The growth in big data analytics and the Internet of Things (IoT) is estimated to add £322bn to the UK economy by 2020, in addition to creating 182,000 new jobs.
Big data is expected to result in efficiency savings of £220.4bn, innovation benefits of £12.4bn and business creation benefits of £8.1bn in the next five years, according to the SAS report.
The IoT is anticipated to bring efficiency benefits of £72.5bn, innovation benefits of £4.5bn and business creation benefits of £4.3bn.
With respect to adoption rates, around 56% of companies surveyed in the SAS report have currently rolled out big data analytics. This is expected to rise to 67% by 2020.
“Just under half of UK businesses are not using any form of Big Data analytics, and those that are will sometimes be using it infrequently in just one or a few areas of the business. Less than one in three have adopted IoT.”
Manufacturing, professional services, retail banking and telecoms will benefit from the growth in the next few years.
Big Data Analytics – Learning Objectives
After completing the course, students should be able to
Characterize the phenomena of Big Data and Big Data Analytics
Analyze and apply different visual analytics concepts and tools for a big data sets
Analyze and apply different concepts, methods, and tools for analyzing big data in organzizational contexts
Understand the linkages between business intelligence and business analytics and the potential benefits for organziations
Critically assess the ethical and legal issues in Big Data Analytics
- What is Big Data & Why Hadoop?
What is Big Data?
Characteristics of big data
Traditional data management systems and their limitations
What is Hadoop?
Why is Hadoop used?
The Hadoop eco-system
Big data/Hadoop use cases
- Hadoop Overview & its Ecosystem
“Anatomy of Hadoop Cluster, Installing and Configuring Hadoop
- HDFS – Hadoop Distributed File System
HDFS internals and use cases
Files and blocks
Namenode memory concerns
HDFS access options
Installing and configuring Hadoop
Basic Hadoop commands
- Mapreduce Anatomy
“How Mapreduce Works?
The Mapper & Reducer, Input Formats & Output Formats, Data Type & Customer Writable”
Functional programming concepts
Mapping and reducing lists
Putting them together in MapReduce
Word Count example application
Understanding the driver, mapper and reducer
Closer look at MapReduce data flow
Additional MapReduce functionality
- Developing MapReduce Program
Setting up Eclipse Development Environment
Creating Mapreduce Projects
Debugging and Unit Testing MapReduce Code
Testing with MRUnit
- Hive, Pig & Mahout
Pig program structure and execution process
Joins & filtering using Pig
Group & co-group
Schema merging and redefining functions
Using Hive command line interface
Data types and file formats
Basic DDL operations
- Introduction to Analytics
What is analytics and why is it so important?
Applications of analytics
Different kinds of analytics
Various analytics tools
- Basic Analytic Techniques
Introduction to R
Data Exploration with R
Data Preparation with R
Data Visualization with R
- Fundamentals of R
Installation of R & R Studio
Getting started with R
Basic and Advanced Data types in R
Variable operators in R
Working with R data frames
Reading and writing data files to R
R functions and loops
Special utility functions
Merging and sorting data
Case study on data management with R
- R and Hadoop Overview
“Introduction to R tool
R and Hadoop Integration
Hadoop Streaming using R
- Getting Data into the R environment
Reading local data
- Predictive Modeling Techniques
Time Series Analysis
- Descriptive statistics
- Inferential statistics
“T-test and non-parametric equivalents
Chi-squared test, logistic regression
- Linear Regression
- Sophisticated Graphics in R
Big Data Hadoop Data Analytics Training in chennai is Primarily hands-On & available as
Classroom / Online / Corporate Training
Call – +91 9789968765 / +91 99627 74619 / +91 9176HADOOP / 044 – 42645495
Big Data Analytics Training in Chennai
Updated on 2016-03-05T10:29:29+00:00, by .