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Reporting with Snowflake
Advanced SQL | Stored Procedures | BI Tools
If you work with data, you’ve probably heard someone mention Snowflake. The Snowflake Data Cloud stores data for thousands of organizations, across every industry of business today. Their platform is an excellent option for all kinds of work loads, from AI and Machine Learning to Data Engineering and Cybersecurity. But what you don’t hear as often is how to leverage Snowflake to build analytics projects, how to automate business intelligence reporting with tools like Tableau, Streamlit, or even Power BI.
Agenda:
- Playing with Transactional data
- Stored Procedures (SQL)
- Building a Report
PLAYING WITH TRANSACTIONS
Dim and Fact tables are key concepts used in the context of data warehousing and relational database design, particularly in the realm of business intelligence and analytics. They are components of the Snowflake schema, which are approaches to organizing data for efficient querying and reporting. Transactional databases are commonly used in applications where data accuracy and integrity are critical, such as online banking systems, e-commerce platforms, reservation systems, and inventory management systems. They provide a reliable way to ensure that data remains consistent and dependable, even when multiple users are concurrently interacting with the system.
Dimension Tables: contain descriptive or textual information about business entities, such as customers, products, time periods, locations, etc.
Fact Tables: store quantitative and measurable data that are usually the result of business events or transactions. These tables contain data that can be aggregated or analyzed, such as sales revenue, quantities sold, profit margins, etc.
Common Reports that contain transactional data:
- Sales Revenue, Loyalty Points, Inventory Planning
- Fiscal Year, Quarterly, Daily, Weekly, Previous Fiscal Month
- Customer Behavior, Location Performance, Marketing…
