As a data engineer, you hold all the cards to make data easily accessible to your business teams. Your team just requested an Airtable to Snowflake connection on priority. We know you don’t want to keep your data scientists and business analysts waiting to get critical business insights. As the most direct approach, you can go straight for the CSV files exporting if this is a one-time thing. Or, hunt for a no-code tool that fully automates & manages data integration for you while you focus on your core objectives.
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With this article, you will get a step-by-step guide for connecting Airtable to Snowflake effectively and quickly, delivering data to your marketing team. Hevo Data doesn’t support Airtable as a source at the moment, but it will be available soon.
Replicate Data from Airtable to Snowflake Using CSV
To start replicating data from Airtable to Snowflake, firstly, you need to export data as CSV files from Airtable. Then, import the CSV files into Snowflake and modify your data according to your needs.
- Step 1: In the Airtable dashboard, you need to select the three-dot menu against the view that you want to export. You will have the option to click Download CSV. The CSV file of your view will be automatically downloaded in the default location of your local system.
- Step 2: You can upload the CSV file to Snowflake using the data loading wizard present in the Snowflake Web Interface. Using the Snowflake Web UI, you can easily load data into Snowflake by selecting the table you wish to load, followed by clicking the LOAD button. The staging and data loading processes are merged into a single operation by deleting all staged files immediately after loading them into the data warehouse.
You can check ways of loading data as CSV files here.
This 2-step process using CSV files is a great way to replicate data from Airtable to Snowflake effectively. It is optimal for the following scenarios:
- One-Time Data Replication: When your marketing team needs the Airtable data only once in a long period of time.
- No Data Transformation Required: This method is ideal if there is a negligible need for data transformation and your data is standardized.
- Small Amount of Data: If the amount of data is small, then this method is a good fit as it the accuracy of data replication would be high.
In the following scenarios, using CSV files might be cumbersome and not a wise choice:
- Data Mapping: Only basic data can be moved. Complex configurations cannot take place. There is no distinction between text, numeric values, and null and quoted values.
- Two-way Synchronization: To achieve two-way synchronization, the entire process must be run frequently to access updated data on the destination.
- Time Consuming: If you plan to export your data frequently, the CSV method might not be the best choice since it takes time to recreate the data using CSV files.
When the frequency of replicating data from Airtable increases, this process becomes highly monotonous. It adds to your misery when you have to transform the raw data every single time. With the increase in data sources, you would have to spend a significant portion of your engineering bandwidth creating new data connectors. Just imagine — building custom connectors for each source, transforming & processing the data, tracking the data flow individually, and fixing issues. Doesn’t it sound exhausting?
How about you focus on more productive tasks than repeatedly writing custom ETL scripts? This sounds good, right?
In these cases, you can…
Automate the Data Replication process using a No-Code Tool
Here, are the following benefits of leveraging a no-code tool:
- Automated pipelines allow you to focus on core engineering objectives while your business teams can directly work on reporting without any delays or data dependency on you.
- Automated pipelines provide a beginner-friendly UI. Tasks like configuring and establishing a connection with source and destination, providing credentials and authorization details, performing schema mapping etc. are a lot simpler with this UI. It saves the engineering teams’ bandwidth from tedious preparation tasks.
Hevo Data will support Airtable as a source soon, you will have to provide basic details like credentials, data pipeline name, etc., and configure your Airtable Source.
You can have a look at the exhaustive list of sources provided by Hevo Data here.
What Can You Achieve by Migrating Your Data from Airtable to Snowflake?
Here’s a little something for different departments of your team. We’ve mentioned a few core insights you could get by replicating data from Airtable to Snowflake. Does your use case make the list?
- You want a detailed product catalog or efficient track of the purchase process.
- You want to explore and build efficient records for marketing analytics.
- Your sales team wants custom reports for the customer journey.
- Your development team needs to build bug-tracking reports.
You can have a deep understanding of the use cases here.
Summing It Up
Exporting and importing CSV files is the right path for you when your team needs data from Airtable once in a while. However, an ETL solution becomes necessary if there are rapid changes in the source and frequent data replication needs to be done to meet the data demands of your product or marketing channel. You can free your engineering bandwidth from these repetitive & resource-intensive tasks by selecting Hevo Data’s 150+ plug-and-play integrations.Visit our Website to Explore Hevo
Saving countless hours of manual data cleaning & standardizing, Hevo Data’s pre-load data transformations get it done in minutes via a simple drag-n-drop interface or your custom python scripts. No need to go to your data warehouse for post-load transformations. You can run complex SQL transformations from the comfort of Hevo Data’s interface and get your data in the final analysis-ready form.
Want to take Hevo Data for a ride? Sign Up for a 14-day free trial and simplify your data integration process. Check out the pricing details to understand which plan fulfills all your business needs.
Share your experience of replicating data from Airtable to Snowflake! Let us know in the comments section below!