Data-as-a-Service has significant potential to become accepted mainstream. We explore the factors that can contribute to DaaS' success.

1. Can Data-as-aService be the Next
Big Thing?
PromptCloud’s Perspective
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2. DaaS is integral to BI and Analytics
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According to market research firm Gartner, the SaaS market will grow to
$22.1 billion by 2015. DaaS, which is increasingly an integral part of BI
and analytics, is poised to garner a decent share of this pie.
•
By 2020, the scope of pattern recognition and data analysis in real-time
will improve with an advancement in technology. Even more open
source, DIY tools will lead the way towards user innovation, enabling an
improved understanding of people and the world.
•
Big data has become a crucial aspect of strategic intelligence of many
corporations, providing them competitive advantage by enhancing the
value that various business functions deliver.
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3. DaaS and Business Intelligence
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The business intelligence space is growing faster than many
organizations would have anticipated. Companies are moving towards
more comprehensive insights concerning consumer behavior and
internal processes.
•
This has led them to move beyond the traditional data management
towards more intelligent, real-time and proactive BI analytics.
•
Earlier, organizations that were using licensed software applications, are
now hiring out vertical-specific data service providers that also bring
along analytic capabilities. Apart from BI, many other industries such as
healthcare are witnessing rapid adoption of big data, proving to be a
real life-saver.
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4. Personalization of Customer
Experience
•
The future of e-commerce is mass personalization, and to achieve
that, humongous amounts of data needs to be monitored, analyzed and
recommendations made in real-time.
•
For example, if a user inputs a search term for (say) Apple's iPhone
5S, suggesting an iPhone case that suits the user's taste (based on past
buying experience or profile) within milliseconds can be done using
data.
•
Online services such as Amazon, Google Play store, Netflix already
provide real-time recommendations on the basis of previous behavior or
profile of a user. This not only saves the user's time but also enhances
user experience as they're introduced to products that they only had a
latent need for.
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5. Use of Data in Influencing War
Sentiment
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According to Sean Gourley of Quid, governments are increasingly using
big data in war zones to predict attacks or influence violent sentiments
on social media.
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In the future we can expect data to be a core part of war strategies, and a
major tactical advantage.
•
Sean also mentioned that to solve the biggest problems of the world, a
shift in focus from data science to data intelligence is required.
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The primary difference between these two is that while data science is
about finding correlations, data intelligence refers to solving real
problems.
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6. Roadblocks to DaaS adoption (1/2)
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A few limitations still exist in mass adoption of DaaS. While some of
these are addressable, for others changes in the current tech capabilities
would be necessary.
•
For instance, data transparency for people and an open access to
analytical tools are necessary for creating a conducive environment for
big data. For making judgements on data and to derive insights, human
intervention will still be required.
•
We must also figure out a way to keep up with the burgeoning rate at
which data is expanding.
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7. Roadblocks to DaaS adoption (2/2)
•
Analysts regularly encounter roadblocks while processing exabytes of
data due to the volume of data sets from various verticals, devices and
platforms such as web, research, email, social
media, meteorology, genomics, etc.
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This rapid expansion is attributable to an internet of things, feeding
sensory data from various devices in real time.
•
DaaS integration must be aimed at achieving simplicity. Towards that, it
should derive from SaaS - which has based its growth on simplified
business processes. As more and more business people realize the
importance of real-time data capture and analysis, data as a service is set
to become an integral part of BI.
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8. Thank You.
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