Big Data Analyst

Learn Hadoop & Big Data Analytics Course Singapore

Big Data Analysis Overview

Big Data Analytics Course Singapore help businesses to organize their data to find new opportunities to improve in. By using Big Data, the delegate will be able to identify any issues and solve them efficiently.

The delegate will also have the confidence to make changes within the business which will result in higher profits and more satisfied clients.

About Course: The Big Data Analytics courses will help delegates learn the methods and tools to collect large amounts of data when making business decisions. By using these techniques, the delegate will be able to improve the process of decision-making, cost reduction and the improvement of products.

Hadoop is the cloud computing platform data scientists use to perform highly paralleled operations on big data. You will learn in this course that:
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  • How to analyze data using Pig, Hive and YARN
  • How to configure the Hadoop distributed file system (HDFS) perform processing
  • Ingestion using Map Reduce Apache Hive is a tool of choice for many data scientists because it allows them to work with SQL, a familiar syntax, to derive insights from Hadoop, reflecting the information that businesses seek to plan effectively.

This course shows how to use Hive to process data, structure and optimize your data. The course will also show how to use HUE, the Hadoop user interface, to leverage HiveQL when analyzing data.

Duration: 4 Days

Venue: 10 Anson Road, 26-08A International Plaza, Singapore 079903

Target Student: All professional who work late or overtime, have back logs of work, and not punctual on time.

Bigdata Analysis Course  Big Data Training Course Outline

Module 1: Big Data Basics

  • Understanding Hadoop fundamentals
  • Introduction to Pig
  • Basic data analysis with Pig
  • Processing Complex data with Pig
  • Multi Dataset operations with Pig

Module 2: Optimising Data

  • Pig troubleshooting and Optimization
  • Introduction to Hive and Impala
  • Quering with Hive and Impala
  • Data Management
  • Data Storage and Performance

Module 3: Analysis of Data

  • Relational Data Analysis
  • Working with Impala
  • Analyzing Complex Data and Text with Hive
  • Hive Optimization

Module 4: Tools for Data Analysis

  • Extending Hive
  • Choosing the Best Tool for the Job
  • Use cases
  • Calculate Best possible location
  • Analyzing mp3 files

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