This document discusses an introduction to big data module. It covers topics like the evolution of big data, best practices for big data analytics, characteristics of big data, validating big data's value, characteristics of big data applications, and the data analytics lifecycle. It describes how enterprises can capture value from big data through creating transparency, data-driven discovery, segmentation and customization, automation, and enabling innovation. Examples are provided of how Netflix, Uber, and other companies use big data to improve customer experiences, solve problems, increase revenue, and cut costs.

1. 19CSE13 - DATA ANALYTICS MODULE 1
1 INTRODUCTION TO BIG DATA
Evolution of Big data - Best Practices for Big data Analytics -
Big data characteristics - Validating – The Promotion of the
Value of Big Data - Characteristics of Big Data Applications –
Data Analytic Life cycle– Applications of Big Data Applications
MODULE 1 - INTRODUCTION TO BIG DATA
INTRODUCTION TO BIG DATA 1

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1 INTRODUCTION TO BIG DATA
INTRODUCTION TO BIG DATA 2
S.No Topic
1.1 Evolution of Big data
1.2 Best Practices for Big data Analytics
1.3 Big data characteristics
1.4 Validating
1.5 The Promotion of the Value of Big Data
1.6 Characteristics of Big Data Applications
1.7 Data Analytic Life cycle
1.8 Applications of Big Data Applications

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SESSION 1.5
The Promotion of the Value of Big Data
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1 INTRODUCTION TO BIG DATA
Value of Big Data
◾ The primary reason why Big Data has developed rapidly over the
last years is because it provides long-term enterprise value. Value
is captured both, in terms of immediate social or monetary gain,
and in the form of a strategic competitive advantage.
◾ Due to its wide range of applications, Big Data is embraced by all
types of industries, ranging from healthcare, finance and
insurance, to the academic and non-profit sectors.
◾ There are various ways in which value can be captured through
Big Data and how enterprises can leverage to facilitate growth or
become more efficient.
◾ Each of these drives the ʻdigital transformationʼ of organizations
and have a long-term effect on the way the enterprises will have
to be designed, organized and managed.
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Capturing the Value of Big Data
 Enterprises can capture value from Big Data in one of the
following five ways:
1) Creating transparency
2) Data driven discovery
3) Segmentation and customization
4) The power of automation
5) Innovation and new products.
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1) Creating transparency
INTRODUCTION TO BIG DATA 6
 Using the data of an organization to determine future
decisions makes an organization increasingly more
transparent and breaks down the silos between different
departments.
 Big Data is analyzed across different boundaries and can
identify a variety of inefficiencies. In manufacturing
organizations.
 For example, Big Data can help identify improvement
opportunities across R&D, engineering and production
departments in order to bring new products faster to market.

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2) Data driven discovery
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 As enterprises create and store more and more transactional
data in digital forms, more performance data becomes
available.
 Big Data can provide tremendous new insights that might
have not been identified previously by finding patterns or
trends in data sets.
 In the insurance industry for example, Big Data can help to
determine profitable products and provide improved ways to
calculate insurance premiums.

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3) Segmentation and customization
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 The analysis of Big Data provides an improved opportunity to
customize product-market offerings to specified segments of
customers in order to increase revenues.
 Data about user or customer behavior makes it possible to
build different customer profiles that can be targeted
accordingly.
 Online retailers, for example, can tailor the product offering on
their websites to match the current customer and increase
their conversion rates.

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4) The power of automation
INTRODUCTION TO BIG DATA 9
 The analysis of Big Data provides an improved opportunity to
customize product-market offerings to specified segments of
customers in order to increase revenues.
 Data about user or customer behavior makes it possible to
build different customer profiles that can be targeted
accordingly.
 Online retailers, for example, can tailor the product offering on
their websites to match the current customer and increase
their conversion rates.

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1 INTRODUCTION TO BIG DATA
5) Innovation and new products.
INTRODUCTION TO BIG DATA 10
 Big data can unearth patterns that identify the need of new
products or increase the design of current products or
services.
 By analyzing purchasing data or search volumes,
organizations can identify demand for products that the
organization might be unaware of.
 Universities or colleges, for example, might study their
website traffic and search volumes to forecast class
enrollment and allocate teaching resources accordingly.

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How Does Big Data Help Companies in terms of Value?
 Making better business decisions
 Understanding your customers
 Delivering smarter services or products
 Improving business operations
 Generating an income
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1. Improving Customer Experiences
 When you collect data about your leads and customers, you can
track trends to deliver the best customer service throughout their
journey with your company. One unconventional but highly
effective example of this is the "House of Cards" series on Netflix.
 As New York Times explained: "[Netflix] already knew that a
healthy share had streamed the work of David Fincher, the
director of The Social Network, from beginning to end. And films
featuring Kevin Spacey had always done well, as had the British
version of "House of Cards."
 Netflix took the risk of putting down $100 million for two seasons.
 Essentially, data determined the creative direction of "House of
Cards" and delivered viewers with exactly what they wanted to
see.
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2. Solving Problems
 Big data can be used to identify blockers in business
processes and funnels and remedy these with diagnostic
data analysis.
 Uber is one example of this. Uber has been honing its big
data solution to forecast rider demand during high traffic
events and even identify and address bottlenecks in the
driver sign-up process.
 Uber Movement now shares anonymized data aggregated
from over ten billion trips to help urban planning around the
world.
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3. Increasing Revenue
 Revenue is closely tied to customer experience.
 By using big data to deliver tailor-fit recommendations for
every viewer, Netflix has an estimated churn rate of just 9%.
 Big data enables businesses to also increase revenue by
iterating existing products and designing new launches
around proven customer needs.
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4. Cutting Costs
 According to NewVantage Venture Partners, the top
advantage of big data is decreasing expenses.
 By nature, big data works at scale — it removes the need
to manually collect and analyze data, which, alongside
reduced churn, comes with big cost savings.
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Session 1.6
Characteristics of Big Data Applications
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