Delegates will have computer based examples and case study exercises to undertake with relevant big data tools
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- Big data fundamentals
- Big Data and its role in the corporate world
- The phases of development of a Big Data strategy within a corporation
- Explain the rationale underlying a holistic approach to Big Data
- Components needed in a Big Data Platform
- Big data storage solution
- Limits of Traditional Technologies
- Overview of database types
- The four dimensions of Big Data
- Big data impact on business
- Business importance of Big Data
- Challenges of 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 and extracting data from database
- Transforming and preparation data for processing
- Using Hadoop MapReduce for processing distributed data
- Monitoring and executing Hadoop MapReduce jobs
- Hadoop distributed file system building blocks
- Mapreduce and Yarn
- Handling streaming data with Spark
- Big data analysis tools and technologies
- Programming Hadoop with Pig Latin language
- Querying big data with Hive
- Mining data with Mahout
- Visualizing and reporting tools
- Big data in business
- Managing and establishing Big Data needs
- Business importance of Big Data
- Selecting the right big data tools for the problem
- Big data fundamentals
- What is Data Ware House?
- Difference between OLTP and Data Ware Housing
- Data Acquisition
- Data Extraction
- Data Transformation.
- Data Loading
- Data Marts
- Dependent vs Independent data Mart
- Data Base design
- Introduction.
- Software development life cycle.
- Testing methodologies.
- ETL Testing Work Flow Process.
- ETL Testing Responsibilities in Data stage.
- Big Data and its role in the corporate world
- The phases of development of a Big Data strategy within a corporation
- Explain the rationale underlying a holistic approach to Big Data
- Components needed in a Big Data Platform
- Big data storage solution
- Limits of Traditional Technologies
- Overview of database types
NoSQL Databases
Hadoop
Map Reduce
Apache Spark
- Delegates should have an awareness and some experience of storage tools
- An awareness of handling large data sets
14 hours (usually 2 days including breaks)
