It’s not the size of your data, but what you do with it that counts.
In this webinar, Cesar Longa from IDC Software and SAP’s Mario Dominguez explore the multi-billion dollar global Big Data opportunity. Cesar shares findings of IDC’s Latin America CXO Barometer study hot off the press, while Mario looks at what’s now and next in the application of Big Data to create business value.
1. Big Data, Big Thinking:
The Big Opportunity
It’s not the size of your data, but what you do with it that counts.
In this webinar, Cesar Longa from IDC Software and SAP’s Mario Dominguez explore the
multi-billion dollar global Big Data opportunity. Cesar shares findings of IDC’s Latin America
CXO Barometer study hot off the press, while Mario looks at what’s now and next in the
application of Big Data to create business value.
SAP Big Data, Big Thinking webinar series
2. IDC Latin America CXO
Barometer study:
key findings
More insightful, intelligent business
Everyone’s talking about Big Data as if it were
a passing fad, but it’s not. Big Data analytics
is such a huge phenomenon, we’re barely
scratching the surface today.
Customer satisfaction data can be derived
from multiple sources:
• customer service evaluation
• pre- and post-sales contact center data
• customer surveys
• operational or transactional systems
• social networks
• other digital media (e-mail, chat,
mobile app analytics, geo-localization,
machine sensors)
This data can be used to create contextually
relevant, timely, personalized offers. It’s
precious and should be treated accordingly.
BUT…
most of the data generated via digital
marketing campaigns resides in silos,
or gets consolidated in spreadsheets –
there isn’t a single, reliable platform for
providing insights.
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3. Major challenges
IDC Latin America CXO Barometer study:
key findings
Data
integration
Data
quality
Data
security
Missed opportunities
A lack of tools and talent
Business users typically lack the skills and the time required for analytical decision-making
7 out of 10 organizations are failing to
identify new business opportunities because
they have no lead scoring model in place.
6 out of 10 lack the tools to determine the
revenue impact of marketing campaigns.
4 out of 10 organizations still haven’t
mobilized any of their sales applications.
46% need help from
IT to make sense of
their data, or resort
to spreadsheets for
analysis and reporting
because there are no
self-service tools.
31% of organizations
have a dedicated
business intelligence
position rather than
putting analytics
into the hands of
non-technical users.
What is needed to meet business
imperatives?
• Anytime, anywhere access to
self-service analytics in real-time
• Contextually-relevant
enterprise applications
• Location-based services
• Alerts and notifications
• Workflow automation
• Intelligent systems and devices
The three biggest challenges
for Big Data analytics are:
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4. Technology initiatives increasingly
funded by the business
The business, rather than IT, now funds
61% of technology projects – sometimes
for business-driven initiatives, often for
joint projects with IT, but increasingly using
shadow IT (17%). Business leaders are
driving data requirements, analytics and
output right from the start. Only 19% of
projects are funded and driven solely by IT.
IT/Business alignment
The top business priorities for CXOs are:
#1 operational efficiency and productivity
#2 cost savings
CIOs and CTOs share these same priorities
in reverse, and are increasingly looking to
become business enablers rather than
technology gatekeepers.
Transformational IT requires…
• Information integration
• Infrastructure efficiency
• Automation
• Analytics
…all of which must combine to enable
decision makers to answer business
questions in hours, not weeks or months.
IDC Latin America CXO Barometer study:
key findings
IT spend breakdown
Business
funded
61%
IT funded
39%
19%
17%
Shadow
IT
Solely
IT
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5. Big Data isn’t about the size of the data pool – it’s about the analytics. So even half
a terabyte can still be classified as ‘Big Data’. Analytical applications have emerged
as the #1 use for Big Data.
Big Data 2.0 – a glimpse
into the future
Big Data 1.0
Big Data 1.0 has been characterized by:
• the indiscriminate capture and storage
of data without first determining its
value, thanks to the growing affordability
of storage
• new types of data, which present new
opportunities for analytics
• data discovery and data provisioning
becoming common in most organizations
Big Data 2.0
Big Data 2.0 is all about speed, quality
and the apps through which information is
delivered. One day, data cleansing projects
may become a thing of the past if we can
capture all data at source, including:
• enterprise transactions
• social data
• the Cloud
• the Internet of Things
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6. IoT data is deep and clean, allowing us to analyze it and put it to work in previously unthinkable ways.
Use cases already in practice today include:
The Internet of Things
Health applications
Today, IoT is being used to
prevent Sudden Infant Death
Syndrome by using sensors
embedded in a baby’s pyjamas to
monitor vital signs (temperature,
heart rate and respiration). If an
anomaly is detected, an alert can
be sent to the parent’s device
that something is wrong.
Smart machinery
Sensor data is already being
applied to real-time asset
monitoring, to drive predictive
maintenance programs and
agile logistics. And intelligence is
being embedded within ‘smart
products’ to notify users when
to replace consumables and
optimize usage.
Connected vehicles
Already a reality, connected
vehicles can talk to each other
via protocols to avoid collisions,
encourage safer driving and
parking, monitor tire condition
in real-time, and enable
innovative models such as
pay-as-you-go insurance.
Watch the video
How SAP are using
Big Data
The National Centre for
Tumor Diseases analyzes
Big Data using a custom-
built application – Patient
Data Explorer powered by
SAP HANA – enabling it
to develop individualized
therapies against cancer.
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