Bigdata Training

Best Bigdata Training in Chennai


Troy Infotech is the best BigData training institute in Chennai with a very high level infrastructure and laboratory facility. We feel proud by announcing that Troy Infotech prepares thousands of candidates as BigData professionals by providing training at reasoanble fees structure which is sufficient for the students to attend the BigData classes effectively. Our classes will be conducted on both weekdays & weekends with flexible timings for the students.Join our BigData training in Chennai provided by Troy Infotech & increase your portability, maintainability, compatibility, capability, reliability, efficiency and usability.BigData job is becoming dream job for many professionals now. In Our BigData training course in Chennai, we train our students in a way that they become the preferred candidate among the others in IT sector. This course helps any businessman and worker to increase productivity and efficiency in their career. BCA / MCA / B.Sc(IT) / M.Sc(IT) / B.Tech(All stream) are basically the eligibility criteria for the students for doing this testing course.

 

Our BigData trainers are BigData certified experts and experienced working professionals from the industry with hands on real time multiple BigData projects knowledge. We have designed our BigData course content and syllabus based on students requirement for achieving everyone’s career goal. We are providing the excellent BigData training in Chennai with placement assurance for students.

 

Course Description


Big Data actually refers to the analysis of large data sets to find trends, correlations or other insights not visible with smaller data sets or traditional processing methods. The exponential growth of internet-connected devices and its sensors is a major contributor to the massive data and the storage, processing and analysis can require hundreds or thousands of computers. An example of big data in use is seen in the development of the autonomous vehicle. The sensors on self-driving vehicles are capturing millions of data points that can be analyzed to help in improving performance and avoid accidents.

 

Our Troy Infotech’s Big Data training topics covered are Big Data Overview, Use Cases, Data Analytics Process, Data Preparation, Tools for Data Preparation, Hands on Exercise by Using SQL and NoSql DB’s, Hands on Exercise in Usage of Tools, Data Analysis Introduction, Classification, Data Visualization using R, Big Data Hadoop & Many more

 

Course Objective


Students will understand the actual concept of Big Data.
They will understand the use cases, Data Analytics, Data Preparation with Data Visualization concepts.
They will Understand the various parts of Hadoop condition, for instance, Hadoop 2.7, Impala, Yarn, MapReduce, Pig, Hive, HBase, Sqoop, Flume, and Apache Spark
They will Learn Hadoop Distributed File System (HDFS) and YARN building, and make sense of how to function with them for limit and resource organization
They will Understand MapReduce and its qualities and retain advanced MapReduce thoughts

Bigdata Training In Chennai Course Syllabus:


Introduction

  • Big Data Overview
  • What is Big Data Analytics
  • Necessity for Big Data Analytics
  • Role of a Data Analyst
  • What is Data Science
  • Necessity for Data Science
  • Role of Data Scientist

Use Cases

  • Finance
  • Retail
  • Advertising
  • Defense and Intelligence
  • Telecommunications and Utilities
  • Healthcare and Pharmaceuticals

Data Analytics Process

  • Preparation
  • PreProcessing
  • Analysis
  • Post Processing

Data Preparation

  • Planning
  • Data Collection
  • Data Selection

Tools for Data Preparation

  • Introduction to SQL DB’s
  • Introduction to NoSql DB’s
  • Key / Value pair
  • MongoDB
  • Cassandra
  • Graph DB’s (Neo4j)
  • Hands on Exercise on Using SQL and NoSql DB’s

HADOOP BIG DATA ECOSYSTEM

  • 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 for existing Data Analytics Architecture
  • Comparison of traditional data management systems including Big Data management systems
  • Evaluating key framework requirements for Big Data analytics
  • Hadoop Ecosystem & Hadoop 2.x core components
  • Explain the relevance of real-time data
  • Explain on how to use big and real-time data as a Business planning tool

HADOOP CLUSTER-ARCHITECTURE-CONFIGURATION FILES

  • Hadoop Master-Slave Architecture
  • The Hadoop Distributed File System with Concept of data storage
  • Explain different types of cluster setups like Fully distributed/Pseudo etc
  • Hadoop cluster set up – Installation
  • Hadoop 2.x Cluster Architecture
  • A Typical enterprise cluster with Hadoop Cluster Modes
  • Understanding cluster management tools like Cloudera manager/Apache ambary

HDFS & MAPREDUCE

  • HDFS Overview & Data storage in HDFS
  • Get the data into Hadoop from local machine like 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)

Data Preparation – Import/Export

  • Sqoop
  • Flume
  • Hands on Exercise : Usage of Tools

DATA ANALYSIS USING IMPALA

  • Introduction to Impala & Architecture
  • How Impala executes Queries and its importance
  • Hive vs. PIG vs. Impala
  • Extending Impala with User Defined functions

INTRODUCTION TO OTHER ECOSYSTEM TOOLS

  • NoSQL database – Hbase
  • Introduction Oozie

PreProcessing

  • Data Cleaning
  • Data Filtering
  • Data Completion
  • Data Correction
  • Data Standardization
  • Data Transformation
  • Tools for Data PreProcessing
  • Data Preprocessing using Pig
  • Writing Pig Latin scripts and processing data
  • Data Preprocessing using Hive
  • Writing Hive Scripts and processing data
  • Hands on Exercise : Pig and Hive

