![]() The Snowflake to Data Studio connector is created with security in mind. There’s no need for separate data extractions as each time you are building a new report in Data Studio you can easily configure multiple data sources in one go and use them in your future reports. Simply connect to each data source with Supermetrics’ connectors and pull the data you need into your Google Data Studio reports. For example, if you’re storing your call, SMS, email interaction, and other customer information in Snowflake and you want to combine this data with metrics coming from your paid advertising platforms, like Google Ads, Facebook Ads or LinkedIn Ads, then that’s also possible. In addition, you can easily combine Snowflake data with data from other sources. However, if you want to use SQL to build more complex queries and blend various data sets, you can totally do that as well. ![]() And selecting tables is easy as you can just pick them from the drop down menu. All you need to do is select the tables you’d like to fetch. You don’t need to go to another website or tab to create queries or select which metrics and dimensions you want to pull.Īnother benefit of the Snowflake connector is that it’s very easy to use since you don’t have to learn complex SQL or scripts to get the data you need into Data Studio. Our Snowflake connector works fully in Data Studio’s UI. Instead of pulling data directly from their data warehouse, they were forced to export data to Google Sheets and use the spreadsheet as a data source in Data Studio. Until now, Snowflake users have had to use a clunky workaround to get their data to Data Studio. Google Data Studio is one of the best ways to visualize marketing data from Snowflake since it’s a free tool with nearly endless opportunities for customizing reports. Need your Snowflake data in Google Data Studio? Now it’s a breeze In this post we want to share some of the benefits you’ll get with our Snowflake connector and show you how to get started. With this connector, marketers can effortlessly export all their data from Snowflake and combine it with data from other sources to create reports in Data Studio or their to-go spreadsheet tool. That’s why we built a Snowflake connector for Google Data Studio, Google Sheets, and Microsoft Excel. Snowflake is a great choice for many as it can be built on top of any existing cloud platform, whether it’s Google, Amazon Web Services, or Microsoft Azure. For this blog, we use pre-existing connections that have already been discussed, but you can feel free to use whichever source you would like for your Source connection.As the volume of marketing data grows, more and more businesses are moving their data to a data warehouse. ![]() To start configuring your ADF Pipeline, you will first need to set-up your linked services, which will serve as your Source and Sink for your pipeline. All limitations around Direct Copy to Snowflake are listed in the Microsoft Copy and Transform data in Snowflake Document. To begin, we will go through some core steps that have been covered in the Getting Activity Data from Power BI Service with REST APIs blog. Sink and Source Linked Services Created.Snowflake (Create, Read, Update, Delete (CRUD) Access.Shared Access Signature (SAS) Authentication.Prerequisitesīefore we begin talking about how to copy your data using Azure Data Factory, there are a few prerequisites you need to have set up to ensure you are able to configure this for your organization. The Copy Activity you will use within your Azure Data Factory Pipeline will automatically manage the flow from staging to source for you. What this means for this blog is that you will be connecting your Azure Blob Storage as an interim staging store. What is Azure Blob Storage?Īzure Blob Storage will allow you to store and access your unstructured data at scale. For our choice we used Snowflake, however you are more than welcome to copy it to your source of choice. The purpose of Azure Data Factory in this blog is to use it as a tool to create an ETL process for you to call your Power BI REST API and GET the data from it which you will then store in a source of your choice. In essence, what this document will walk you through is how to use the Azure portal to create an application registration which you can use to get an application ID and create a client secret which you will need for a step later in this blog. To learn more about creating a service principal please refer to the documentation created by Microsoft. A service principal is an identity created within Azure to be able to access Azure resources such as applications, tools, and hosted services.
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