What is ‘pervasive intelligence’ and why is it big news for business? In this webinar, Alys Woodward, Research Director, IDC, and Javier Cuerva, Big Data Evangelist at SAP, explore how analytics is undergoing both an evolution and a revolution, point out the all-important fourth ‘V’ of Value when it comes to Big Data, and reveal why analytics projects are like sports. Take a look at this fact sheet to discover the future of Big Data now. More information at http://www.sapbigdatabigthinking.com

1. Big Data, Big Thinking:
Pervasive Intelligence
What is ‘pervasive intelligence’ and why is it big news for business?
In this webinar, Alys Woodward, Research Director, IDC, and Javier Cuerva, Big Data Evangelist at SAP,
explore how analytics is undergoing both an evolution and a revolution, point out the all-important
fourth ‘V’ of Value when it comes to Big Data, and reveal why analytics projects are like sports.
SAP Big Data, Big Thinking webinar series

2. There’s a constant battle to
handle higher data volumes,
reduce latency and integrate
more sources.
Pervasive intelligence in 2014 is no longer focused on front-
end business intelligence or end-user self service – it’s about
giving broad access to information to as many decision makers
as possible in real-time, whether that’s employees within the
organization or customers and partners outside.
Evolution or revolution?
Analytics is undergoing both. There’s a constant battle to handle
higher data volumes, reduce latency and integrate more sources.
But emerging technologies are becoming available and some
technologies that have been around for ages are becoming
democratized by coming within affordable reach of more
organizations.
Pervasive Intelligence today
SAP Big Data, Big Thinking webinar series
2

3. There are three principal types of business processes
or workloads to which analytics can be applied:
According to IDC, there are three major business
disciplines that harness the power of analytics:
Workloads and opportunities
SAP Big Data, Big Thinking webinar series
2. People
(customers, employees)
e.g. psychological predictions,
personalization of offers and content,
next best offer
1. Money
(accounts, cash, liquidity)
e.g. financial planning
Enterprise
Performance
Management
– plan and analyze
Technologies: relational
data warehouse with
in-memory technology,
OLAP, dashboard)
3. Things
(products, materials)
e.g. predictive maintenance, optimizing
assets and operations, demand sensing
Operational intelligence
– sense and respond
Technologies: Event or
Stream processing, rules
engine, workflow
Exploration and discovery – model and predict
Technologies: Hadoop, NoSQL, schema-less databases,
advanced analytics
1
3
2
3

4. Market trends
SAP Big Data, Big Thinking webinar series
Today, the top priority is investing in new storage
technologies – suggesting companies are still focusing
on the ‘v’ of Volume.
In the next 12 months, companies plan to test or use
a Big Data solution in the cloud – up from seventh
place in 2013 to top priority in 2014.
Why?
Cloud divides, distributes and delivers
technology in a way that democratizes
Big Data and allows even relatively
small organizations to:
- Take advantage of inexpensive
storage
- Analyze as well as access data in
the cloud
- Exploit a powerful engine that mid-
market or even large enterprise
couldn’t afford to run in house and
turn CAPEX into manageable OPEX
Line of business purchasing of Big Data
services is ramping up. That means IT
functions need to stay in touch with
business units and guide them towards
best practice rather than exposing the
business to the risks of shadow IT.
Cloud divides, distributes
and delivers technology
in a way that democratizes
Big Data
4

5. Expectations and realities
No organization achieves
Big Data Zen mastery
overnight without getting
a few analytics projects
under their belt first.
SAP Big Data, Big Thinking webinar series
In general, organizations’ expectations of Big Data initiatives are outstripping results.
But that’s hardly surprising: it’s a challenge to get value from Big Data as you won’t
save or generate millions overnight.
It typically takes many years of practice, a strong analytical culture and the ability
to withstand and learn from some failed attempts.
No organization achieves Big Data Zen mastery overnight without getting a few
analytics projects under their belt first.
One to watch…
IDC’s research indicates Hadoop has witnessed a dramatic upswing in popularity in the last
twelve months, with aggressive plans among organizations for 2015 – a dramatic rate of
adoption for a very new technology.
5

6. - Big data is exploding – more user types, more data types, more applications.
A hybrid architecture is needed to handle it.
- The connection between IT and lines of business has always been important to
the success of analytics – but never more so the case than with Big Data.
- Be realistic about obtainable benefits. Big Data is like a sport – taking part is good
but high performance mostly comes from years of training and a little bit of luck.
- Forget the three Vs of volume, velocity and variety: the only V that’s really important
is Value – how you plan to monetize Big Data analytics.
Recommendations
Join us
Participate in this webinar
series to understand how you
can get started with Big Data.
Join our expert speakers
as they share their insights
and guide you through
real-world Big Data examples.
For detailed information
about the Big Data, Big
Thinking webinars and
to register, go to
bit.ly/BigDataBigThinking
SAP Big Data, Big Thinking webinar series
The SAP Big Data Platform: acquire, analyze and act
- Oncologists are using the SAP Big Data platform to detect
cancers earlier. They’re accelerating genome analysis on
petabytes of data by 408,000 times, to detect variant DNA.
- Pirelli is using Big Data and predictive analytics to save
lives by detecting defects in tires before fatal accidents
can occur.
Watch on YouTube
6