Bigdata Course Content

Introduction to Big Data

Defining Big Data

» The four dimensions of Big Data: volume, velocity, variety, veracity
» Introducing the Storage, MapReduce and Query Stack

Delivering business benefit from Big Data

» Establishing the business importance of Big Data
» Addressing the challenge of extracting useful data
» Integrating Big Data with traditional data

Storing Big Data

Analyzing your data characteristics

» Selecting data sources for analysis
» Eliminating redundant data
» Establishing the role of NoSQL

Overview of Big Data stores

» Data models: key value, graph, document, column-family
» Hadoop Distributed File System
» HBase
» Hive
» Cassandra
» Hypertable
» Amazon S3
» BigTable
» DynamoDB
» MongoDB
» Redis
» Riak
» Neo4J

Selecting Big Data stores

» Choosing the correct data stores based on your data characteristics
» Moving code to data
» Implementing polyglot data store solutions
» Aligning business goals to the appropriate data store

Processing Big Data

Integrating disparate data stores

» Mapping data to the programming framework
» Connecting and extracting data from storage
» Transforming data for processing
» Subdividing data in preparation for Hadoop MapReduce

Employing Hadoop MapReduce

» Creating the components of Hadoop MapReduce jobs
» Distributing data processing across server farms
» Executing Hadoop MapReduce jobs
» Monitoring the progress of job flows

The building blocks of Hadoop MapReduce

» Distinguishing Hadoop daemons
» Investigating the Hadoop Distributed File System
» Selecting appropriate execution modes: local, pseudo-distributed, fully distributed

Tools and Techniques to Analyze Big Data

Abstracting Hadoop MapReduce jobs with Pig

» Communicating with Hadoop in Pig Latin
» Executing commands using the Grunt Shell
» Streamlining high-level processing

Performing ad-hoc Big Data querying with Hive

» Persisting data in the Hive MegaStore
» Performing queries with HiveQL
» Investigating Hive file formats

Creating business value from extracted data

» Mining data with Mahout
» Visualizing processed results with reporting tools

Developing a Big Data Strategy

Defining a Big Data strategy for your organization

» Establishing your Big Data needs
» Meeting business goals with timely data
» Evaluating commercial Big Data tools
» Managing organizational expectations

Enabling analytic innovation

» Focusing on business importance
» Framing the problem
» Selecting the correct tools
» Achieving timely results

Statistical analysis of Big Data

» Leveraging RHadoop functionality
» Generating statistical reports with RHadoop
» Exploiting RHadoop visualization
» Making use of analytical results

Implementing a Big Data Solution

» Selecting suitable vendors and hosting options
» Balancing costs against business value
» Keeping ahead of the curve

Below you can find city wise Bigdata Institutes

Bigdata training institutes in India
Bigdata training institutes in Chennai
Bigdata training institutes in Bangalore
Bigdata training institutes in Mumbai
Bigdata training institutes in Pune
Bigdata training institutes in Delhi-NCR