Applications of BIG Data in E-Commerce

Slide ‹#›© 2015 BlueCamphor Technologies (P) Ltd. www.skillspeed.com
Applications of BIG Data in
E-Commerce

Introduction to BIG Data
Big data is the term for a collection of data sets so
large and complex that it becomes difficult to
process using on-hand database management tools
or traditional data processing applications
Retail industries generate extremely high volumes of
data due to high churn of transactions & inventory.
These companies can utilize BIG Data insights to
ensure higher profitability.

Applications of BIG Data in E-Commerce
• Personalization – Enhanced Experience
• Dynamic Pricing
• Improved Customer Service
• Managing Fraud
• Predictive Analytics

Personalization
Consumers shop with the same retailer in different ways. Data from these multiple touch
points should be processed in real-time to offer the shopper a personalized experience,
including content and promotions.
The segmentation should be such that loyal users are rewarded and new users are incentivized
in tandem with their requirements to enter the ecosystem. BIG Data will enable this process.
BIG Data Applications in E-Commerce
Dynamic Pricing
Dynamic pricing is needed as majority of products compete on price with other sites. This
requires taking data from multiple sources such as competitor pricing, product sales, regional
preferences and customer actions to determine the right price to close the sale. Real time
analytics can help create a competitive advantage in choosing optimal price points.
Get Started with BIG Data & Hadoop

BIG Data Applications in E Commerce
Customer Service
Online retailers can use Big Data to provide an excellent customer service experience.
For example, if a customer has complained via the contact form on an online store and also
tweeted about it, Big data need be used to have the tweet in background when he/she calls
customer service. This will result in the customer feeling valued, creating a quicker resolution
and positive brand-image.
Fraud Detection
BIG Data can help aid fraud detection. If fraud is detected in real-time, it leads to a quicker
resolution.
When fraud detection pattern and combined with BIG Data powered real-time detection the
system gathers the required intelligence to detect & negate fradulent practices.

BIG Data Applications in E-Commerce
Predictive Analytics
BIG Data can enable you to predict product demand, consumer behavior patterns & supply
chain mechanics.
For example, if the demand for a particular product can be predicted, accordingly, marketing
spends and inventory cycles can be optimized..

Current Examples of Big Data Application
Homeshop 18
 Homeshop 18 tracks the entire customer journey, which includes customer behaviour—how customers look at
the site and what products they usually choose, action taken by a customer on the website and how customers
navigate the website. The company has been deploying Big Data analytics since the last 15 months using
Hadoop, a software from open source software foundation Apache that can process huge amounts of data.
Snapdeal
 Snapdeal has 20 Million subscribers and a catalogue of over 5 Million products. They utilize BIG Data Analytics to
track data regarding consumer purchase patterns, time-to-purchase interactions & website navigation. Based on
this, they've generated an algorithm based recommendation engine & other products to boost sales.
Alibaba
 China's e-commerce giant Alibaba Group uses Big Data to protect intellectual property rights and crack down on
counterfeit products. ‘The Internet and BIG Data can be a powerful tools to fight the making and sale of
counterfeit goods’, said Alibaba's Chief Risk Officer Shao Xiaofeng.

© 2015 BlueCamphor Technologies (P) Ltd.
How Are Insights Derived from BIG
Data?
Say Hello to Hadoop Development :)

Introduction to Hadoop
Apache Hadoop is a framework that allows the distributed processing of large data sets across clusters of
commodity computers using a simple programming model.
It is an Open-Source Data Management technology with extensive storage and distributed processing.
Hadoop
Characteristics
Flexible
Reliable
Economical
Scalable Get Started with BIG Data & Hadoop

Why Should You Learn Hadoop?
• Hadoop is a modern BIG Data processing framework which utilizes distributed computing clusters.
• It can process, manage and store unstructured data with absolute ease.
• Due to its scalability & effectiveness, companies are heavily adopting Hadoop.
• It has become the standard for storing, processing and analyzing big data.
• BIG Data & Hadoop professionals are in extremely high demand.
• This is the first step to becoming a data scientist or data architect.

Reports – 2015
Here are some of the other Reports that convey the same message:
• “It is expected that Hadoop and Big Data Analytics will grow to around $13.9 billion from 2012 to 2017.”
(Markets and Markets Research Report)
• “The Data market currently with the fastest growth are Hadoop and NoSQL software and services.”
(Technology Research Organization, Wikibon)
• “The Big Data market will likely hit $23.8 billion with a 31.7% rise per year.” (IDC Report)
• “Almost 90% organizations have embarked on Hadoop related projects and thus Hadoop skills are in huge
demand.” (According to the Big Data Executive Survey 2013)
• “Companies hiring Hadoop professionals Analytics professionals obtain a 250 percent hike in their
salaries.” (According to Analytics Industry Report)
Gartner had predicted, “Hadoop will be in most advanced analytics products by 2015.” By far and large, this
prediction has turned out to be true. Hadoop is “The Technology” to harness Big Data

Predictions for 2015
According to the Forrester Report:
• A new data economy will arise, Hadooponomics. Due to its vast data prowess, enterprise adoption of
Hadoop will become compulsory. All those companies, which were unsure of adopting Hadoop till 2014,
are bound to adopt it in 2015
• The surge in demand for Hadoop job professionals will be fulfilled by Java professionals & other software
engineers who will upgrade their skills
• The creation of SQL-on-Hadoop options will further enhance usability & adoption
• Due to the introduction of Yarn (Version 2.0), the usage of Hadoop will go beyond analytics. It will
transform into an application platform giving birth to new frameworks in the Hadoop ecosystem
• New Hadoop sources will emerge from organizations like Oracle, HP, Tibco and SAP. Vendors such as Red
Hat, VMware and Microsoft will include Hadoop in their operating Systems

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Course Topics
Module 1
Introduction to Big
Data and Hadoop
Module 2
HDFS Internals, Hadoop
Configurations and
Data Loading
Module 3
Introduction to Map
Reduce
Module 4
Advanced Map Reduce
Concepts
Module 5
Introduction to Pig
Module 6
Advanced Pig and
Introduction to Hive
Module 7
Advanced Hive
Concepts
Module 8
Extending Hive and
HBase Introduction
Module 9
Advanced HBase and
Oozie Introduction
Module 10
Project Set-up
Discussion

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Applications of BIG Data in E-Commerce

Applications of BIG Data in E-Commerce

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