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Data warehousing, data preparation and collaboration using Snowflake, DBT and GIT

April 25, 2023

In today’s data-driven world, businesses are collecting data from various sources such as web analytics, customer relationship management (CRM) systems, social media, and more. While these data sources can provide valuable insights, it can be challenging to consolidate and analyze them to get a complete picture of the business. However, with the use of DBT, Snowflake, and Git, for data warehousing, data preparation and collaboration, businesses can streamline their data processes and gain valuable insights.

The Problem: Multiple Separate Data Sources

One of the biggest obstacles for businesses today is consolidating data from various sources. With data coming in from different platforms and systems, it can be difficult to get a complete view of the business. This can result in missed opportunities, inaccurate reporting, and wasted resources.

The Solution: DBT, Snowflake, and Git

To overcome the struggle of consolidating data from different sources, businesses can leverage make use of three powerful technologies: DBT, Snowflake, and Git. Further, the combination could yield in interactive reporting using Tableau and a host of project management technologies.

Data Ingestion: The data from each platform is extracted and loaded into Snowflake. This can be achieved using Snowflake’s built-in connectors, APIs (Application Programming Interface) or using ETL tools like Fivetran, Supermetrics, ChannelMix, or something similar.

Snowflake

Snowflake is a cloud-based data warehousing platform that allows you to store and analyze large amounts of data. Snowflake provides a secure environment that allows you to expand on size as necessary for storing your data, allowing you to easily consolidate data from different sources and access it in real-timeas soon as it is available.

With Snowflake, you can create a consolidated view of your data that brings together information collected from all your sources. This combined view makes it easy to analyze your business performance across different platforms, identify trends, and make informed decisions.

DBT

DBT, or Data Build Tool, is an open-source platform for data transformation and modelling. DBT allows you to define and execute complex SQL (Structured Query Language) transformations on your data, making it easy to combine data from different sources and transform it into a format that is consistent across all platforms.

Using DBT, you can create a series of SQL scripts that transform your raw data into a format that is standardized and easy to work with. For example, you can use DBT to aggregate data at a daily level, standardize naming conventions, and calculate key performance metrics.

Git

Git is a popular version control system that allows you to track changes to your code and collaborate with others. By using Git to manage your SQL scripts, you can ensure that all team members are working on the latest version of the scripts and that any changes are tracked and documented.

Git also provides a backup system for your SQL scripts, allowing you to roll back to a previous version if necessary. This is particularly important when working with data, as changes to your SQL scripts could have a significant impact on your business performance metrics.

An overall project flow diagram

Benefits of Using DBT, Snowflake, and Git

By using DBT, Snowflake, and Git to consolidate your data, you can gain several benefits:

  • Improved Data Quality: By standardizing your data using DBT, you can ensure that your data is consistent across all platforms and free from errors.
  • Efficient data transformation: DBT allows users to write SQL code to transform and model data, making the process more efficient and scalable.
  • Real-Time Access to Data: With Snowflake, you can access your consolidated data in real-time, making it easy to monitor your business performance and make informed decisions.
  • Collaborative Environment: By using Git to manage your SQL scripts, you can collaborate with team members and ensure that everyone is working on the latest version of the scripts.
  • Version control: With Git, the company can track changes to data models and transformations, collaborate with team members, and revert to previous versions if needed.
  • Scalable Solution: With Snowflake, you can easily expand your data warehousing capabilities as your business grows, ensuring that your data is always available and easy to work with.

Conclusion

In conclusion, businesses today face the challenge of consolidating data from various sources. With the use of DBT, Snowflake, and Git, companies can streamline their data processes and gain valuable insights. By standardizing data, accessing it in real-time, collaborating with team members, and developing your data warehousing capabilities, your business can make informed decisions and stay ahead of trends in your market.