What you'll learn

Transforming raw data into actionable insights is critical for effective analytics. However, manual data preparation can be time-consuming and prone to errors, hindering timely decision-making. Snowflake offers powerful tools to streamline this process, enabling efficient data transformation and preparation for analysis.

In this course, Data Transformation in Snowflake, you’ll gain hands-on experience in building robust data pipelines, applying essential SQL techniques, and shaping data for business intelligence (BI) tools, and also learn how to use Snowsight for data exploration and validation.

First, you’ll explore how to build efficient data pipelines in Snowflake, focusing on the key stages of ingestion, transformation, and loading, and learn best practices for using Snowflake’s features to improve performance and maintain data quality.

Next, you’ll develop essential SQL skills for transforming data--such as trimming strings, handling NULLs, converting data types, and using aggregation functions with GROUP BY and HAVING clauses--and work with Common Table Expressions (CTEs) to structure more complex queries.

Then, you’ll learn how to format data for BI tools and dashboards, including pivoting, unpivoting, and flattening nested data like JSON.

Finally, you’ll use Snowsight to run, organize, and validate transformation queries, preparing datasets that are optimized for visualization and analysis.

By the end of this course, you'll be equipped to efficiently transform and prepare data in Snowflake, enabling accurate and timely insights for your organization.