Key concepts
Imply Polaris is a fully managed Cloud service that enables you to build modern analytic applications without worrying about the infrastructure. It provides intelligent database optimizations that empower you to get all the performance out of Apache Druid without being a Druid expert.
Polaris is designed to get you from the initial setup to production in record time. To help you get started, this topic covers the main Polaris concepts and terminology.
Organization
An organization is a top-level entity that maps to your Imply customer account. When you first sign up for a Polaris account, Imply creates an organization for you. Subsequently, you log into your organization to manage projects, add users, process data, and build dashboards.
Project
A project consists of pre-configured Polaris components sized to meet specific data analytics requirements. Tables, files, data cubes, dashboards, and visualizations all belong to a project.
Role
A role is a permission to perform an action within an organization or a project. You can assign roles to individual users or combine multiple roles to form a set of permissions, also called a group, which you can add users to. To view the available roles, see User roles reference.
Group
A group represents a collection of roles with permissions to perform certain actions in the context of an organization or a project. Instead of assigning multiple roles to an individual user, you can assemble those roles to form a group, and then assign users to that group. To learn more about groups, see Manage user groups.
API client
An API client is an OAuth client used to authenticate a third-party application against the Polaris API in a secure manner. You need to define an API client to use Polaris API resources.
An API client contains a client ID, a client secret, and a client token. Imply uses these credentials to validate your application and authorize the API calls. To learn how to enable your application to interact with the Polaris API, see Authenticate API requests.
Table
A table is the central concept in Polaris. Tables store and organize data records in a row-and-column format. If you have data, such as clickstream data, you ingest it into a table in order to be able to query and visualize it. For more information, see Create a schema.
A detail table has rollup disabled. It stores each ingested record as is. For example, an e-commerce site might keep track of each purchase that is made. When you ingest those purchase records into a detail table, the table shows one row for each purchase.
An aggregated table has rollup enabled to group individual records according to the table's time granularity and dimensions. For example, an e-commerce site might only be interested in the total sales per hour for a region. In this case, you don't need to see each sales record, only a summary by hour.
Data cube
A data cube is a multidimensional data model used to organize and visualize aggregated data. Data cubes contain data from one or more data sources and provide an interface for users to explore a data set. Data cubes offer a way for data experts to encode their own knowledge and expertise into a body of raw data, making it usable to someone who is not a data expert or who would otherwise have trouble navigating it.
Dashboard
A dashboard combines views from multiple data cubes on a single screen. Using a dashboard, you can create effective and focused data visualizations such as line charts, heatmaps, and vertical bar charts just to name a few.