Analytics Engineering
A mix of disciples with the best qualities of each.
What Is Analytics Engineering
Analytics engineering is cross-disciplinary that bring the best from the software engineering disciple and the data analytics disciple. When you put these two disciples together, you can build some really useful technology.
It's like peanut butter and jelly. They are each good on their own, but when mixed together the combination is incredible.
Software Engineering
Best practices from the software engineering disciples which include roles such as web developer, mobile developer, software engineer, etc.
Best Of Software
- Efficient code
- Automation
- Version Control
- Testing
Data Analytics
Best practices from the data analytics disciples which include roles such as data analyst, data engineer, data scientist, etc.
Best Of Analytics
- Data Quality
- Feature Engineering
- Data Analysis
- Business Intelligence
Tech Stack
The technology that I use most frequently is listed below, but this is not a complete list. Many other tools have been used as well.
Python
Django, Pandas & Machine Learning
JavaScript
Node, React Native, Vue, Next
Databases
MySQL, SQL Server, SQLite
Analytics
CSV, JSON, Jupyter Notebooks, Excel