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LT-1250

Introduction to Big Data

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Description

In this hands-on Introduction to Big Data Course, learn to leverage big data analysis tools and techniques to foster better business decision-making – before you get into specific products like Hadoop training (just to name one). Learn ways of storing data that allow for efficient processing and analysis, and gain the skills you need to store, manage, process, and analyze massive amounts of unstructured data to create an appropriate data lake.

Key Features of this Intro to Big Data Training:

  • Learn Big Data Analytics
  • After-course instructor coaching benefit
  • Learning Tree end-of-course exam included
  • After-course computing sandbox included

You Will Learn How To:

  • Store, manage, and analyze unstructured data
  • Select the correct big data stores for disparate data sets
  • Process large data sets using Hadoop to extract value
  • Query large data sets in near real time with Pig and Hive
  • Plan and implement a big data strategy for your organization

Outline

 

Introduction to Big Data

Defining Big Data

  • The four dimensions of Big Data: volume, velocity, variety, veracity
  • Introducing the Storage, MapReduce and Query Stack

Delivering business benefit from Big Data

  • Establishing the business importance of Big Data
  • Addressing the challenge of extracting useful data
  • Integrating Big Data with traditional data

Storing Big Data

Analyzing your data characteristics

  • Selecting data sources for analysis
  • Eliminating redundant data
  • Establishing the role of NoSQL

Overview of Big Data stores

  • Data models: key value, graph, document, column–family
  • Hadoop Distributed File System
  • HBase
  • Hive
  • Cassandra
  • Hypertable
  • Amazon S3
  • BigTable
  • DynamoDB
  • MongoDB
  • Redis
  • Riak
  • Neo4J

Selecting Big Data stores

  • Choosing the correct data stores based on your data characteristics
  • Moving code to data
  • Implementing polyglot data store solutions
  • Aligning business goals to the appropriate data store

Processing Big Data

Integrating disparate data stores

  • Mapping data to the programming framework
  • Connecting and extracting data from storage
  • Transforming data for processing
  • Subdividing data in preparation for Hadoop MapReduce

Employing Hadoop MapReduce

  • Creating the components of Hadoop MapReduce jobs
  • Distributing data processing across server farms
  • Executing Hadoop MapReduce jobs
  • Monitoring the progress of job flows

The building blocks of Hadoop MapReduce

  • Distinguishing Hadoop daemons
  • Investigating the Hadoop Distributed File System
  • Selecting appropriate execution modes: local, pseudo–distributed and fully distributed

Handling streaming data

  • Comparing real–time processing models
  • Leveraging Storm to extract live events
  • Lightning–fast processing with Spark and Shark

Tools and Techniques to Analyze Big Data

Abstracting Hadoop MapReduce jobs with Pig

  • Communicating with Hadoop in Pig Latin
  • Executing commands using the Grunt Shell
  • Streamlining high–level processing

Performing ad hoc Big Data querying with Hive

  • Persisting data in the Hive MegaStore
  • Performing queries with HiveQL
  • Investigating Hive file formats

Creating business value from extracted data

  • Mining data with Mahout
  • Visualizing processed results with reporting tools
  • Querying in real time with Impala

Defining a Big Data strategy for your organization

  • Establishing your Big Data needs
  • Meeting business goals with timely data
  • Evaluating commercial Big Data tools
  • Managing organizational expectations

Developing a Big Data Strategy

Enabling analytic innovation

  • Focusing on business importance
  • Framing the problem
  • Selecting the correct tools
  • Achieving timely results

Implementing a Big Data Solution

  • Selecting suitable vendors and hosting options
  • Balancing costs against business value
  • Keeping ahead of the curve

 

PreRequisites

 

In order to succeed in this course, you should have working knowledge of the Microsoft Windows platform and basic database concepts

Audience

 

This course is geared toward anyone needing to implement, enhance your big data environment and looking to advance their analytics career by ensuring foundational knowledge.

Typical job roles include: Project Managers and IT Managers, Database Administrators & Data Architects, Developers & SQL Developers, Data Scientists & Business Intelligence.

$2650.00 List Price

3 Days Course

Class Dates

Request a Date or a Private Class below.


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