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Introduction to Big Data and Data Analytics

Event Details


After successful completion of this course, participants will understand:

  • Introduction to Big Data-what is 4Vs (volume, velocity, variety and veracity) in Big Data- Generation, extraction and management
  • How Big Data analytic differs from legacy data analytic
  • In-house justification of Big Data
  • Introduction to Hadoop Ecosystem- familiarity with all Hadoop tools like Hive, Pig, SPARC –when and how they are used to solve Big Data problem
  • How Big Data is extracted to analyze for analytics tool-how Business Analysis’s can reduce their pain points of collection and analysis of data through integrated Hadoop dashboard approach
  • Bigdata, Machine Learning, and Artificial Intelligence: Fundamental Concepts

 

Overview of Bigdata:

  • Main characteristics of Big Data-volume, variety, velocity and veracity
  • Data Warehouses – static schema, slowly evolving dataset
  • Hadoop/Spark Based Solutions – no conditions on structure of dataset
  • Typical pattern : HDFS, MapReduce (crunch), retrieve from HDFS
  • Batch- suited for analytical/non-interactive
  • Volume : CEP streaming data
  • Typical choices – CEP products (e.g. Infostreams, Apama, MarkLogic etc)
  • Less production ready – Storm/S4
  • NoSQL Databases – (columnar and key-value): Best suited as analytical adjunct to data warehouse/database

 

Who Should Attend?

Chief Technology Officers, Product Managers, Technical Managers and IT Professionals.

 

Course Duration:

3-day instructor-led training

 

Course Outlines:

  • Big Data Introduction : Hadoop
  • Introduction to Map Reduce /HDFS
  • Spark : In Memory distributed database
  • Storm – Real time processing in Big Data
  • Predictive analytics in Business Intelligence
    • Fundamental Techniques & Machine learning based BI
11 Sep 2017

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