Big Data (Technical)
PREREQUISITE:
- Participants should be very fluent in computer usage and its general technological concepts.
- A previous course in statistics or probability is an edge to the course.
COURSE OVERVIEW:
Data sets that have the potential to grow, even maximally, have to be managed effectively. This course provides the needed knowledge and training to use new Big Data tools and techniques to allow for more efficient and sustained data processing and analysis for informed business decision-making. It also offers new and innovative ways of storing information for the improvement of your data cache. And more importantly, participants will gain understanding and knowledge in learning how to store, manage, process and analyze huge amounts of unstructured data.
COURSE CURRICULUM:
- Introduction to Big Data
- Defining Big Data
- Delivering business benefits from Big Data
- Discussing business importance of Big Data
- Outlining the challenges and their corresponding solutions in extracting useful data
- Incorporating Big Data with traditional data
- Storing Big Data
- Choosing data sources for data analysis
- Eliminating recurrent data
- Establishing the duty of NoSQL
- Overview of Big Data stores
- Overview of data models such as key value, graph, document, column-family
- Hadoop Distributed File System
- HBase
- Hive
- Cassandra
- Hypertable
- Amazon S3
- BigTable
- DynamoDB
- MongoDB
- Redis
- Neo4J
- Selecting correct data stores based on your data characteristics
- Moving code to data
- Coordinating business objectives to its appropriate data stores
- Transforming Big Data
- Connecting data to the programming framework
- Connecting and squeezing data from its storage
- Converting data for further processing
- Classifying data in preparation for Hadoop MapReduce
- Producing Hadoop MapReduce job components
- Delivering data processing across server farms
- Assessing the progress of job flow
- Choosing the most suitable execution modes
- Comparing real-time processing models
- Balancing Storm to extract live events
- Speedy processing using Spark and Shark
- Tools and Techniques to Analyze Big Data
- Connecting with Hadoop in Pig Latin
- Implementing commands using the Grunt Shell
- Integrating increased level of processing
- Continuing process of data in the Hive MegaStore
- Employing queries with HiveQL
- Assessing Hive file formats
- Creating business value from extracted data
- Obtaining processed outputs through the use of available reporting tools
- Investigating in real time using Impala
- Designing a Big Data Strategy
- Designing a Big Data strategy for your business
- Implementing your Big Data needs
- Addressing business objectives using timely data
- Assessing commercial Big Data tools
- Administering organizational expectations
- Allowing use of innovations in analytics
- Directing innovations on business importance
- Constructing the problem
- Choosing the appropriate tools for the problem
- Obtaining timely outputs
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- Integrating a Big Data Solution
- Choosing appropriate vendors and hosting options
- Harmonizing business values and costs
- Maintaining lead of the curve
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