The Datameer Interface

Here on the home page, you can see the ability to create a new project, alongside the ability to perform a keyword search for any Snowflake datasets, schemes, or transformation projects created and cataloged in Datameer.
Searching for content is a great place to start. Here in the Datasets tab, we can search any Snowflake tables and views.

Selecting a dataset allows you to browse the column metadata. Here we can see the names, data types, and any descriptions added to the dataset.
I can also preview what the data looks like by selecting the data preview tab. Once you have the data set you want, you select the add to project button

Inside the project, the workbench is where we can transform our Snowflake data. In the middle of the screen, we can see how the data is being transformed and a preview of how the data is being transformed.
To transform your data, select the green plus button, or select the new transformation or new SQL editor buttons at the top.
Let's start with the SQL editor. If you are a data engineer, you will be used to writing SQL code to query and transform data using this approach. We can execute Snowflake statements, call native Snowflake functions and see a preview of the data being transformed. Once applied, you can see your SQL in the workbench as a transformation step.

To add more data sets to your workbench, browse your Snowflake data and schemes on the left-hand side and select that add to project button.
You upload CSV files to the workbench if your data isn't already in Snowflake.

To join multiple datasets together, I could use the SQL editor or use the no code join recipe. I can select the data source I'd like to join, and Datameer will recommend column names to join against. With the ability to change the join mode or behavior.
I can also perform other no-code recipes, such as pivot and aggregating my data. Here I can select the fields or column names to be aggregated. I can add measurable value to calculate. And I can apply aggregate functions, such as sum, avg, min, or max. And optionally, you can include the row count.
You can see how your aggregate view looks before you hit the apply button to add this transformation as another recipe.

Datameer UI