BIG DATA

AGENDA
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What is Big Data?
The 3 V’s of Big Data
Advantages and disadvantages of Big Data
Big Data challenges
Big Data applications

WHAT IS BIG DATA ?
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TERM BIG DATA
Big data is a term that describes the large volume of data from traditional and
digital sources inside and outside a company that represents a source for
ongoing discovery and analysis
• both structured and unstructured
• Inundates a business on a day-to-day basis

3 V’S OF BIG DATA
While the term “big data” is relatively new, the
act of gathering and storing large amounts of
information for eventual analysis is ages old.
Big Data gained momentum in the early 2000s
when industry analyst Doug Laney articulated
the now-mainstream definition of big data as
the three Vs
 Volume
 Velocity
 Variety
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VELOCITY
 The data growth and social media explosion have changed how we look at
the data. There was a time when we used to believe that data of yesterday is
recent. But today, the data movement is now almost real time and the update
window has reduced to fractions of the seconds.
 RFID tags, sensors and smart metering are driving the need to deal with
torrents of data in near-real time.
 Velocity refers to the speed of information generated and flowing into the
enterprise
 Every big data analytics project will ingest, correlate and analyse the data
sources, and then render an answer or result based on an overarching query.
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VOLUME
 Organizations collect data from a variety of sources, including business
transactions, social media and information from sensor or machine-to-
machine data.
 It is very common to have Terabytes and Petabytes of the storage system
for enterprises. As the database grows the applications and architecture built
to support the data needs to be revaluated quite often.
 Sometimes the same data is re-evaluated with multiple angles and even
though the original data is the same the new found intelligence creates
explosion of the data.
 In the past, storing it would’ve been a problem – but new technologies
(such as Hadoop) have made the process easy.
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VARIETY
 Data comes in all types of formats – from structured, numeric data in
traditional databases to unstructured text documents, email, video, audio,
stock ticker data and financial transactions.
 It is the need of the organization to arrange it and make it meaningful. It
will be easy to do so if we have data in the same format, however it is not the
case most of the time.
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MORE ON BIG DATA
The Big Data landscape is dominated by two classes of technology:
1. Systems that provide operational capabilities for real-time, interactive
workloads where data is primarily captured and stored
2. Systems that provide analytical capabilities for retrospective, complex
analysis that may touch most or all of the data.
Each has driven the creation of new technology architectures. Operational
systems, such as the NoSQL databases, focus on servicing highly
concurrent requests. Analytical systems, on the other hand, tend to focus on
high throughput;
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ADVANTAGE OF BIG DATA
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 Improved Customer Insights
(For Ex. Southwest Airlines, extracts Large volume of data from interactions
between customers and personnel to get a better understanding of their customers.)
 Faster, better decision making
(Ex. Caesars, a leading gaming company that has long embraced analytics, is
now embracing big data analytics for faster decisions.)
 Cost Reduction
(Big data technologies like Hadoop and cloud-based analytics can provide
substantial cost advantages.)
 New products and services
(Ex: GE, for example, has made a major investment in new service models for its
industrial products using big data analytics.)

DISADVANTAGE OF BIG DATA
 It requires special computer power
 Using real-time insights requires a different way of working within your
organisation
 Difficult to assess accuracy and uncertainty
 Privacy and confidentiality issues
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BIG DATA CHALLENGES
 Capturing data
 Storage
 Searching
 Sharing
 Transfer
 Analysis
 Presentation
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BIG DATA
APPLICATIONS
Reference: http://blog.spec-india.com/looking-into-the-future-with-big-data-and-analytics/

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Thank you