big data & hadoop applications in e-commerce

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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.

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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.



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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 CharacteristicsFlexible

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




Why SkillSpeed?

Course Curriculum

from Industry Experts

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Lifetime access to Course

Content via LMS

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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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