5 Tips for Implementing Slowly Changing Dimensions with Matillion and dbt

What does it take to excel in the world of data engineering and analytics? The answer lies in the powerful mix of innovation, collaboration, and commitment to best practices. Welcome to the first of a new blog series that covers the intricacies of data engineering excellence. Guided by the wealth of experiences and expertise of our consulting partners from the Matillion Partner Network, each offers a unique perspective to help companies do more with their data. Whether fine-tuning data pipelines or maximizing the power of cloud-native architectures, each installment will provide diverse insights, strategies, and success stories gleaned from the diverse perspectives of our esteemed partners. In this article, we'll explore best practices for implementing Slowly Changing Dimensions (SCDs) Type 2 tables using Matillion and dbt, drawing from the collective expertise of Matillion and Spaulding Ridge

SCDs play a crucial role for data engineering teams in maintaining historical data accuracy and enabling comprehensive analysis – and they’re used in data warehousing to manage and track changes in dimension data over time. Dimensions, like customer information or product details, often change, and SCDs maintain these changes for precise reporting. For example, SCDs enable an electronics store to accurately report TV shipments to New York in 2023, even if customers have since moved. Without SCDs, reports would only reflect current residents, leading to inaccurate data.

With SCD Type 2 dimensions, a new row with updated information is added to the dimension table when a dimension attribute changes. The existing row is then marked as inactive or historical, allowing you to preserve the dimension's historical state and track the changes over time. You can track multiple changes over time by adding effective_start and effective_end columns to the table.

5 Tips for Implementing SCD Tables:

How should an organization get started with SCD tables? We have five tips that will give you a starting point:

Tip 1: Understand Your Data Dynamics: Begin by understanding your data's dynamics. Identify key attributes prone to changes and determine the SCD type that best suits your business requirements, focusing on preserving historical accuracy while optimizing performance.

Tip 2: Efficiently Detect Changes with Matillion: Leverage Matillion's Detect Changes Component to quickly identify and track data modifications. Configure the component to compare input tables based on primary keys and relevant columns, facilitating seamless detection of new, changed, or deleted records.

Tip 3: Incorporate Versioning and Timestamps: Ensure robust versioning by incorporating effective_from and effective_to timestamps in your SCD tables. This enables precise tracking of data changes over time, facilitating accurate historical analysis and auditing.

Tip 4: Automate Incremental Loads with dbt: Streamline your data pipeline by automating incremental loads with dbt. Configure your dbt models as snapshots, enabling efficient detection and incorporation of updated records without duplicating unchanged data.

Tip 5: Establish Monitoring and Alerting Mechanisms: Set up automated job schedules within Matillion and dbt to ensure the timely execution of SCD updates. Implement robust monitoring and alerting mechanisms to address any failures or anomalies in your data pipeline proactively.

Unlock SCD Mastery with Matillion, Spaulding Ridge, and dbt

Implementing SCD Type 2 tables empowers organizations to maintain data integrity, facilitate historical analysis, and drive informed decision-making. By adhering to these best practices, data engineers can optimize their data pipelines, enhance operational efficiency, and unlock the full potential of their data assets.

Ready to revolutionize your data practices? 
Start your journey to SCD mastery today with a free trial of Matillion Data Productivity Cloud. Contact Spaulding Ridge for additional assistance with setting up SCD tables. Transform your data and unleash the power of historical insights in minutes.

About the Authors:

Miraj Jallie - Partner Marketing Manager (Matillion)

Miraj Jallie is a results-driven Partner Marketing Manager with extensive experience in the tech industry. With roles at companies like Okta, Human Interest, Dialpad, Spekit and Matillion, Miraj has honed her skills in driving successful marketing strategy and initiatives with channel partners.

Dan Greenberg - Senior Director (Spaulding Ridge)

Dan Greenberg is a Senior Director at Spaulding Ridge and a seasoned cloud data architect and technical sales expert with over 20 years of experience in enterprise data and analytics. He specializes in Snowflake technology, developing tailored solutions and fostering strong client relationships.