BEST BIG DATA HADOOP TRAINING IN LUCKNOW

BIG DATA HADOOP TRAINING IN LUCKNOW

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Big data has potential to improve and make faster and more intelligent decisions. The data is collected from number of resources and then captured and analyzed can help number of companies to solve problem. Big Data is a growing term that describes an amount of structured, semi structured and unstructured data. EME Technologies is the best company that provides 6 weeks/months industrial training in Lucknow. Big Data is usually characterized by 3Vs i.e. volume, variety and velocity of data. Voluminous data can come from different source and may be raw or preprocessed. Data may also exist in a wide variety of file types such as SQL and big data is analyzed quickly and accurately. Now a day’s demand of big data is increasing due to the increase in usage percentage of digital and electronic devices. More than 90% of world’s data is stored in last two years. Most of the companies are turning to big data so that there is a increase in number of vacancies for big data jobs. At Promosys Technology you may get chance to work on projects like Home automation, android control robot, dc motor control, railway level gate control, voice control robotic vehicle, wireless robotic alarm, military spying and bomb disposal robot and many more.


BIG DATA HADOOP TRAINING IN LUCKNOW

  •   INTRODUCTION OF BIG DATA
  •   Basics of Big data
      Big Data Generation
      Big Data Introduction
      Big Data Architecture
      Understand Big data Problem
      Big data Management Approch
      treditional and Current Data storing approch
      Understand various data formats and data units
      Big data With Industry Requirments
      Big Data Chalanges
  •  HADOOP ENVIRONMENT
  •  Understand Hadoop Enviorment
      requirment of hadoop
      Importance of Data Analytics
      Setting up hadoop Enviorment
      Hadoop advantages over RDMS
  •   HADOOP CLUSTER & FILE SYSTEM
  •   Explaining Various file systems
      Hdfs GFS, POSIX, GPFS
      explain clustring methetology
      Master Nodes and slave nodes
     
  •  HADOOP HIVE
  •   Understand Data Ware Housing
      Requirement of Data Ware housing
      Data Ware housing with Hive
      Understand Hive environment
      working with Hive Query Language
      Perform DDL approach Through Hive
      Perform DML approach through Hive
  •   HADOOP PIG
  •   Introduction of PIG
      Requirement of Pig
      Working with pig Script
      Running and managing Pig Script
      Perform Streaming Data Analytics through PIG
      Pig Advantages and Disadvantages
  •  HADOOP FILE SYSTEM(HDFS) & HADOOP ARCHITECTURE
  •   Working on hdfs File System
      Creating lib and accessing lib from HDFS
      hadoop commands make dir,delete dir etc
      working with web console
  •   HADOOP MAPREDUCE
  •  Introduction of Map Reduce
      mapreduce programming and word count
      mapreduce nodes job tracker and task tracker
      running Mapreduce program through web console
  •  HADOOP JAQL
  •   Introduction of JAQL Approch
      Understand information stream
      Understand Information ocean
      Working with JAQL Language
  •   HADOOP FLUME & SQOOP
  •   Understand Flume methodology
      Requirement of flume
      flume advantages
      working lab with flume
      introduction of Sqoop
      Requirement of sqoop
      advantages of sqoop
  •   HADOOP BIG R & OZIE
  •   Introduction of BIG R
      Advantages of BIG R
      Working Lifecycle of ozie
      understand ozie data flow
      ozie setup and requirement
      understand ozie scheduling
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