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LinkedIn Learning

ETL in Python and SQL

via LinkedIn Learning

Overview

Gain the knowledge you need to build data pipelines in a data-driven world.

Syllabus

Introduction
  • Create an ETL in Python and SQL
  • Tools used in this course
1. What Are ETLs?
  • What are ETLs and how do you create them?
  • ETL process overview
  • Exploring your data with pandas (Python) and SQL
  • Understanding your data
  • Challenge: Reading data using Python
  • Solution: Reading data using Python
2. Extracting and Transforming Data with Python
  • Loading data from different sources
  • Extracting your data
  • Cleaning, preprocessing data, and data formatting
  • Standardization, handling duplicates, and missing values
  • Challenge: Extract and transform data using pandas
  • Solution: Extract and transform data using pandas
3. Loading Data into Target Systems
  • Introduction to data warehouses and data lakes
  • Loading data into relational databases
  • Data quality checks and validation with SQL
  • Challenge: Transform the data and remove duplicates and nulls
  • Solution: Transform the data and remove duplicates and nulls
4. Automating ETL Jobs: Scheduling ETL Jobs with Python
  • Querying your data with SQL
  • Scheduling ETL jobs with Airflow: Part 1
  • Scheduling ETL jobs with Airflow: Part 2
  • Challenge: Load the data into a database and automate
  • Solution: Load the data into a database and automate
Conclusion
  • Expand your knowledge of ETLs

Taught by

Jennifer Ebe

Reviews

4.7 rating at LinkedIn Learning based on 478 ratings

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