Data Analysis Introduction

  • Sqoop
  • Recommendation
  • Classification
  • Clustering
  • Mahout

Recommendation

  • Introduction to Recommendations
  • Making recommendations, various techniques
  • Hands on Exercise for Recommendations

SPARK INTRODUCTION

  • Introduction to Apache Spark
  • Streaming Data Vs. In Memory Data
  • Map Reduce Vs. Spark
  • Modes of Spark
  • Spark Installation Demo
  • Overview of Spark on a clusterIntroduction to Apache Spark
  • Streaming Data Vs. In Memory Data
  • Map Reduce Vs. Spark
  • Modes of Spark
  • Spark Installation Demo
  • Overview of Spark on a cluster
  • Spark Standalone Cluster

SPARK: SPARK IN PRACTICE

  • Invoking Spark Shell
  • Creating the Spark Context
  • Loading a File in Shell
  • Performing Some Basic Operations on Files inside the Spark Shell
  • Caching Overview
  • Distributed Persistence
  • Spark Streaming Overview(Example: Streaming Word Count)

SPARK: SPARK MEETS HIVE

  • Analyze Hive and Spark SQL Architecture
  • Analyze Spark SQL
  • Context in Spark SQL
  • Implement a sample example for Spark SQL
  • Integrating Hive and Spark SQL
  • Support for JSON and Parquet File Formats which Implement Data Visualization in Spark
  • Loading of Data
  • Hive Queries through Spark
  • Performance Tuning Tips in Spark
  • Shared Variables: Broadcast Variables & Accumulators

SPARK STREAMING

  • Extract and analyze the data from twitter by using Spark streaming
  • Comparison of Spark and Storm – Overview
  • SPARK GRAPHX
  • Overview of GraphX module in spark
  • Creating graphs with GraphX

IMPLEMENT MACHINE LEARNING USING SPARK

  • Brief introduction to Machine learning framework
  • Implement some of the ML algorithms by using Spark MLLib (ML is not covered in detail in this course, for Machine Learning concept pls refer to Advance Big Data Science course or Machine Learning Specialization course)
  • Spark Standalone Cluster

Classification

  • Classification System Overview
  • Classification process
  • Naive Bayes Classifier
  • Decision Trees
  • Examples of Classification
  • Clustering
  • Clustering basics
  • Hierarchical clustering
  • K-Means clustering
  • Running clustering example
  • Exploring distance measures

Data Visualization using R

  • Language basics
  • Data Frames
  • Vectorized operations on Data Frames
  • Selection
  • Projection
  • Transformation

 

Take A Look At Our Bigdata Training Course


Real-Time Practical Training

You will get the real-time project experience on our training. We provide more practical training classes preferred by the candidates. Our practical oriented training will inspire all the participants.

Assured Placement Assistance

We are the pioneer in providing the assured placement assistance for the participants after their course completion.

Certified Trainers

Learning made easy by our certified trainers who fulfills the needs of the candidates in that particular course. Your knowledge will be transformed into expertise level by our trainers.

Internship Training

We provide internship training effectively for our participants which are highly helpful for their professional career.

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Frequently Asked Questions


Who can attend Bigdata Training Course?

The following can attend this BigData course:

  • Analytics Professionals
  • BI /ETL/DW Professionals
  • Project Managers
  • Testing Professionals
  • Mainframe Professionals
  • Software Developers and Architects
  • Graduates aiming to build a career in Big Data

Why this Course?

  • Big Data is more fastest growing and most promising technology for handling large volumes of data for doing data analytics.
  • This Big Data Hadoop training course will help you to be up and running in the most demanding professional skills.
  • Almost all the top MNC are trying to get into Big Data Hadoop hence there is a huge demand for Big Data professionals.
  • Getting the big data certification from our institute can put you in a different league when it comes to applying for the best jobs.

What will you learn?

You will learn & become expert in the following concepts:

  • Students will understand the actual concept of Big Data.
  • They will understand the use cases, Data Analytics, Data Preparation with Data Visualization concepts.
  • They will Understand the various parts of Hadoop condition, for instance, Hadoop 2.7, Impala, Yarn, MapReduce, Pig, Hive, HBase, Sqoop, Flume, and Apache Spark
  • They will Learn Hadoop Distributed File System (HDFS) and YARN building, and make sense of how to function with them for limit and resource organization
  • They will Understand MapReduce and its qualities and retain advanced MapReduce thoughts
  • They will Ingest data using Sqoop and Flume
  • Get a working knowledge of Pig and its parts

What are the Career Opportunities available in Big data?

The following are the job opportunities you will get:

 

  • Big Data Hadoop – Lead
  • Big Data Developer
  • Big Data Engineer
  • Big Data Architect

What Are The Pre-Requisites For Learning The Bigdata Training Course?

  • Java / C++ prior knowledge / experience
  • Linux / UNIX prior knowledge / experience

TROY Course Duration For Bigdata Training In Chennai

  • Fast Track Training Program (6+ hours daily)
  • Regular Classes (Morning, Day time & Evening)
  • Weekend Training Classes (Saturday, Sunday & Holidays)

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