Introduction to Big Data
Virtual ClassroomLearning Style
3 DaysCourse Duration
About Individual Course:
Learn to leverage big data analysis tools and techniques to foster better business decision-making with this big data introduction training. In this course, you will 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.
- 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
- Working knowledge of the Microsoft Windows platform
Virtual Instructed-Led 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
- Amazon S3
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
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
Implementing a Big Data Solution
- Selecting suitable vendors and hosting options
- Balancing costs against business value
- Keeping ahead of the curve
|Learning Style||Virtual Classroom|
|Course Duration||3 Days|
Frequently Asked Questions About Virtual Instructor-Led Courses
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Will I get my certificate upon completion?
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