Data Engineering for Managers

Chapter 1. Defining Data Engineering

• Data is King
• What is Data Engineering
• The Data-Related Roles
• The Data Engineer Role
• Core Skills and Competencies
• What is Data Wrangling (Munging)?
• Typical Data Processing Pipeline
• Data Discovery Phase
• Data Harvesting Phase
• Data Priming Phase
• Exploratory Data Analysis
• Model Planning Phase
• Model Building Phase
• Communicating the Results
• Production Roll-out
• Data Logistics and Data Governance
• Data Processing Workflow Engines
• Data Lineage and Provenance
• The Traditional Client–Server Processing Pattern
• Enter Distributed Computing
• Data Physics
• Data Locality (Distributed Computing Economics)
• The CAP Theorem
• Mechanisms to Guarantee a Single CAP Property
• Eventual Consistency
• What is Apache Spark
• The Spark Platform
• Languages Supported by Spark
• Running Spark on a Cluster
• The Resilient Distributed Dataset (RDD)
• The Lineage Concept
• Datasets and DataFrames
• Data Partitioning
• Data Partitioning Diagram
• Python's Value
• Python on AWS
• What is Serverless Computing?
• How Functions Work
• What is AWS Glue?
• Summary