This document discusses the importance of connecting and exploiting big data through linking various data sources. It argues that simply creating new large data silos does not provide much value, and that true value is derived when numerous sources are brought together to create a single reference point. The document also discusses how linked data provides advantages over traditional big data approaches by structuring data around semantic triples that can interconnect different records and provide a bigger picture view. However, it cautions that linked data also requires rigorous controls and understanding to avoid simply creating another unstructured data source.

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Connecting and
Exploiting Big Data
Rajendra Akerkar
rak@vestforsk.no

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 Whilst big data may represent a step forward
in business intelligence and analytics, we see
added value in linking and utilizing big data for
business benefit.
 Once we bring together numerous data
sources to provide a single reference point can
we start to derive new value. Until then, we
only risk creating new data silos.

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Source: Bloor Group

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Hype around Big Data
Today, the difference between success and failure is the ability to monetize a
new class of data. It’s ironic that, despite billions of dollars spent on business
intelligence systems, we are still data‐bankrupt.
– Roman Stanek, Founder and CEO of Good Data

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What is Big Data?
Too big, moves too fast, or doesn’t fit the structures of your database
architecture
3 Dimensions: Variety, Velocity, and Volume
Big
Data
social
videos & photos
mobile GPS
email

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The rise and rise of Big Data

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Share of the digital universe by India and China

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Definition(s) of “big data”
Big Data is a term encompassing the use of
techniques to capture, process, analyse and
visualize potentially large datasets in a
reasonable timeframe not accessible to
standard IT technologies.
By extension, the platform, tools and
software used for this purpose are collectively
called ‘Big Data technologies’
(Networked European Software and Service Initiative, 2012).

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Attributes
Venue
Veracity
Vocabulary
What happens if the raw data you are
injecting into your system is
incomplete or formatted incorrectly
from the get‐go?

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The potential of Big Data
 Data contains information of enormous
business value
 Extract those insights and make far better
decisions
 ...but is data indeed that valuable?

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Correlation versus Causation versus “What’s great for
the job”
Oncologists might benefit from seeing the similarities among cells in a
biopsy, but targeting certain markers doesn’t guarantee you can cure
someone’s cancer.
Source: Columbia University

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Advanced (intelligent) data analytics
In-Database
analytics
Conventional
Advanced
analytics
Hadoop
Evolution
• Needs human intervention
• Latency, compression and speed
• Coverage is vital rather than thoroughness
• Data can be Tbytes  Pbytes
• Enhances the system performance by scale-out
• Statistical data and data mining
Conventional
• Fully automated thoroughness
is required
• Restricted on kinds of data
• Transaction management
• Volumes of data
Big Data Future
• New insight of multi-structured data
• Real-time big data analytics
• Process information in-memory, In-time, in-place
• Enhanced speed with low latency
• Semantic technologies
Conventional Advanced
(intelligent)
Analytics – NLP
and semantic
technologies
Unstructured data
batch processing -
Hadoop
In-Database
analytics
Information
Applications
Infrastructure
Cohesive
Infrastructure

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Semantics of big data
 shifting from “data of action” to “data of intention.”
 The future of big data will be to use it as a tool to
discover new segments & audiences, and invent new
products.

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Why Linked Data?
 Big data tends to be unstructured and metadata
becomes important
 for example, location data can help to make some sense of the
data in that it provides particular structure.
 Here, linked data provides some significant advantages in
knotting together different records to provide a view of
the bigger picture.
 linked data sees the Web as a giant database that can be
mined to link to data, rather than document‐based
resources.

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Linked Data ‐ Paradigm
 Use URIs as names for things
 Use HTTP URIs so that people can look up
those names.
 When someone looks up a URI, provide useful
information.
 Include links to other URIs. so that they can
discover more things.

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Linked data ̶ the next evolutionary stage for the
database?
 Through linked data, data in unstructured databases
can be linked to data in traditional data stores without
changing existing schemas
 Using linked data provides a highly scalable solution,
based on the same principles as unstructured data but
by structuring the linked data around triples
 An agent!
 mapping and interconnecting, indexing and feeding real‐time
information from a variety of sources

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Implementing big data and linked data
• Data integrity
• Understanding of the data
• Integration
• Data quality
• Data storage and replication
• Data migration
• Data security

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But, linked data is no remedy...
if rigorous controls are not applied to the
metamodel then
it becomes yet another unstructured data
source, making the problem worse, rather than
better!

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Publisher: Taylor & Francis Group/CRC Press
http://www.taylorandfrancis.com/books/details/9781466578371/
Read this book!