate data
http://data.mint.com/
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ruary
3, 2012
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Concur: Aggregating Travel Data
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ruary
3, 2012
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ruary
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Insights
Public
Data
Aggregate
Data
Enterprise
Data
As Enterprise Data
moves to the
cloud, it would be
easier to combine
enterprise data
with aggregate and
public data
sources.
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ruary
3, 2012
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Beyond the enterprise applications,
large number of apps will be available
on a pay-per-use basis in the App Store.
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ruary
3, 2012
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There will be a hierarchy of apps with
different price points; all available on a pay-
per-use business model.
Business Process
Specific Apps
Task/Device
Specific Apps
Traditional
Applications will
be commoditized
on the cloud.
Aggregate
Data
Enterprise
Data Public Data
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ruary
3, 2012
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Products/Apps will be consumed in
ready-to-eat bite-sized portions
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From the
App Store
Low per
Unit Cost
Zero Loyalty
Pay per
Use
Snap-in
Snap-out
The New App World
Feb
ruary
3, 2012
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To summarize
• As applications move to the cloud they are taking data to the cloud as
well.
• Data on the cloud is now accessible through APIs independent of the
application.
• Cloud operators are aggregating data.
• The ability to combine Enterprise data, Aggregate data and Public data
is very powerful.
• The world is moving to “the world of apps.” Apps will be business
process specific or task/display specific.
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Technology Driving Growth
Anand Deshpande
February 3, 2012
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Innovation through Gandhian
Engineering Getting more for less for more
Feb
ruary
3, 2012
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India:
the source
and
the market
for innovation
85
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Technology Driving Growth
Anand Deshpande
February 3, 2012
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