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Course Outline
- Big Data Fundamentals
- The role of Big Data in the corporate world
- Phases of developing a Big Data strategy within a corporation
- Understanding the rationale behind a holistic approach to Big Data
- Key components required in a Big Data platform
- Big Data storage solutions
- Limits of traditional technologies
- Overview of database types
- The four dimensions of Big Data
- Impact of Big Data on Business
- Business importance of Big Data
- Challenges in extracting useful data
- Integrating Big Data with traditional data
- Big Data Storage Technologies
- Overview of Big Data technologies
- Data storage models
- Hadoop
- Hive
- Cassandra
- MongoDB
- Choosing the right Big Data technology
- Overview of Big Data technologies
- Processing Big Data
- Connecting to and extracting data from databases
- Transforming and preparing data for processing
- Using Hadoop MapReduce to process distributed data
- Monitoring and executing Hadoop MapReduce jobs
- Building blocks of the Hadoop Distributed File System
- MapReduce and YARN
- Handling streaming data with Spark
- Big Data Analysis Tools and Technologies
- Programming Hadoop using the Pig Latin language
- Querying Big Data with Hive
- Data mining with Mahout
- Visualization and reporting tools
- Big Data in Business
- Managing and defining Big Data requirements
- Business importance of Big Data
- Selecting the appropriate Big Data tools for specific problems
Data Warehousing Concepts
- What is a Data Warehouse?
- Difference between OLTP and Data Warehousing
- Data Acquisition
- Data Extraction
- Data Transformation
- Data Loading
- Data Marts
- Dependent vs. Independent Data Marts
- Database Design
ETL Testing Concepts:
- Introduction
- Software Development Life Cycle
- Testing Methodologies
- ETL Testing Workflow Process
- ETL Testing Responsibilities in the Data Stage
Big Data Fundamentals
- The role of Big Data in the corporate world
- Phases of developing a Big Data strategy within a corporation
- Understanding the rationale behind a holistic approach to Big Data
- Key components required in a Big Data platform
- Big Data storage solutions
- Limits of traditional technologies
- Overview of database types
NoSQL Databases
Hadoop
MapReduce
Apache Spark
Requirements
Participants should have a basic awareness and some practical experience with storage tools, as well as an understanding of how to handle large data sets.
14 Hours
Testimonials (1)
trainer's knowledge
