Your takeaways from this blog
✔️ How does the Skill profile of a Snowflake Data Warehouse Engineer look like?
✔️ What capabilities to have as a Data Warehouse Engineer in Snowflake to become a better problem solver?
Ready to hit the road?
You wish to build your career as a Data Warehouse Engineer with Snowflake. Before hitting any tool, it is important to have fundamentals clear. Below are the skills you must possess before starting off with Snowflake :
✔️ Relational Database Fundamentals :
- Ability to work with Relational Database : Clarity on the concepts of primary keys, foreign keys, constraints, cardinality, E-R Modeling etc.
- Comfort with writing DDL and DML statements in SQL :
- You should be able to create, alter, drop tables using SQL
- You should be able to perform all data operations (select, filter, group-aggregate, pivot, merge, windowing etc.)
- You should be able to write functions & procedures using T-SQL
Please refer the Skill profile of a Data Analyst here to find resources to brush up your Database Fundamentals
✔️ Need for a Data Warehouse :
- You should be able to articulate why Data Warehouse is needed at the first place
- You should be able to differentiate between a Database and a Data Warehouse
- You should be able to differentiate between OLTP and OLAP systems
- You should be comfortable with following data warehouse concepts :
- Dimensions : Hierarchical, Junk, Conformed, Role Playing & Degenerate Dimensions
- Facts : Additive, Semi-Additive, Non-Additive Facts
- Grain of data
- Need for surrogate keys. How are they different from Natural keys
- Fundamentals of Dimensional Modeling : Star vs Snowflake Schema
- Understanding of Slowly Changing Dimensions :
- Why are they required?
- How to implement them?
This excellent playlist by aroundBI has everything you'd need to brush up your Data Warehousing Fundamentals
Considering you have decent idea of the pre-requisites, here you go about skills you need to develop to excel as a Snowflake DW Engineer.
✔️ What's the need for Snowflake?
- You should be able to articulate on what parameters Snowflake fares better than Traditional Data Warehouses?
- Management Overhead
- Data Sharing
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