It’s here

After a long wait, I have finally published this blog. It’s not perfect and I may have to revise it further. But in the interest of shipping it quickly. Here is some high-level information on how to integrate Dbt and Fivetran.

Dbt + Fivetran

Extract, load, transform, and analyze are the four primary layers of the analytics stack. There are multiple software alternatives available in the market that can allow analysts to extract, load, and run data. However, data transformation is still a challenge for many as it requires specialized expertise. Data transformation is a crucial step for every business, and it needs to streamline all the data to support modeling and analytics.

What is dbt?

Dbt or Data Build Tool is a tool from dbt Labs that helps in data modeling and transformation. This SQL-based transformation tool allows data professionals to automate the work of data modeling and transformation.

With SQL SELECT statement, users model their data in a text editor, create dependencies and relationships between models, and transform those models into tables that can be viewed in the data warehouse. It makes it simple for professionals to turn models into business intelligence. The Data Build tool supports databases like BigQuery, Snowflake, and Redshift.

What is Fivetran?           

It is a cloud-based data integration platform that automates the data extraction process from multiple sources. It helps in loading the data into the destination or data warehouse and continuously syncs the data to keep it updated. Fivetran supports all types of data sources, including files, applications, databases, and more. This platform integrates data from all such sources with data warehouses like Google BigQuery, Snowflake, Amazon Redshift, etc. The main aim of this platform is to simplify the data and allow businesses to focus on data insights rather than managing the intricacies of data integration.

Why dbt and Fivetran are preferred tools for a data platform

There are several reasons which have made these tools a preferred choice for the professionals:

Complementary capabilities: Fivetran automates data ingestion taken from multiple sources into a data warehouse. Meanwhile, DBT works on modeling and data transformation within the warehouse.

Ease of use: Both these platforms are user-friendly. With dbt, data analysts can use familiar syntax for SQL transformations, while with Fivetran’s interface, it is possible to simplify the management and setup of data connectors.

Automation: Automation is one of the main benefits of both tools. Through Fivetran, you can automate the process of extraction, loading, and data syncing, which reduces manual intervention. Similarly, through dbt, you can automate data transformation workflow execution.

Scalability: Both Fivetran and dbt are scalable, that implies both can handle extensive data. With the increase in data, both tools can manage the processing requirements without compromising on performance.

Integration Flexibility: Fivetran supports integration with multiple data sources, while dbt allows integration with various data warehouses like BigQuery, Snowflake, and Redshift. This facility makes it possible for companies to use their preferred tools along with Fivetran and dbt.

Check the image below, which shows the integrated work of both DBT and Fivetran.

Image Credit

 Fivetran and Dbt: a dynamic pair accelerating data analysis

When Fivetran is combined with dbt, it can create a powerful solution to help companies that have moved their data to cloud. Fivetran can take care of the extraction and loading stage of data, while dbt can model data to transform them into analytics-ready tables. This duo combination can round up the ELT (Extract, load, transform) process. Together, these tools are capable of creating a comprehensive pipeline that is flexible enough to match the rapid changes in the industry.

Including Fivetran and dbt duo in their modern data stack, businesses can get reliable reports and can have easy access to data-driven insights. Such democratization will allow decision-makers to make quality decisions and will also enable the data team to emphasize on valuable insights.

Why trends should not be followed blindly

For many companies, dbt and Fivetran can be the most important weapon in their arsenal to manage and transform data, but the same may not be true for other companies. You should never follow the trend blindly, as before adopting any technology, it is essential to consider the specific needs and context of your company. Below are some of the reasons why Fivetran and dbt may or may not be advisable for your brand.

• Context Matters: Each company has its sources, infrastructure, and requirements. What may work for your company may not be suitable for others. You must embrace dbt and Fivetran after understanding your organization’s specific context to maintain your process and data pipelines
• Customization requirements: Although both Fivetran and Dbt put various capabilities and features in your plate, there may be a condition where you need some additional development and customization to match your company’s needs. Unquestioningly, adopting these technologies can limit the efficiency of your company’s data operations.
• Data Quality Considerations: Data quality is an uncompromising factor in any data pipeline. Although both dbt and Fivetran can manage and transform data, they may not provide the desired data quality. Even after embracing dbt and Fivetran technology, you must do the proper quality checks of your data to maintain accuracy.
• Cost considerations: Companies need to pay for both dbt and Fivetran based on their usage. Blindly adopting such tools without considering their cost may lead to unexpected expenses for your organization.
• Evolution of requirements: The data landscape experiences continuous evolution, and your company’s requirements may change with time. Adopting dbt and Fivetran without reassessing your data pipeline and tools as per the future requirements may result in stagnation or missed opportunities.
• Technical limitations: Even being one of the most powerful tools, dbt, and Fivetran have technical limitations that can hamper your organization’s suitability. It would help if you considered the technical limitations of these tools to avoid scalability and performance issues in the future.

Conclusion

Being a part of the modern data stack, dbt and Fivetran help companies gain faster and more reliable data-driven insights. This data democratization allows companies to make informed decisions and focus on valuable insights. These tools help companies create an end-to-end pipeline, which provides you the desired flexibility to match up with this fast-paced industry.

Just like the two sides of a coin, dbt and Fivetran have their limitations. It would help if you consider how they can fit into your company’s particular requirements, context, and constraints before their adoption. Don’t follow these tools blindly without critical evaluation.