My Journey Through Snowflake’s Data Warehousing Workshop

I’m excited to share that I’ve recently completed my Snowflake Badge 1 certification!

As a third-year computer science student, I committed to pursuing a career in data engineering by enrolling in a three-month fellowship program. It felt like the right way to begin my journey, and through this experience, I gained a clear understanding of the roadmap and overcame my initial uncertainty.

With that being said, in my second month of this fellowship program, we are assigned to learn to snowflake out of three cloud platforms that are: Azure, AWS, and Google Cloud; they provide $400 free credits (with no MasterCard required) to play with their web app for one month. Compute and storage layers are separated. A virtual warehouse can automatically start and process your queries and pack up after 5 to 10 minutes.

What is Snowflake?

Snowflake is a cloud-based data platform that supports many data-related workloads, including data warehousing, data lakes, data applications, and data engineering, as well as for the secure sharing and consumption of data. Besides secure sharing, it helps load, integrate, and analyze data. It is a fully managed service that enables concurrent workloads.

Over two-fifths of Fortune 500 companies use Snowflake to fulfill their data analysis needs. Customers from companies like Microsoft, Google, and Amazon are using Snowflake.

Snowflake has been running smoothly with these three tech giants for a long time.

What does Snowflake offer?

The main functionalities that Snowflake offer include:

• Querying and Analysis of disparate data in one single place
• Multi-cluster shared data architecture.
• Seamless Data Sharing

Key Takeaways from the Workshop

1. Create, edit, and load Snowflake Tables.

With the help of Snowflake, I learned how to design and define table structures, modify existing tables by adding or altering columns, and load data into these tables from various sources.

This hands-on experience helped me master managing and manipulating large datasets within Snowflake, enabling me to work more effectively with cloud-based data warehouses.

2. Create, edit, and use Snowflake File Formats

I became skilled at defining file formats to match specific data structures, such as CSV, JSON, and Parquet, ensuring the data could be imported accurately.

Additionally, I gained experience in editing these file formats to accommodate different data sources and requirements, enabling seamless integration and transformation of raw data into the Snowflake environment.

3. Create, edit, and use Snowflake Compute Resources

I gained practical experience setting up compute clusters to handle various workloads, ensuring optimal performance for querying, data loading, and processing tasks.

In addition, I learned how to modify these resources by scaling them up or down depending on the operation's needs, maximizing efficiency while managing costs.

4. Create, edit, and use Snowflake Copy into Statements

Additionally, I learned how to edit the COPY INTO commands to handle different file formats and data types, ensuring accurate and efficient data ingestion.

This experience also involved managing errors and optimizing performance, allowing me to streamline the data loading process for structured and unstructured data sources.

5. Transform, parse, and load both CSV and JSON

I developed the ability to handle and manipulate these file types, transforming raw data into structured formats that fit the desired schema. With CSV files, I mastered the process of parsing rows and columns, ensuring correct data types and formats were applied during loading.

For JSON, I gained experience extracting nested data using Snowflake’s native functions, making it easy to flatten complex structures. This knowledge allowed me to seamlessly load and process diverse data formats for analysis and reporting within Snowflake.

Wrap up

I hope this article helps you gain some insights about Snowflake software. The aim was to give you a proper review.

However, Completing the Snowflake Badge 1: Data Warehousing Workshop was a valuable experience that equipped me with essential skills for handling data. I’m eager to apply these newfound abilities in future projects as I progress on my data engineering path.

If you’d like to follow my journey or explore more of my work, feel free to connect with me:

• GitHub: Rabiya Asif | GitHub
• LinkedIn: Rabiya Asif | LinkedIn

Thank you for reading! I’m always open to feedback and collaboration, so don’t hesitate to reach out!