Course Objectives of Big Data Engineering for Analytics
Understand the fundamental characteristics, storage, analysis techniques, and the relevant distributions
Gain expertise with the fault-tolerant computing framework
Construct configurable and executable tasks
Understand the nuances of writing functional programs
Understand various data processing, querying, and persistence available for usage in RDD’s context.
Perform tasks such as filtering, selection, and categorization.
Introduction to Data Science, Data Engineering, and Big Data
Data Scientist vs. Data Engineer
Different Roles in Data Engineering
Core Data Engineering Skills and Resources
Understand Big Data from an Analytics Perspective
Architectural Viewpoints in Big Data
Reference Architecture Conceptual View
Reference Architecture Logical View
Oracle Product Mapping View
The Hadoop Ecosystem for Big Data
Distributed File Storage
NoSQL Databases for Big Data
Spark and Functional Programming for Big Data
Spark and Resilient Distributed Data Sets
Spark QL for Big Data
Spark and Real-Time Stream Processing
Management of Big Data initiatives
Case study
Project Requirement Elaboration
Project and Assessment
Project Demonstration
Report Submission and Presentations
Dates | Venues | Price | Details |
---|
Write a public review