Now, Let’s dive into the actual data exploration. We will start with how Atlan insights can truly accelerate your ability to understand your data, along with making you confident in the data that you are using. We click on the insights icon on the left-hand side to bring up the insights page. On the left-hand side, there is the explorer. This is similar to the common explorers that you see in other I D Es or sequel editors but is powered up by having the metadata context of the assets as you explore. Additionally, it allows you to switch from one source to another just by clicking the drop-down.
In this case, we see that we can go from exploring and being able to query Big Query data, right to our Snowflake Production data. We select our Snowflake production connection, along with our database and schema that we want to explore. As with any other tool, the schema, tables, and columns are all kept in a nested fashion, and clicking on the arrow will expand to lower levels. What is great with Atlan is that we are able to hover over the assets and get the metadata for the assets, whether the schema, table, or columns. This gives us an immediate understanding of the data we are looking at, with descriptions and ownership.
It can truly help ensure that we are confident in the data we are using. On the asset icons themselves, if an asset is deprecated, there will be a red visual indication of this, alerting us immediately that we should not use the asset. To create a new query, we simply click on the plus icon next to our existing query and select new sequel query. Now we can start writing our query. In this case, we want to create a new query that shows the top products that are sold from the bakery department.
First, we update our connection in the top right to Snowflake Production, then update the database and schema, as we know where this information lies. Next, we write our sequel as we normally would for Snowflake. Prior to starting to write our query, We can click on the three dots next to the save button to get additional options. We can update the theme, in case we want a dark background like many other tools allow for, set our default tab indenting size, change the overall font size, and also can specify how we want our cursor to appear. this allows us to customize the feel of insights to fit how we are most comfortable.
There is also the command pallet, where we can run different actions, such as removing trailing white space, and will show the quick key actions where applicable for some of the actions.
During the sequel writing process, Atlan will auto suggest values as you write, and you can easily accept these by hitting enter. As you write out your query, any assets that are referenced in the sequel will actually link back to those assets and the metadata for the asset can be seen by hovering over the asset name in the sequel. It is another amazing example of getting the metadata you need to be confident in the data sources you are using right inside of insights, something no other I D E or sequel querying tool can do.
We finish writing our sequel, and Since we want to see all results, we will uncheck the limit to 100 rows option. We now run our query by clicking on the Run button or by hitting command and enter. Our query will then run and the results will return. Once returned, we can search the results if there is a specific value that we are looking for, sort the results, copy the results, download our results as a C S V, or share the results in Slack. Now that we have created our query, we want to validate it with our other query developer Duane before we promote it to production. We click on the Save button and enter the name of Top Bakery Product Sales.
In the description we put this query outputs the top bakery products. for the collection, we select development as we want to collaborate with Duane prior to promoting it to our sales production folder. For the certification, we put draft. Finally, we click on save and share. Here, we can add any additional users to the development collection, in case there is someone who does not currently have access that we want to run the query, along with being able to copy the link, or share it on Slack or Teams. We click on the slack icon and quickly select the channel we want to share the query with.
In the message, we tag Duane, notifying him that we would like him to review the query prior to moving it to production. A message in slack will be created with a direct link to our query for Duane to go ahead and review.
