This course is divided into threemodules.

Module 1: Fundamental Big Data

This module provides a high-level overview of essential Big Data topic areas. A basic understanding of Big Data from business and technology perspectives is provided, along with an overview of common benefits, challenges, and adoption issues. The following primary topics are covered:

  • Fundamental Terminology and Concepts
  • A Brief History of Big Data
  • Business Drivers leading to Big Data Innovations
  • Characteristics of Big Data
  • Benefits of Adopting Big Data
  • Challenges and Limitations of Big Data
  • Basic Big Data Analytics
  • Big Data and Traditional Business Intelligence and
  • Data Warehouses
  • Big Data Visualization
  • Common Adoption Issues
  • Planning for Big Data Initiatives
  • New Roles Introduced by Big Data Projects
  • Emerging Trends

Module 2: Big Data Analysis & Technology Concepts

This module explores a range of the most relevant topics that pertain to contemporary analysis practices, technologies and tools for Big Data environments. The course content does not get into implementation or programming details, but instead keeps coverage at a conceptual level, focusing on topics that enable participants to develop a comprehensive understanding of the common analysis functions and features offered by Big Data solutions, as well as a high-level understanding of the back-end components that enable these functions. The following primary topics are covered:

  • Big Data Analysis Lifecycle (from business case evaluation to data analysis and visualization)
  • A/B Testing, Correlation
  • Regression, Heat Maps
  • Time Series Analysis
  • Network Analysis
  • Spatial Data Analysis
  • Classification, Clustering
  • Outlier Detection
  • Filtering (including collaborative filtering & content-based filtering)
  • Natural Language Processing
  • Sentiment Analysis, Text Analytics
  • File Systems & Distributed File Systems, NoSQL
  • Distributed & Parallel Data Processing,
  • Processing Workloads, Clusters
  • Cloud Computing & Big Data
  • Foundational Big Data Technology Mechanisms

Module 3: Big Data Lab

This course module presents participants with a series of exercises and problems designed to test their ability to apply knowledge of topics covered previously in course modules 1 and 2. Completing this lab will help highlight areas that require further attention, and will further prove hands-on proficiency in Big Data analysis and technology and practices as they are applied and combined to solve real-world problems.

As a hands-on lab, this course provides a set of detailed exercises that require participants to solve a number of inter-related problems, with the goal of fostering a comprehensive understanding of how Big Data environments work from both front and back-ends, and how they are used to solve real-world analysis and analytics problems.

For instructor-led delivery of this lab course, the Certified Trainer works closely with participants to ensure that all exercises are carried out completely and accurately. Attendees can voluntarily have exercises reviewed and graded as part of the class completion.