> AI agents: this is one page from Mammoth Analytics documentation. The index of all pages as Markdown is https://docs.mammoth.io/llms.txt. Append `.md` to any docs URL, or send `Accept: text/markdown`, to get Markdown. # Glossary > Definitions of Mammoth terms such as Workspace, Project, Dataset, Batch, View, Pipeline, Automation, Data Check, and Checkpoint, each linked to its main docs page. This glossary defines the terms Mammoth uses, in alphabetical order. Each entry links to the page that covers the topic in full. ## Activity Log The Activity Log is Mammoth's audit trail. It records the actions people take in your workspace, from creating datasets and editing pipelines to changing Automations and managing users. Workspace Owners and Workspace Members can open it from the **Monitor** page. See [Activity Log](https://docs.mammoth.io/learn/monitor/activity-log). ## Auto-sync Auto-sync is a toggle that controls whether a View or an export updates automatically when its upstream data changes. Mammoth has two independent layers: **View Auto-sync** re-runs a View's pipeline when a new batch arrives, and **Export Auto-sync** sends a View's new output to its destination after each run. When Auto-sync is on, which is the default, updates flow through. When it is off, data is held until you release it manually from the Monitor panel. See [Automations](https://docs.mammoth.io/learn/automations/#auto-sync), [Datasets and Views](https://docs.mammoth.io/learn/data-library/dataset-panel/#view-auto-sync), [Send to destinations](https://docs.mammoth.io/learn/export-share/send-to-destinations), and [Live links](https://docs.mammoth.io/learn/export-share/live-links). ## Automation An Automation runs recurring work in a project without manual steps. Mammoth has four Automation types: Dataset Refresh, Data Consolidation, File Collection, and Messaging. You create and manage them from the **Automations** tab in the Data Library. See [Automation types](https://docs.mammoth.io/learn/automations/automation-types/) and [Managing automations](https://docs.mammoth.io/learn/automations/managing-automations/). ## Batch A Batch is one version of data inside a Dataset. Each time data is added to a Dataset, it creates a Batch with its own identifier, timestamp, and row count. Batches can be combined, replaced, removed, or suspended. See [Core concepts](https://docs.mammoth.io/learn/getting-started/core-concepts) and [Batch management](https://docs.mammoth.io/learn/data-sources/batch-management). ## Checkpoint A Checkpoint is a pipeline control that pauses the pipeline at a specific step to notify your team or wait for explicit approval before continuing. Use it when a person needs to review the data before the pipeline proceeds. See [Pipeline controls](https://docs.mammoth.io/learn/transform/controls/). ## Connector A Connector links Mammoth to an outside source such as a database, a cloud data warehouse, a SaaS platform, cloud storage, or a REST API. Each connector handles authentication and data selection in a consistent flow. See [Connectors](https://docs.mammoth.io/learn/connectors/). ## Dashboard A Dashboard is an interactive set of charts and insights that you build by describing what you want to an AI assistant. It reads a View as its data source and can be published to a shareable link. See [Creating dashboards](https://docs.mammoth.io/learn/dashboard/creating-dashboards/) and [Publishing and sharing dashboards](https://docs.mammoth.io/learn/dashboard/share-dashboard/). ## Dashboard Editor and Dashboard Viewer Dashboard Editor and Dashboard Viewer are the two roles on a single dashboard. A Dashboard Editor can modify the dashboard, and a Dashboard Viewer can only view it. See the [roles and permissions matrix](https://docs.mammoth.io/learn/security-overview/access-control/#roles-and-permissions-matrix). ## Data Check A Data Check is an automated quality gate attached to a pipeline step. After the step runs, the Data Check evaluates the output against rules you define, such as row count, null percentage, unique values, or value range, and either pauses the pipeline or flags the problem and continues. See [Pipeline controls](https://docs.mammoth.io/learn/transform/controls/). ## Data Consolidation Data Consolidation is an Automation type that processes files uploaded to a source folder and merges them into a destination Dataset. It runs every time a new file lands in the folder, with no schedule, and works in a combine mode or a replace mode. See [Data Consolidation](https://docs.mammoth.io/learn/automations/data-consolidation/). ## Data Library The Data Library is where a project's Datasets live, alongside the reusable pipeline components called Parameters and Snippets. It also holds the **Automations** tab. See [Data Library](https://docs.mammoth.io/learn/data-library/). ## Data Quality Report The Data Quality Report is an AI-powered assessment that evaluates your data health using the DAMA framework. It gives an overall quality score with recommendations organized into sections. See [Data quality report](https://docs.mammoth.io/learn/explore-discover/data-quality-report). ## Dataset A Dataset is the result of importing data into Mammoth. It holds your working data in a standardized form, with a schema, metadata, and a collection of Batches. See [Core concepts](https://docs.mammoth.io/learn/getting-started/core-concepts) and [The Dataset panel](https://docs.mammoth.io/learn/data-library/dataset-panel/). ## Dataset Refresh Dataset Refresh is an Automation type that re-fetches data from a cloud source on a schedule, so a connected Dataset stays current. It only works on Datasets connected to an API or database, not on uploaded files. See [Dataset Refresh](https://docs.mammoth.io/learn/automations/dataset-refresh/). ## Draft Mode Draft Mode is a pipeline setting that queues your