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Set up a data warehouse

Data warehouses for dummies​

Historically, setting up a data warehouse was a complex task that required a dedicated team of data engineers. However, we now live in an era where setting up a cloud data warehouse is a breeze.

This guide will walk you through the steps to set up a data warehouse for Mitzu.

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The great thing about this guide is that it will continue to serve you in the later stages of your data journey.

Step 1. Choose a data warehouse solution​

For most companies, we recommend starting with one of the simplest solutions:

  • Clickhouse
  • Snowflake
  • BigQuery
  • PostgreSQL

In this guide, we will use BigQuery as an example.

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Google BigQuery is an excellent choice for most companies that are starting out with data warehouses. It is easy to set up and has a free tier.

Please get in touch with us if you want to use another data warehouse. You can find our Slack community here.

Step 2. Set up BigQuery (5-10 mins)​

Getting started with BigQuery is easy:

  1. Go to the BigQuery console.
  2. Create a new free account (a credit card is required), but the first 10GB of data storage is free.
  3. Go to the BigQuery console: BQ Admin. Here, you should see your default project.
  4. Create a new dataset.
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    We suggest keeping it as a single-region dataset.
  5. Once done, your BigQuery project should look like this:
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  6. Create a service account to access your data warehouse. The service account should have the BigQuery Admin role. You can change this later if needed.
  7. Create a new JSON access key under the Manage keys menu item.
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    Mitzu will use this JSON key to access your data warehouse in the next steps.
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Congratulations! You have successfully set up your data warehouse.

Step 3. Collect data into BigQuery (10-15 mins)​

Moving data into your data warehouse is also very simple. You have multiple options available:

This guide will use Jitsu, as it is the simplest way to get started.

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Jitsu is an excellent choice for most companies that need to ingest data into a data warehouse. It is easy to set up and has a very generous free tier.

By the end of this guide, you will have a Jitsu account, with data from your landing page, your application, and Stripe collected into BigQuery. You should see the result below:

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Let's get started!

Go to Jitsu and create a new free account.

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3.1. Add BigQuery as a destination​

Create your first destination by clicking the + Add button under destinations. Choose BigQuery as the destination.

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3.2. Add your landing page visits as a data source​

Create your first data source by clicking the + Add button under data sources.

Then, name your data source and create a browser key. You can leave the rest as default.

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You must embed a JavaScript snippet into your website to finalize your setup. This part is probably the easiest. Copy Jitsu's JavaScript snippet and paste it into your website's <head> section. You can find the snippet under the Setup instructions menu item.

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Finally, connect your new data source to the BigQuery destination. You can do this by clicking the Connections button in the middle of the overview page.

3.3. Add your application as a data source​

Adding the application data source is similar to adding the landing page data source. However, you will most likely use an SDK to collect the data. Jitsu currently supports multiple SDKs. You can find the list of supported SDKs under the Setup instructions menu item.

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Remember to connect your data source to the BigQuery destination.

3.4. Add Stripe as a data source​

Now we will add Stripe as a data source. This is valuable for measuring revenue inside Mitzu. Mitzu lets you analyze revenue based on user segments.

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Mitzu works best with Stripe data for consumer products. The product userID must also be stored as metadata on your Stripe customers. Follow this guide to add metadata to your Stripe customers.

The best way to integrate Stripe with Mitzu is to follow the guide provided by Jitsu. This guide will appear when you add your Stripe connector.

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Here is what it should look like:

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Step 4. Verify your setup​

As a final step, let's verify that everything is working as expected. You should see the following tables in BigQuery:

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Step 5. Connect BigQuery to Mitzu (10 mins)​

Follow the Setup Mitzu guide.