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INTELLIGENT CITIES
petabytes, and even exabytes of data generated by enterprises and
consumers. ey are specifically capable of processing multiple data
types. at is, NoSQL databases could contain different data types
such as text, audio, video, social network feeds, weblogs, and many
more that are not being handled by traditional databases. ese data
are highly complex and deeply interrelated. erefore the demand is
to unravel the truth hidden behind these huge yet diverse data assets
besides understanding the insights and acting on them to enable busi-
nesses to plan and surge ahead.
Having understood the changing scenario, Web-based businesses
have been crafting their own custom NoSQL databases to elegantly
manage the increasing data volume and diversity. Amazon’s Dynamo
and Google’s Big Table are shining examples of home-grown data-
bases that can store large amounts of data. ese NoSQL databases
were designed for handling highly complex and heterogeneous data.
e key differentiation here is that they are not built for high-end
transactions but for analytic purposes.
4.9 Conclusion
Enterprises squarely and solely depend on a variety of data for their
day-to-day functioning. Both historical and operational data have
to be meticulously gleaned from different and disparate sources and
then cleaned, synchronized, and analyzed in totality to derive action-
able insights that in turn empower enterprises to get ahead of their
competitors. In the recent past, social computing applications have
been delivering a cornucopia of people’s data. e brewing need is to
seamlessly and spontaneously link enterprise data with social data to
enable organizations to be more proactive, preemptive, and people-
centric in their decisions, discretions, and dealings. Data stores, bases,
warehouses, marts, cubes, and so on are flourishing to congregate and
compactly store different data. ere are several standardized and
simplified tools and platforms for accomplishing data analysis needs.
en there are dashboards, visual report generators, business activ-
ity monitoring, and performance management modules to deliver the
requested information and knowledge to the authorized persons.
Data integration is an indispensable cog in that long and com-
plex process of transitioning data into information and knowledge.
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BDA FOR REAL-TIME CITY INSIGHTS
However, as in the past, data integration is not easy and rosy. ere
are patterns, products, processes, platforms, and practices galore for
smoothening data integration goals. In this chapter, we described
the necessity of information architecture for next-generation cloud
applications.
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