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BIG DATA Training

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BIG DATA Syllabus

Big Data is a term applied to data sets whose size or type is beyond the ability of traditional relational databases to capture, manage and process the data with low latency. Big data has one or more of the following characteristics: high volume, high velocity or high variety. Artificial intelligence (AI), mobile, social and the Internet of Things (IoT) are driving data complexity through new forms and sources of data. For example, big data comes from sensors, devices, video/audio, networks, log files, transactional applications, web, and social media — much of it generated in real time and at a very large scale.


Analysis of big data allows analysts, researchers and business users to make better and faster decisions using data that was previously inaccessible or unusable. Businesses can use advanced analytics techniques such as text analytics, machine learning, predictive analytics, data mining, statistics and natural language processing to gain new insights from previously untapped data sources independently or together with existing enterprise data.


Big Data Training modules

Why Big Data?
  • What is Big Data?
  • Use of Big Data
  • Different types of Databases:
  • OLAP & OLTP
  • Data
  • Hadoop major components
  • How Map reduce work?
  • HDFS
  • Reading and writing data from and to from HDFS
  • components in HDFS
  • Hadoop 1 and Hadoop 2
  • Hadoop1 Architecture
  • Hadoop2 Architecture
  • Map reduce V1 components & Responsibilities:
  • Job Tracker
  • Task Tracer
  • Map reduce in Hadoop2
  • Limitations and Advantages of Hadoop1 & 2
  • what is Yarn?
  • Yarn Architecture
  • Core Components in Yarn:
  • Application Master
  • Resource Manager
  • NodeManager
  • Container
  • How it Work?
  • Writing Map reduce Programs
  • Introducing UNIX Commands

  • HIVE

    Why and What HIVE?
  • Hive Architecture:
  • Metastore
  • HiveQL
  • Working on Hive
  • Hive Data types:
  • Column Types
  • String typesv
  • Timestamp
  • Literals
  • Complex Types
  • Create Databases and Operations
  • Partitioning:
  • Static Partition
  • Dynamic partition
  • Hive Bucketing
  • Querying a Table:
  • To filter on conditions
    Arithmetic and Logical Operators
    Complex Operators
    Built-in Functions
  • Aggregate functions
  • Joins:
  • Left outer join
    Right Outer join
    Full Outer Join
    SubQuery
    File Format in hive
  • Program from Java to hive
  • Program

  • PIG

    Big Data Analytics Using Pig
  • Pig features
  • Pig Vs Mapreduce
  • Pig Architecture
  • Pig Components
  • How pig Work?
  • Data Model
  • Tuple, Bag, Relation
  • Pig - Execution Modes
  • LOAD file
  • Pig Latin - Data Types
  • Complex Data Types
  • Type construction operators
  • Relational Operators
  • Join Operator:
  • Self-join
  • Inner-join
  • Outer-join: left join, right-join, and full join
  • Using Multiple Keys:
  • Cross Operator
    Union Operator
    Split Operator
    Filtering
  • Distinct Operator
  • Foreach operator
  • Order By
  • Limit Operator
  • Built in eval functions
  • String functions
  • Date Time functions
  • Program Exercise

  • R PROGRAMMING

    OVERVIEW OF R
  • Features of R
  • Basic Syntax
  • R Data Types
  • R-variables
  • R-variables
  • R-Operators
  • Conditional Statements
  • R-switch statement
  • R-Loops
  • R-functions
  • R-Strings
  • R-Vectors
  • R-lists
  • R-Matrices
  • R Arrays
  • R Factors
  • R Dataframes
  • R Packages
  • Melting and casting
  • R using Files
  • R JSON file
  • R-databases
  • Pie Charts
  • Bar Charts
  • Boxplots
  • Histograms
  • Mean, Median, Mode
  • Line Graph
  • Scatter plots

  • HBASE

  • What is HBase?
  • How it Works?
  • HBase Architecture
  • HBase Features
  • Table Creation
  • Describe and Alter
  • DML: Data Manipulation Language
  • Table scope operators
  • Exercise
  • Sqoop
  • Sqoop introduction
  • Import Data
  • Export Datav
  • Sqoop JOB
  • codegen
  • Eval
  • List Databases
  • List tables

  • Spark

  • what is Apache Spark?
  • How it Works?
  • Architecture
  • RDD
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