This article illustrates how to add multiple cloud and marketing data in Tableau.
Note: This tutorial is aimed at experienced Tableau users, as it requires familiarity with the solution and with creating custom metrics in Tableau.
Your company has run a couple of campaigns on your website, on social media, and on search. As an analyst, you would like to bring Adobe Analytics, Facebook Ads, Google Ads, and Bing Ads data into Tableau to create campaign performance dashboards for your management team.
We will show you how the Cognetik Cloud Connector works with four data blocks and four data sources, with dimensions and measures changing per data source, while creating calculated metrics in Tableau. The common element, in this case, is the campaign name.
How to link your credentials for:
To see a list of all your linked accounts, click on 'Credential List.'
Let’s start building our Adobe Analytics query.
Choose 'Adobe Analytics' from the 'Choose a provider' drop-down list.
Select your Credential and Report Suite.
You can now filter your data: You can choose from Dimensions (optional), Metrics (mandatory), and Segments (optional). It’s easy to find them from the drop-down list. You can bring anything that’s set up in your Adobe Analytics report suite.
As an example, I’ve selected data related to my campaign performance and also a segment of users I'm interested in that I’ve previously set up in Adobe Analytics.
You can choose from three types of granularities:
You can choose from three types of calendars:
You can now also select a Timezone for your data.
In the present you have a lot of already Preset Date ranges you can use.
Our connector also includes the option to use Date Expressions for all connectors. This is frequently used for Adobe Analytics data. Here's more information on date expressions.
If you need a specific period of time, you can use a Start Date and an End Date.
The row limit is 50,000 rows.
Top limit is only applicable to Adobe Analytics (filters out and returns the first 'n' rows ordered by the first metric chosen).
Function - takes the first n breakdowns, aggregated by the first metric requested, over the entire period specified, then returns the daily values for those values, whether or not they are in the top values for that given day.
*For more information about the Top limit, visit this article.
You can now Name your extract and Preview your request before creating a data extract in Tableau. This will allow you to explore the data quicker and confirm you have the correct data.
The preview runs quickly because the processing is done by Cognetik’s distributed API engine and does not require waiting for Tableau to create a local database for the extract.
The preview section offers a few features to make data exploration easier:
Now that our Adobe Analytics data is correct, we would like to add the Facebook data.
In the upper right corner, click 'Add Data Block' and repeat the process with the second data source.
Select your Facebook credentials from the drop-down list, and choose the metrics, dimensions, and segments.
Make sure you rename the data block name and column prefix to help you identify that data in Tableau, like ‘’FB.’.
Go back to the first block and rename it 'AA' (Adobe Analytics) in order to easily identify it in Tableau.
Repeat the process of adding data block number 3 for your Google Ads query.
Repeat the process of adding data block number 4 for your Bing Ads query.
Once you have it all set up, you can Preview your request before creating a data extract in Tableau.
Once you click Submit, your data will be sent to Tableau.
In the 'Data Source' tab, click 'Update now.'
Once the info is updated, go to 'Sheet 1' to view your data ready to be turned into beautiful dashboards.
As an experienced Tableau user, I’m looking at how my data looks like, knowing that since 'Campaign Name' is the common element between the four data sources, I still need to create a calculated metric to be able to match the campaign names of all four sources.
I created ‘’Campaign nName C’’ as a calculated metric.
Formula used for this example:
By doing so, I was able to easily create beautiful dashboards using all four cloud sources.
Basic dashboard example: