Table of Contents: 1. Techniques to Work with Big Data A) Artificial Intelligence B) Machine Learning C) Deep Learning D) Data Science 2. Data Science Workflow Step 1: Identifying Business Needs Step 2: Data Ingestion Step 3: Preparing Data Step 4: Analyzing Data Step 5: Sharing Data Insights 3. Roles on a Data Science Team A) Platform Administrators B) Data Engineers C) Data Scientists D) Data Analysts 4. Big Data Use Cases in Different Industries A) Oil, Gas and Energy B) Health and Life Sciences C) Retail D) Telecom E) Financial Services F) Media and Entertainment

Table of Contents: 1. What is Distributed Computing 2. Types of Big Data Processing A) Batch Data B) Streaming Data 3. Types of Data Storage Systems A) Data Warehouse B) Data Lakes C) Lakehouse Platform

Table of Contents: 1. How Big Data is Generated A) Human-Generated B) Machine-Generated C) Organization-Generated 2. What Makes Big Data “Big” A) Volume B) Velocity C) Variety 3. Types of Big Data A) Structured B) Unstructured C) Semi-Structured