Hands-On Analytics Engineering Project
30mIntermediate2024-06-14
Authors
Connor Dickson
Course details
This course teaches analytics engineers how to pipeline data into the database from an external source for use in visualization. Such tasks are frequently required of the average analytics engineer. The modern company has more access to data than ever before. Analytics engineers are crucial in making that data accessible for stakeholders. In this course, instructor Connor Dickson presents a scenario where you have a working data stack, and a stakeholder has requested that you take existing data from a source, bring it into the database, transform it, and finally visualize it so it provides value and insights.
Skills covered
Data Build Tool (dbt)Data EngineeringPythonData AnalysisProgramming LanguagesData ScienceBusiness Analysis and StrategyBusiness Software and ToolsOpen SourceSoftware DevelopmentOne-Off
Concepts
0. Introduction
- 01 - The era of analytics engineering
- 02 - How to use Codespaces
1. Building an ETL
- 03 - What are ETLs
- 04 - Preparing our Python environment
- 05 - Transforming data in Python
- 06 - Loading data into a database
2. Wrangling Our Data
- 07 - What is data modeling
- 08 - Building our data model
- 09 - Checking the cleanliness of our data
- 10 - Joining two tables to create a view
3. Visualizing Our Data
- 11 - Why do we visualize data
- 12 - Connecting to our data model
- 13 - Visualizing our data
- 14 - Building our dashboard
- 15 - Publishing and distributing our dashboard
Conclusion
- 16 - Continuing your analytics engineering journey