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INTRODUCTION TO BIG DATA


Course type

Certification Foundation

Course number

029

Duration

3 Days

Overview

What is Big Data? + Key Reasons to Learn Big Data Analytics starting with a vendor-agnostic approach:

This Intro to Big Data is a unique approach to help you act on data for real business gain – not what a tool can do, but what you can do with the output from the tool.  Big data as defined by Wiki is a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications.

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.

 

Recommended Experience:

  • Working knowledge of the Microsoft Windows platform and basic database concepts

What you'll learn

  • 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

Who should attend

  • 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

 

All-Inclusive: After-Course Coaching for Real-World Application:

Learning Tree is with you from the beginning of your planning until you return to your job ready to apply your new skills – with instructor coaching to answer real-world big data implementation challenges.

 

Take Your Big Data Course Online or In-person:

Schedules are busy, but big data training online makes it easy to level-up your career. If you need Big Data online training, we’ve got you covered. Our AnyWare course delivery option gives you the advantages of a live classroom right from the comfort of your computer screen – no matter where you are.

Pre-requis

Outline

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

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

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

Enabling analytic innovation

  • Focusing on business importance
  • Framing the problem
  • Selecting the correct tools
  • Achieving timely results
  • Selecting suitable vendors and hosting options
  • Balancing costs against business value
  • Keeping ahead of the curve

 

Location Dates Status

 

IN CLASSROOM OR ONLINE

PRIVATE TEAM TRAINING

STANDARD

$3895

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GOVERNMENT

$3895


Not applicable