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Data Analysis


Data Visualization


Data Predication

Certified Big Data & Hadoop Expert

  • 120 + hrs. Live Mentoring
  • 20 + hrs. Coding Assignments
  • 2 + Real-Life Projects
  • 3 + Industry cases

Modules Included

 Introduction and relevance

 Uses of Big Data analytics in various industries like Telecom, E- commerce, Finance and Insurance etc.

 Problems with Traditional Large-Scale Systems

  Motivation for Hadoop

  Different types of projects by Apache

 Role of projects in the Hadoop Ecosystem

  Key technology foundations required for Big Data

  Limitations and Solutions of existing Data Analytics Architecture

  Comparison of traditional data management systems with Big Data management systems

  Evaluate key framework requirements for Big Data analytics

  Hadoop Ecosystem & Hadoop 2.x core components

  Explain the relevance of real-time data

 Explain how to use big and real-time data as a Business planning tool

  Hadoop Master-Slave Architecture

  Data manipulation tools (Operators, Functions, Procedures, control structures, Loops, arrays etc)

  The Hadoop Distributed File System - Concept of data storage

 Explain different types of cluster setups(Fully distributed/Pseudo etc)

  Hadoop cluster set up - Installation

  Hadoop 2.x Cluster Architecture

  A Typical enterprise cluster – Hadoop Cluster Modes

  Understanding cluster management tools like Cloudera manager/Apache ambari

  HDFS Overview & Data storage in HDFS

 Get the data into Hadoop from local machine(Data Loading Techniques) - vice versa

  Map Reduce Overview (Traditional way Vs. MapReduce way)

 Concept of Mapper & Reducer

 Understanding MapReduce program Framework

  Develop MapReduce Program using Java (Basic)

  Develop MapReduce program with streaming API) (Basic)

  Integrating Hadoop into an Existing Enterprise

  Loading Data from an RDBMS into HDFS by Using Sqoop

 Managing Real-Time Data Using Flume

 Accessing HDFS from Legacy Systems

 Apache PIG - MapReduce Vs Pig, Pig Use Cases

  PIG’s Data Model

  PIG Streaming

 Pig Latin Program & Execution

 Pig Latin : Relational Operators, File Loaders, Group Operator, COGROUP Operator, Joins and COGROUP, Union, Diagnostic Operators, Pig UDF

 Writing JAVA UDF’s

 Embedded PIG in JAVA

 PIG Macros

 Parameter Substitution

  Use Pig to automate the design and implementation of MapReduce applications

 Use Pig to apply structure to unstructured Big Data

  Apache Hive - Hive Vs. PIG - Hive Use Cases

 Discuss the Hive data storage principle

  Explain the File formats and Records formats supported by the Hive environment

  Perform operations with data in Hive

  Hive QL: Joining Tables, Dynamic Partitioning, Custom Map/Reduce Scripts

 Hive Script, Hive UDF

 Hive Persistence formats

 Loading data in Hive - Methods

 Serialization & Deserialization

  Handling Text data using Hive

  Integrating external BI tools with Hadoop Hive

 What Is Spark

 Spark Ecosystem

 Spark Components

 What Is Scala

 Programming Spark

What You Get?

 Learn from our comprehensive collection of project case-studies, hand-picked by industry experts, to give you an in-depth understanding of how data science moves industries like telecom, transportation, e-commerce & more.

  1. Global Sales Store Data Analytics - WallMart
  2. Service Calls & Engineers Utilization Data Analytics – HCL Services
  3. Clinical Data Analytics of Cancer Patients Diagnosis & Medication – Global Health Care
  4. Data Analytics of Training & Development Program of Defense Forces – Indian Navy ...many more...

  You will be having the opportunity of 10-15 Hrs e-learning exercises along with instructor-led-training which enable candidates to get the maximum out of the subjects and empowering them to build logics to hand any new requirement.

 This program has been designed in collaboration with some of the most influential analytics leader and top academician in data science.


RAJINDER

 Professional with over 18+ years of experience.
 Specialization : Big Data & Hadoop, SAS, R, Python, MS Excel
 Companies worked with : HCL, NIIT, IBM, Tata AIG, CSC, BHEL, AIR FORCE, INDIAN NAVY

Final Outcome

 Thanks to the digital revolution that is sweeping the world and India in particular, data scientists are now the most sought-after professionals by big corporations as well as startups. And companies across industries are rewarding good data analysts and scientists with desirable career growth and salaries.

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Invest Now in a Data Science Career

The field of data science is thriving as it is proving to be effective not just across industries but also across departments within organizations.

In-Demand Skills

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High Salaries

Data scientists make around 75 Lakhs on average.



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Shortage of Data Scientists

India alone will need around 2,00,000 data scientists by 2020



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