Looker provides a whole new approach to Business Intelligence. You can use SQL queries in Looker to access data stored in Treasure Data. Use the data to create dashboards and manage data models in Looker.

Recommended Architecture for Looker

Consider Treasure Data as an event data lake where disparate event data sources (and a few slow-moving dimensions) are aggregated and processed to create more compact and cleaner data packages for further processing, analysis or visualization.

Given the size and scope of an event data lake, providing highly concurrent, interactive access to over trillions of data points while retaining schema flexibility seems technologically impossible (at least when you consider affordability). But you can work around the challenge by using a design pattern called lakeshore data marts.

We’ll continue with the data-as-water metaphor because it provides a great mental model for how data pipelines for analytics work.

Treasure Data offers Data Tanks that provide a convenient and accessible metric store and enable you to drive your Looker platform from Treasure Data, without the burden of managing one or more separate data marts.

Data Tank is an add-on feature. Contact support@treasuredata.com when you start to use Looker integration.

See more details on how to use Data Tanks.

Make the connection on Looker

Go to your Looker account. Select Admin –> Connections –> “New Connection”.

Then complete the following steps:

  1. Enter the name of the connector: any

  2. Select the dialect: PostgreSQL

  3. Enter the Data Tanks’ host and port: xxx.xxx.xxx.xxx:5439

  4. Enter the database name; datatank

  5. Enter the Username: tank_user

  6. Enter the Password: your password

  7. Enable the SSL: Checked

  8. Enter the Max Connections: 30

See Looker for more details of each parameter.

To unlock the magic of Looker, data experts describe their data in a lightweight modeling language called “LookML”. LookML tells Looker how to query the data so that everyone in the organization can create reports without needing to understand the behind-the-scenes details. Refer to the Looker documentation to learn how to get started writing LookML.

  • No labels