Direct Data Distribution from the Google BigQuery Data Warehouse
Automated Data Distribution can now load data directly from your Google BigQuery cloud data warehouse into one or multiple GoodData projects. With the provided tooling, you can simply connect GoodData to your Google BigQuery project, prepare tables and views that you want to use for reporting, generate a logical data model in your workspace, and configure data load and distribution frequency.
That's it! Starting today, you can use your Google BigQuery data and accelerate analytics for all your users.
Direct Data Distribution from Data Warehouses
Organize Your Data Catalog in Analytical Designer
To help users find related items in Analytical Designer and group these visually, administrators can organize measures and attributes into groups.
ADCatalogGrouping platform setting to group items by:
- Folders which enables localization for the group names, or
- Tags which enables you to have one item in multiple groups.
By default, the platform setting is set to
Disabled and users will not see any changes in their Data Catalog.
Data Catalog in Analytical Designer
Life Cycle Management: Release, Provisioning, Rollout Bricks Available
If you are managing projects via Life Cycle Management, you can now deploy and schedule the following bricks in addition to already available Users brick and User Filters brick:
- Release brick, which creates master workspaces for segments based on a predefined template (see Release Brick)
- Provisioning brick, which creates clients' workspaces under the appropriate segments, and deploys the reports, dashboards, filters, logical data model, ETL, and metadata from the master workspace to the clients' workspaces within a segment (see Provisioning Brick)
- Rollout brick, which synchronizes a segment's master workspace and its clients' workspaces: the changes that you made in a master workspace (LDM, ETL, dashboards, and so on) are propagated to all the clients' workspaces within the corresponding segment (see Rollout Brick)
REMINDER: Deprecation and Upcoming End-of-life: JDBC Driver Version 3.0.2 through 3.1.2
The JDBC driver version 3.0.2 through 3.1.2 is deprecated and will stop working on January 16, 2020.
How will this affect you?
If you are using version 3.0.2 through 3.1.2 of the JDBC driver, it will stop working on January 16, 2020. You will receive the following error message:
You are using an unsupported version of the JDBC driver.
Download and install the latest version of the driver itself or
CloudConnect from https://secure.gooddata.com/downloads.html.
Please note that the end-of-life date has changed and is now set to January 16, 2020.
Before January 16, 2020, check the version of your JDBC driver.
If your version is 3.0.2 through 3.1.2, upgrade to the latest version, 3.3.0:
- If you are using the driver directly, download and install the latest version of the driver from the Downloads page at https://secure.gooddata.com/downloads.html. If you are a white-labeled customer, log in to the Downloads page from your white-labeled domain:
- If you are using the driver via CloudConnect, upgrade your CloudConnect to the latest version: from the menu bar, click Help -> Check for Updates.
- For more information about the end-of-life rules for the JDBC driver, see Data Warehouse Driver Version.
- For more information about the deprecation of the JDBC driver version 3.0.2 through 3.1.2, see JDBC Driver Version 3.0.2 through 3.1.2.
- For information about all deprecated features, see Deprecated Features.