Analyze data with BI Engine and Tableau

Create a BigQuery dataset

The first step is to create a BigQuery dataset to store your BI Engine-managed table. To create your dataset, follow these steps:

1. In the Google Cloud console, go to the BigQuery page.

   Go to BigQuery

2. In the navigation panel, in the Explorer panel, click your project name.

3. In the details panel, click more_vert View actions, and then click Create dataset.

4. On the Create dataset page, do the following:

   • For Dataset ID, enter biengine_tutorial.

   • For Data location, choose us (multiple regions in United States), the multi-region location where public datasets are stored.

   • For this tutorial, you can select Enable table expiration, and then specify the number of days before the table expires.

     

5. Leave all of the other default settings in place and click Create dataset.

Create a table by copying data from a public dataset

This tutorial uses a dataset available through the Google Cloud Public Dataset Program. Public datasets are datasets that BigQuery hosts for you to access and integrate into your applications.

In this section, you create a table by copying data from the San Francisco 311 service requests dataset. You can explore the dataset by using the Google Cloud console.

Create your table

To create your table, follow these steps:

1. In the Google Cloud console, go to the BigQuery page.

   Go to BigQuery

2. In the Explorer panel, search for san_francisco_311.

3. In the Explorer panel, expand san_francisco_311 and click the 311_service_requests table.

4. In the Explorer toolbar, click Copy.

   

5. In the Copy table dialog, in the Destination section, do the following:

   • For Project name, click Browse, and then select your project.
   • For Dataset name, select biengine_tutorial.

   • For Table name, enter 311_service_requests_copy.

     

6. Click Copy.

7. Optional: After the copy job is complete, verify the table contents by expanding PROJECT_NAME > biengine_tutorial and clicking 311_service_requests_copy > Preview. Replace PROJECT_NAME with name of your Google Cloud project for this tutorial.

Create your BI Engine reservation

1. In the Google Cloud console, under Administration go to the BI Engine page.

   Go to the BI Engine page

2. Click add Create reservation.

3. On the Create Reservation page, configure your BI Engine reservation:

   • In the Project list, verify your Google Cloud project.
   • In the Location list, select a location. The location should match the location of the datasets that you're querying.

   • Adjust the GiB of Capacity slider to the amount of memory capacity that you're reserving. The following example sets the capacity to 2 GiB. The maximum is 250 GiB.

     

4. Click Next.

5. In the Preferred Tables section, optionally specify tables for acceleration with BI Engine. To find table names, do the following:

   1. In the Table Id field, type part of the name of the table that you want accelerated by BI Engine—for example, 311.

   2. From the list of suggested names, select your table names.

      Only specified tables are eligible for acceleration. If no preferred tables are specified, all project queries are eligible for acceleration.

6. Click Next.

7. In the Confirm and submit section, review the agreement.

8. If you accept the terms of agreement, click Create.

After you confirm your reservation, the details are displayed on the Reservations page.

Connect to a dataset from Tableau

To connect to a dataset from Tableau, you need to take some steps in Tableau and then some steps in BI Engine.

Steps to take in Tableau

1. Start Tableau Desktop.
2. Under Connect, select Google BigQuery.
3. In the tab that opens, select the account that has the BigQuery data that you want to access.
4. If you're not already signed in, enter your email or phone, select Next, and enter your password.
5. Select Accept.

Tableau can now access your BigQuery data.

In the Tableau Desktop, on the Data Source page:

1. From the Billing Project drop-down, select the billing project where you created the reservation.
2. From the Project drop-down, select your project.
3. From the Dataset drop-down, select the dataset biengine_tutorial.
4. Under Table, select the table 311_service_requests_copy.

Creating a chart

Once you have added the data source to the report, the next step is to create a visualization.

Create a chart that displays the top complaints by neighborhood:

1. In the Google Cloud console, click on New worksheet.
2. Set the Dimension to Complaint Type.
3. Filter based on the dimension called neighborhood.
4. Under Measures, select Number of Records.
5. Right-click on the Neighborhood filter and click Edit Filter.
6. Add a filter to exclude null: select Null.
7. Click OK.

For more information, see the Tableau documentation.