• views: 103
• date: 26 September 2025
• posted by: 0nelove

Analytics Engineering is the foundation of Data Science and AI
Analytics Engineering is a dynamic blend of Data Engineering and Data Analytics, serving as the bridge between these two domains. Analytics Engineers develop and maintain a good portion of the data lifecycle, from the ingestion of Data Sources, to the development of Data Warehouses and the corresponding data pipelines, to Business Intelligence tools. Whether you are a Data Analyst/Scientist that would like to practice on modern Data Engineering tools, or an aspiring Analytics Engineer, this workshop is for you.
You will learn how to
● Start and develop a modern Data Warehouse, using Snowflake.
● Ingest data, on a schedule, from multiple sources, using connectors in Fivetran.
● Clean and transform data, and the basics of ELT (Extract, Load, Transform), using DBT and SQL.
● Spin up and connect a Business Intelligence tool (Preset) to a Data Warehouse.
Key outcomes
Build an end-to-end data engineering product, from raw data to data visualization.
Start and develop a modern Data Warehouse, using Snowflake.
Ingest data, on a schedule, from multiple sources, using connectors in Fivetran.
Clean and transform data using DBT and the universal data language of SQL.
Spin up and connect a Business Intelligence tool (Preset) to a Data Warehouse.
Add this hands-on project to your portfolio, showcasing new marketable skills.




   
   
   

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