Badges, Badging

Admins and Creators can add badges to workbooks, datasets, and cloud data warehouse (CDW) tables to indicate whether the content is Endorsed, has a Warning, or has been Deprecated.  Use optional badge notes to provide additional context for all organization members. For more information, see Badging: endorse, warn, and deprecate.

Big Data

Refers to very large and complex data sets that legacy data processing tools cannot handle.

Business Intelligence (BI)

Technologies and strategies used by businesses to manage and analyze business-related information stored in databases.

Calculations (calculated fields)

Calculations can be scalar (i.e., applied to columns of the same level, [column1] + [column2] , or aggregated (when operating on columns of the lower level). Formulas are applied to entire columns. Aggregated calculations can exist to the right of the grouping key, where row level data is bundled into groups based on each distinct value in the key column, or as a summary column that aggregates data at a table's highest aggregation level.

Child element

One or more data elements that share the same parent element or data source in the workbook. If a data source is modified (by a control element or manual edits), all downstream child elements may be affected. For more information, see Data source options.

Cloud Data Warehouse (CDW)

A data store in a cloud environment that is optimized for business intelligence analytics. Popular CDWs include Snowflake and Google BigQuery.

Conditional formatting

The ability to customize the appearance of table/pivot table cells or text based on specific conditions for highlighting trends, exceptions, and opportunities in your data. Workbook creators can highlight cells that contain values within a certain threshold, change the font color of select cells if they meet certain criteria, and add a color scale or data bars to display relative value. Define a formatting rule using the list of provided conditions or write a custom formula to reference other columns and add custom business logic to your formatting criteria. Conditions can be applied to select table/pivot table columns, rows, subtotals, or totals.

Control element (page control)

Control elements are one element type supported by Sigma Workbooks. Sigma users can use controls to manipulate data elements based on user input or selection. Controls behave like filters when a change in the value of a control element updates the data in any elements targeted by that control. The value of a control element can be used as a parameter when the control's identifier is referenced in the formula or Custom SQL. See Intro to Control Elements for a list of all available types of controls.

Dashboard (page, tab)

In Business Intelligence software, a dashboard is a display of visualizations that convey important business metrics and KPIs. In Sigma, workbook pages perform the function of dashboards. Dashboards have pages that appear as tabs at the bottom of the workbook. 

Sigma's legacy Dashboard document has been deprecated.

Data element

Data elements are one element type supported by Sigma workbooks. They include tables, pivot tables, and visualizations. An element's data can be sourced from a Cloud Data Warehouse table, Sigma dataset, written SQL, or an existing workbook element.

Data modeling

The act of creating a standard model of the data to be used in workbooks. In Sigma you model data using datasets. For more information, see Data modeling with datasets.

Database, database management system (DBMS)

An organized collection of data stored in a computer system. There are many different software designs for DBMS systems.


A Sigma dataset is a collection of data based on a table in the Cloud Data Warehouse, and can include aggregations and other data manipulations. A dataset functions as a centralized, shareable data definition. Admins define a dataset that includes most or all of the data needed for analysis. Workbook Creators use the dataset as the consistent source for visualizations, tables, and pivot tables. For more information, see Data modeling with datasets.

Data sources

The underlying data from a connected Cloud Data Warehouse that Sigma users can be granted access to at the connection, individual schema, or table level. Users are not restricted to a single data source per workbook or workbook page. A workbook element's data can be sourced from raw warehouse tables, Sigma datasets, uploaded CSVs, written SQL, or other workbook data elements. For more information, see Create a data element.


In Business Intelligence software, a dimension is a type of data that contains descriptive information.

Drill down (Drill path, Drill Anywhere)

An interactive feature that takes users from a general, macro level overview of a visualization, down to granular, micro details if they choose to explore further. Create a drill down control if your workbook is received by a broader target audience or to employ the same drill path across multiple target visualizations.

Dynamic text

Text generated based on a formula in a text box UI element. Workbook editors can write dynamic text to display headers or inline text that automatically updates based on your data. 


A new Workbook document that has not been saved and has a limited shelf life of 30 days if it remains unsaved. Users with Edit Workbook permissions can leverage explorations to conduct ad hoc analysis.

