When working with a new data visualization or business intelligence tool, one of the most important first steps is connecting to a data source. Whether that is a flat CSV or a live connection to a cloud data warehouse, this can be a confusing task for some platforms.
Using Sigma, you can connect to your Snowflake Data Cloud data source in just a few very quick steps. After this, be sure to check out our other posts about Sigma to continue your journey using Sigma Computing.
How to Connect to Snowflake
When using Sigma Computing and connecting to a new data source, we feel that Snowflake is the easiest data warehouse to set up. You only need a few simple steps and you will be able to connect to your data sets in no time.
First, from your admin console, select ‘Connections’ on the left-hand side. This will allow you to view what connections you can make in Sigma. You’ll see a few options, but we are going to select Snowflake for this exercise. You will see boxes to input the following information:
- Name – this is your connection name. You can name it whatever you want, but we recommend naming it something similar to the table you will connect to. Here I’ve titled it ‘My phData Snowflake Connection’.
- Type – this dictates the type of data source. In this case, we are selecting Snowflake.
- Connection Credentials – this is all of the information you need to provide to connect to your organization’s Snowflake instance. You will need your server, warehouse, user, password, and role (optional).
- Connection timeout – this is optional and will dictate how long a query will run before it will timeout. This is up to you, but typically users will use 120 seconds.
- Enable write access – this is also optional, but you can select this if you intend to materialize your data set.
Following the input of this information, click the create button to create your Snowflake connection. Really, that’s it. You’re now connected to your organization’s Snowflake instance.
Now, to access the tables in your Snowflake connection, go to your Sigma homepage and select Create New at the top left-hand corner of the screen and select Workbook:
At the next screen, select Table. The following screen, Tables, and Datasets. From here, you will see a section titled ‘Select a Source’:
In this example, I have connected to the Sigma Sample Database. In your case, you will see the connection name that you input in the previous steps. Navigate through the dropdowns to select your schema and table, and click the table you want to connect to.
You will see the data set show up and from here, you can select the columns you want to bring it. This is great if there are unnecessary index columns or other information you don’t need:
Select your columns, select Done in the top right corner, and Sigma will automatically create a new workbook for you with only the information that you selected. This is a great way to narrow down the data you bring in to avoid the arduous task of hiding all of the columns you don’t need.
Overall, it is clear how easy it is to connect to Snowflake using Sigma. There are just a few short steps in a user-friendly interface to immediately get started on your journey with Sigma. Here at phData, we have experts that are ready to help you stand up a Snowflake instance, a Sigma workspace, or both. Let us know if you want to learn more!
No, Sigma supports database connections for a number of different data sources, so you are not restricted to just using Snowflake. You can also connect to flat CSVs if that suits your use case. Connecting to Snowflake, however, allows you to maintain a live connection that is always up to date and extremely quick, Plus, as you saw in this post, it is very simple to connect to Snowflake in Sigma.
Absolutely! Not all organizations use Snowflake, so that’s a great question. Migrations from other data stores to Snowflake happen all the time. phData is an Elite Snowflake Partner and we have experts that can help you at every step of the process to move your existing data to Snowflake. Our team will handle everything from migration to repointing visualization data sources and ensuring the transition is seamless. Find out how we can help your organization here.