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Data Engineering Foundations

via LinkedIn Learning

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Overview

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Learn the key facets of data engineering, from its place in the data science realm, to the specific tasks and skills every data engineer should possess.

Syllabus

Introduction
  • What is data engineering?
1. Introduction to Data Engineering
  • Introduction to data engineering
  • Data engineer vs. data scientist
  • Essential tools for data engineering
2. Databases and Dataframes
  • Intro to databases and their types
  • Understanding database schema
  • Distributive computing
3. Data Engineering Tools
  • MapReduce and Hadoop
  • Hive
  • Spark
  • Airflow
4. ETL Pipelines
  • Sources of data extraction
  • Data extraction from a PostgreSQL database
  • Challenge: Data extraction
  • Solution: Data extraction
  • Transforming data
  • Challenge: Transforming data
  • Solution: Transforming data
  • Loading data into a DB
  • Challenge: Loading data
  • Solution: Loading data
  • Scheduling ETL pipeline using Airflow
Conclusion
  • Next steps

Taught by

Ben Sullins

Reviews

4.6 rating at LinkedIn Learning based on 4556 ratings

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