Studying Snowflake - Data Analyst Study Guide

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Snowflake is an Enterprise-Level Data Platform for the major cloud providers: AWS, Azure, and GCP. They've managed to build a platform that addresses the diversity and complexity of an enterprise data warehouse, as well as leveraging cutting-edge big data tools and processes.

The SnowPro certification is divided into Core and several advanced specializations. In this blog post, I dig into the Data Analyst SnowPro certification with examples from my own KEXP Data Warehouse in Snowflake, freely available on my Big Data Platforms Git page.

• https://github.com/timowlmtn/bigdataplatforms/tree/master/src/kexp

The basis for this blog post is the course exam notes. Download the PDF file, and you can follow the guide while running the examples cited in this post.

• https://learn.snowflake.com/courses/course-v1:snowflake+SPSG-DAA+A/course/

Here is a list of domains in the guide.

1. Data Ingestion and Data Preparation

2. Data Transformation and Data Modeling

3. Data Analysis

4. Data Presentation and Data Visualization

Data Ingestion and Data Preparation

Worksheet - Collecting the Data

Collecting the data is accessing it on a remote site and copying it into the storage provider's location. Snowflake currently supports three service providers: S3, GCS, and Azure.

Data collection frequency	​Weekly
Volume of data	~400 fact records daily
Data sources	​https://api.kexp.org/v2
Data collection method	Python API Call