Glossary

This guide serves as a quick reference on most common terms that users can encounter when using RapidCanvas user interface (UI) and notebook interface. Some most common terms in RapidCanvas UI include:

Glossary

Dashboard

Dashboard lets you create, edit and delete your current project. You can also see a complete history of every change you have made to your project. The dashboard lists all the recent projects that are created within your tenant.

Projects

When you click the Projects tab within the Workbench tab, you will be able to access all of the projects you are involved in. Go to Dashboard to view all your recent projects.

Datasets

A dataset is a data file or a collection of files you input while creating a project. A dataset is organized in rows and columns. You can add multiple files as a dataset in your project. RapidCanvas currently supports the use of .csv, .xls, .xlsx, .parquet files as datasets.

Library

RapidCanvas' library includes custom-built templates and solutions that you can reuse without requiring any coding skills.

Templates

RapidCanvas Library provides built-in templates for quick prototyping and allows you to create your templates from scratch or from existing templates. It helps you to create a specific solution by allowing the input of data from multiple sources and transforming it into a model that can be saved and used in several applications.

Logs

Logs help you to get a full picture of your processes by identifying all of the API calls, requests, and messages that occur during your workflow. You can even view the complete data for each request or message within the Logs.

Tokens

Token allows you to authenticate the notebook to connect with RapidCanvas. It allows you to securely communicate with the RapidCanvas server so that you can log into your account and access the data.

Environments

Environment provides the required infrastructure to create and manage a data project. Depending on the scale of the project, you can customize the environment. In RapidCanvas, you can create your custom environment by selecting the appropriate environment type from the Environment Type drop-down menu. If no environment is selected, the default environment is where the project is built.

Transform

Transform is a process of data modification, structuring, and processing to make it more convenient for creating the desired recipe. With RapidCanvas, you can choose from a wide range of transformation options to process the data and make a recipe.

Recipe

Recipe is a list of ordered transformations that are applied to data at different stages of the data pipeline. A recipe can be viewed as a series of transformation steps applied to the datasets in order to achieve a desired outcome.

Canvas

Canvas in RapidCanvas is a directed acyclic graph (also called DAG) that allows business users to create visualizations and dashboards with datasets. While building a model in Canvas, you can view different shapes that represent different stages of the process. The square denotes inputting the datasets, the circle denotes the transform and recipe, and the diamond denotes the output. This allows users to explore data, build predictive models, analyze insights, and visualize their findings through beautiful and interactive visualizations.

Scenario

Scenario refers to a set of instructions that runs a pipeline (or a recipe) only when certain conditions are met. Data Scientists can set a scenario that allows them to run a specific use case to predict machine learning without having to wait for all of the data sets and pipelines to be finished. It works as a trigger that ensures that given condition(s) is/are true and the workflow executes. This will make your workflow faster and reduce the number of steps.

Segment

In RapidCanvas, segments refer to the act of breaking down a large collection of data into smaller groups that are more manageable. Segmenting makes it easier to understand and work with data, especially large and complex data sets.

Workspace

A workspace is a dedicated space designed for a group of users to collaborate and work together. It provides a secure environment where data and projects are accessible only to the users who are part of that workspace. Organizations with a large number of projects often create multiple workspaces to efficiently organize and manage different streams of AI/ML problems they are working on. This helps in maintaining data isolation, ensuring that each team has access only to relevant projects and information.

User

A User is anyone who has access to the web or notebook interface of RapidCanvas. Every user is assigned a specific role that defines their level of access and actions within the platform. The scope of a user's privileges is controlled by the admin based on their assigned role. For example, a user with the DataApp View role can only view the DataApps created within a project but cannot modify them.

User Role

A User Role is a set of permissions that define what a user can do within RapidCanvas. There are four types of user roles: Admin, Business User, Demo User, and DataApp View User. These roles determine the scope of access and actions available to users on the platform.

• Admin: Admin users have the highest level of access, including the ability to invite other team members to join a tenant and assign roles to them.

• Business User: Business users have access to create, modify, and collaborate on projects within the assigned workspaces.

• Demo User: Demo users have limited access, typically used for demonstration purposes, allowing them to explore platform features without full access rights.

• DataApp View User: These users can only view the DataApps created within a project but do not have the privileges to edit or delete them.

All users gain access to RapidCanvas through an invitation to join a tenant. Admin users are responsible for assigning roles based on the user’s intended tasks. While users can be part of multiple workspaces, their roles and permissions may vary across different workspaces. Additionally, the default roles come with predefined permissions that cannot be modified.

Artifact

Any project related asset such as models that are built by users can be saved as artifacts. These artifacts can be used across projects. Typically, generic and reusable assets are saved as artifacts and are used in multiple projects. Creating, saving and accessing artifacts is available only to notebook users currently.

Model

A predictive model is built for classification and regression problems to forecast the actionable insights or future outcome using the raw data. All the models built using different datasets are stored in the Models catalog.

Data pipeline

A data pipeline is a series of data processing steps. Data pipelines automate the flow of data from one system to another, transforming it along the way.