GoodData.CN 1.0

Introducing GoodData Cloud Native

GoodData Cloud Native is an analytics platform that you can deploy in Kubernetes next to your data in a public or private cloud environment or as an on-premises solution.

GoodData.CN is built to scale with microservices, it connects to your data source, and can be integrated with your user authentication setup. 

Using declarative APIs, whatever you do and build with GoodData can be easily stored in a version control system.

Your GoodData.CN resources:

• GoodData Slack Community on Slack 
• GoodData Support Portal
• GoodData.CN Getting started, Documentation, and API

Key Components of GoodData.CN

GoodData analytics engine connects directly to your data warehouse and translates all the analytics queries to SQL in real-time. It works with a semantic layer for data relations and calculation definitions.

Data Source connectors

Data source connectors connect GoodData.CN with a data source that you plan to use for data analysis and visualisation.

Currently, GoodData.CN supports the following data source connectors:

• PostgreSQL
• Snowflake
• AWS Redshift
• Vertica

Data Modeler & Logical Data Model (LDM)

The logical data model defines what data will be available for use in your analysis. LDM also contains information about which tables (datasets) can be joined together and how. This allows end-users to build insights and dashboards in a simple drag-and-drop interface without the need to write complex SQL queries.

Multi-tenant real time analytics

GoodData.CN works with what we call workspaces. All your analytical work takes place in a workspace - from connecting to a datasource, through creating an LDM, to building insights and dashboards.

Workspace is a tenant/sub-tenant environment that can be assigned per-user or per-use-case/project. Workspaces can be organised in hierarchies with parent-child relations in order to share data structures and visualisations. Workspaces can have custom declarative filters assigned in order to achieve customisation per each.

Workspaces are connected to data sources on a real-time basis, without necessity to use ETL.

Self-service analytics with visual tools for building insights and dashboards

Once you define your logical data model, you can start building insights and dashboards on the top of your data. Insights are unique chart types that you can customize both visually and functionally. Dashboards are complex data visualisations that consist of customised combinations of insights.

You can share the insights and dashboards with your customers or clients in B2B use cases, or embed both tools into 3rd party apps through the API and SDK.

Declarative API and integration with GoodData.UI SDK

Every part and object of GoodData.CN can be accessed and managed through the API layer (RESTful). Objects are stored in a declarative way in order to enable app management through a version control system.

Known limitations

• ACL limited functionality. GoodData.CN 1.0.0 does not contain user access rights and roles for application objects. All users that are allowed to access the application have the equivalent of administrator rights. This will be addressed in future versions.
• AWS Redshift integration's support for analytical functionality Period over Period is limited in the GoodData.UI. The following Period over Period scenarios are not supported:
  • DayOfWeek
  • DayOfMonth
  • DayOfYear
  • WeekOfYear
  • MonthOfQuarter
  • MonthOfYear
• Workspace ID is limited to alphanumeric characters [A-z0-9]+. Special characters such as '-' (hyphen), '_' (underscore), and '.' (period, full-stop) are not supported.
• When you first use Analytical Designer to build insights, error message Connection failed, try again later may appear during. You may ignore the message as it appears in error and does not affect Analytical Designer.