Components of a Big Data and AI Solution Introduction

This hands-on Introduction to Big Data training provides a unique approach to help you act on data for real business gain. The focus is not on what a tool can do, but on what you can do with the output from the tool. By integrating Big Data training with your data science training you gain the skills you need to store, manage, process, and analyze massive amounts of structured and unstructured data to extract meaningful insights.

Attend this Introduction to Big Data in one of three formats - live, instructor-led, on-demand or a blended on-demand/instructor-led version.

Introduction to Big Data Training Delivery Methods

• In-Person

• Online

• On-Demand

Introduction to Big Data Training Course Benefits

• Store, manage, and analyze unstructured data
• Select the correct big data stores for disparate data sets
• Process large data sets using Hadoop and Spark 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

• Leverage continued support with after-course one-on-one instructor coaching and computing sandbox

Introduction to Big Data Course Outline

Module 1: 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

Module 2: 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
• 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
• Messaging with Kafka
• Implementing polyglot data store solutions
• Aligning business goals to the appropriate data store

Module 3: 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
• 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
• Accelerating process with Spark

Handling streaming data

• Comparing real–time processing modelsLeveraging Storm to extract live events
• Leveraging Spark Streaming to extract live events
• Combining streaming and batch processing in a Lambda architecture

Module 4: 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 metadata in the Hive Metastore
• Performing queries with HiveQL
• Investigating Hive file formats

Creating business value from extracted data

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

Module 5: Developing a Big Data Strategy

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

Module 6: Implementing a Big Data Solution

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

Introduction to Big Data Training Bundle

Training Bundle Benefits

This product offers access to:

• 2 on-demand courses and 5 eBooks that have been mapped directly to the objectives of the 3-day introduction course.
• At any time during your annual access to this offering, you may attend one of our 1-day course events focused specifically on Big Data Technologies, Trends & Insights Training .

Training Bundle On-Demand Contents

On-Demand Courses

• Mastering Big Data Analytics with PySpark
• Master Big Data Ingestion and Analytics with Flume, Sqoop, Hive and Spark

eBooks

• Artificial Intelligence for Big Data
• Big Data Architect's Handbook
• Modern Big Data Processing with Hadoop
• Big Data Processing with Apache Spark
• Practical Big Data Analytics

Unlimited Access Introduction to Big Data Premium Blended Training

Premium Blended Training Benefits

The Premium Blended Training offers access to:

• 2 on-demand courses and 5 eBooks that have been mapped directly to the objectives of the 3-day course.
• At any time during your annual access to this offering, you may attend one of our 1-day course events focused specifically on Big Data Technologies, Trends & Insights Training .
• Enrolling in this bundle also grants you access to any of our multi-day Introduction to Big Data Training course events.

Premium Blended Training On-Demand Contents

On-Demand Courses

• Mastering Big Data Analytics with PySpark
• Master Big Data Ingestion and Analytics with Flume, Sqoop, Hive and Spark

eBooks

• Artificial Intelligence for Big Data
• Big Data Architect's Handbook
• Modern Big Data Processing with Hadoop
• Big Data Processing with Apache Spark
• Practical Big Data Analytics