task changes as Pending Updates instead of running them immediately. The queued changes run together when you click **Apply now**. See [Understanding the pipeline](https://docs.mammoth.io/learn/transform/understanding-the-pipeline). ## Explore Cards Explore Cards are interactive cards that show what is inside a column: the distinct values of a text column, the distribution of a numeric column, or the timeline of a date column. Clicking values on a card filters the grid. See [Explore Cards](https://docs.mammoth.io/learn/explore-discover/explore-cards-overview). ## File Collection File Collection is an Automation type that collects files from folders in external cloud platforms into a destination folder in Mammoth. It is available on plans that include it. See [Automation types](https://docs.mammoth.io/learn/automations/automation-types/). ## Folder A Folder organizes Datasets in the Data Library. You can move Datasets and Folders into other Folders, and a Data Consolidation Automation can watch a Folder for new files. See [Cloning and moving datasets](https://docs.mammoth.io/learn/data-library/clone-move-data/). ## Insights Insights, also called View Insights, are short business observations that Mammoth's AI generates from the statistical profile of a View. You click a button and the AI surfaces the most significant observations in plain language. See [View insights](https://docs.mammoth.io/learn/explore-discover/view-insights). ## Live Connection A Live Connection is a connection from a project to a source such as a database, API, or business application. Mammoth pulls the data into a Dataset, and credentials are stored per project. Only a Project Admin can create, update, or delete Live Connections. See [Connectors](https://docs.mammoth.io/learn/connectors/). ## Messaging Messaging is an Automation type that sends scheduled email notifications with Dataset Views attached as CSV files. It runs on a recurring schedule and has no manual-only option. See [Messaging](https://docs.mammoth.io/learn/automations/messaging/). ## Metrics Metrics are single-value calculations such as total revenue, average deal size, or defect rate, built from a column in the Metrics panel. They update as you filter your data in Explore Cards. See [Metrics panel](https://docs.mammoth.io/learn/explore-discover/metrics-panel). ## Parameter A Parameter is a named value, either a number, a text string, or a date, that you reference in pipeline conditions and filters. Change the value once and every pipeline that uses it updates. See [Parameters and snippets](https://docs.mammoth.io/learn/data-library/parameters-snippets/). ## Pipeline A Pipeline is the ordered list of Tasks that transform the data in a View. It runs top to bottom, can be reused on new data, and every step can be reviewed, edited, reordered, or removed. See [Understanding the pipeline](https://docs.mammoth.io/learn/transform/understanding-the-pipeline). ## Project A Project is an organizational container inside a Workspace. It groups related Datasets and Automations together and controls which people can access them. See [Projects](https://docs.mammoth.io/learn/projects/) and [Creating a project](https://docs.mammoth.io/learn/projects/create-project/). ## Project Admin and Project Editor Project Admin and Project Editor are the two project roles shown in the product. A Project Admin controls the project's settings and members as well as everything an Editor can do. A Project Editor works with the project's data and pipelines. See the [roles and permissions matrix](https://docs.mammoth.io/learn/security-overview/access-control/#roles-and-permissions-matrix) and [Project roles and permissions](https://docs.mammoth.io/learn/projects/project-roles-and-permissions/). ## Snippet A Snippet is a reusable block of SQL or expression code that you embed in tasks using double-brace syntax. Where a Parameter holds a single value, a Snippet holds logic. See [Parameters and snippets](https://docs.mammoth.io/learn/data-library/parameters-snippets/). ## Task A Task is one transformation step in a Pipeline, such as a filter, a join, or a calculation. Each Task does one operation, can be configured in the function panel, and can be previewed. See [Core concepts](https://docs.mammoth.io/learn/getting-started/core-concepts). ## Trash Trash is where deleted Datasets, Views, Automations, and Dashboards wait before being permanently removed. Items stay recoverable for 30 days, and each project has its own Trash. See [Trash and recovery](https://docs.mammoth.io/learn/trash-recovery/). ## View A View is where you interact with your data. It shows the data in an interactive grid, with Explore Cards, a Metrics panel, and a Pipeline for building transformations. One Dataset can have many Views, and Views do not change the source data. See [Core concepts](https://docs.mammoth.io/learn/getting-started/core-concepts) and [View management](https://docs.mammoth.io/learn/data-sources/view-management). ## Workspace A Workspace is your organization's whole Mammoth environment. It is where billing and the subscription are managed, users are invited and given roles, and all Projects live. See [Core concepts](https://docs.mammoth.io/learn/getting-started/core-concepts) and [Workspace management](https://docs.mammoth.io/learn/workspace-management/). ## Workspace Owner and Workspace Member Workspace Owner and Workspace Member are the two workspace roles. A Workspace Owner has full administrative control, including users, billing, and API keys. A Workspace Member can create projects and view the Activity Log, and reaches a project only after being added to it. See the [roles and permissions matrix](https://docs.mammoth.io/learn/security-overview/access-control/#roles-and-permissions-matrix). --- Source: https://docs.mammoth.io/learn/glossary.md ยท Updated: 2026-10-03