As an analyst, I would like to get data related to my website and products from Adobe Analytics into the data warehouse I’m currently using, which is Snowflake.

First I would need to set the Data Extract Source. I can choose an Existing Data Source or a New Data Source. I’m going to connect to a New Data Source.

From the Data Connector List select Adobe Analytics.

Note that you would need to link your Adobe Analytics account before getting started. Once you do that, you’ll be able to see your Adobe Analytics credentials into the credentials list.

You can also select the Report Suite.

Then, you can name your Data Source. I’m going to call it "Test0416AA" and click Submit.

Next step would be to set up the Data Destination.

From the Data Connector List, select your data warehouse of choice (I will go with Snowflake).

First, you will have to link your Snowflake account.

Once you do that, you will be able to select your credentials from the credentials list.

You can choose an Existing table or create a New table. I’m going to go with create a new table.

Next step will be Schedule and Data Range.

You can set your stream to be One-time or Recurring.

You have a lot of predefined sections in Date Range.

You can also choose to set your own Start Date and End Date.

In terms of Granularity our product offers: Daily, Weekly, Monthly.

We also offer 3 types of calendars, Standard, Retail and Custom.

If you want your stream to be recurring you can also select the Frequency, Time of day and Timezone. You can also make use of the fields “Import Data since” and “Run this report until” fields.

I’m gonna go with One-time only stream with a specific period of time, daily granularity and the standard calendar.

Next Step would be to add Filters and Segments. 

This step is optional but I am going to show you how you can choose a metric or dimension, in order to filter specific data, or how to Segment your data.

In Filters section you can filter by any metrics and dimensions you have set up.

Simply use the drop down tab and select the data you would like to segment.

In Segments, you can select any segments you have set up.

For the demo purpose I’m going to select a segment I’ve set up in Adobe Analytics for this demo called "Connector Demo".

The next step. Metrics and Dimensions. In this section you will see 3 tabs. The first tab is Source. Here you will set your Metric (mandatory) or Dimension in the drop down. Once the Source is set you can select your Destination.This will be the column in the table.

In Data Type you will need to select the appropriate description.

To have more than one Metric or Dimension simply click the green button below that says Add Metric or Dimension.

You can add as many metrics and dimensions you want for your data (*any limitations in this regard are from the cloud platform). I’m going to go for the following Metrics: Revenue, Orders, Units of products sold and I’m also going to add couple Dimensions: product and campaign name.

Before you save your stream you can preview your data. Click Preview Data. Note: you can preview all the data you selected not only a sample.

This is how my data would look like, see the columns: Date/ Revenue/ Orders etc.

Now I can name my stream and save it "test0416".

Once it's saved my stream will show in the stream list, top of the list. It's in STARTED status and in couple minutes it will pass in SUCCESS status.

Once it’s successful I know I was able to successfully transfer Adobe Analytics data into my Snowflake data warehouse.

What I want to do next is analyze that data and maybe build dashboards with it. It’s very easy to put any BI tool like Tableau, Domo, Power BI on top of Snowflake data.

I’m going to show you how easy it is to do this in Tableau.

Open Tableau Desktop, go to "To a server", choose "Snowflake"from the list of data warehouses, log in with your Snowflake Credentials and click SIGN IN.

Select your Warehouse, Database, Schema and look for your Table. Drag and Update and this is it, your data is now in Tableau for you to build dashboards. That simple!

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