Filter, element filter

Sigma filters can be added to individual data elements in a workbook, across a workbook page with control elements, and in the dataset to only display data that meets certain criteria. See Data element filters for a list of all available types of element filters.

Grouping key

The column used to define a grouping in a table. Each row in the column is rearranged into single cells based on the N number of distinct values, and the rows of data to the right of the key column in the table are bundled into groups corresponding to each distinct value in the key column. The grouping key column defines the level of granularity within which the aggregate functions should be calculated. 

Input table

Sigma-managed tables that support structured manual data entry at the cell level in workbooks. This dynamic data element allows integrating data outside the Cloud Data Warehouse to facilitate what-if analysis, forecasting, and more without overwriting source data. Input tables can be empty or linked. Linked input tables are an extension of empty input tables, where users can derive data from existing workbook data elements or data sources currently used by other elements in the workbook. Users can combine input tables with other workbook data elements using lookups or joins.


A database join is a method for combining tables using matching columns from each table. The join combines two tables into one.

Key Performance Indicator (KPI)

A quantifiable and important indicator of business performance, such as total revenue, number of unique customers, or number of customer transactions.


A Sigma feature that provides an overview of the ancestry and relationships between data elements in a workbook and dataset. Data lineage allows for the convenient oversight of edits to a data element or data source an editor is viewing and its effect on downstream elements or data sources, diagnosing the source of unexpected calculations or errors, and cleaning up existing workbooks or datasets to remove unused or redundant elements or calculations.


Links are column-based relationships established between two data sources in Sigma. When a Dataset link is defined by a Sigma Admin or Creator, workbook editors can access dataset column(s) that do not appear in the source table across multiple workbooks. In addition to creating links between workbook tables (lookups), a Sigma dataset can be linked to another dataset or a Cloud Data Warehouse table. A data source can have links to multiple data sources, where each row in the source object should have at most one corresponding result in the target object (one-to-one or many-to-one relationships). For more information, see Use linked columns in workbooks.


A feature that allows users to write datasets and workbook elements back to your Cloud Data Warehouse as tables, individual of the original data source. Materialized tables are simplified versions of the complex SQL queries built in Sigma and are rewritten to your warehouse on a defined schedule (updating the previous materialization) to avoid recomputing the data source when it's used by an element in your Sigma analysis. These tables are saved in your warehouse's writeback schema (write access destination) and can help enhance query performance while reducing compute costs.


In Business Intelligence software, a measure (noun) is a type of data that you can measure (verb), usually numeric or quantitative values.


Data that describes other data. 


A metric is often a measure used for comparing or assessing quantitative data.

Sigma Metrics are custom aggregate calculations that can be reused across workbook data elements if they share a data source. A metric's logic is defined at the data source level (Sigma dataset or connection table) and can be used at any level of grouping in a workbook data element to standardize analysis across your organization. Changes to metric definitions will update everywhere the metric is used. For more information on adding metrics to your workbook, see Add metrics to data elements.


Sigma parameters are global variables associated with page controls that can be added to a dataset or workbook and referenced in formulas or Custom SQL. Parameters collect user input and allow for the dynamic update of variables in calculations when the page control's identifier is referenced in formulas, typically for what-if analysis. Manipulating the referenced control element in the workbook causes the data source and all downstream data elements to update accordingly. Additionally, you can append one or more control values to the URL for applying default filters to a workbook as it loads.


The data source from which a workbook data element inherits data (one level preceding the element in the lineage). For more information, see Data source options.


Metadata that describes a database.

SQL Runner

Sigma's SQL Runner is an environment that lets users with the appropriate permissions run and preview SQL queries against supported connections. It provides a tree menu of the available databases, schemas, and tables in the select Cloud Data Warehouse connection you can query to create new workbook data elements and datasets. See Write custom SQL for more information on how to reference existing custom SQL-based workbook elements and datasets within your queries written in the SQL Runner.

Structured Query Language (SQL)

A programming language for relational databases. Database professionals use SQL to create, update, and delete data from relational database tables.


Summaries are single value column aggregates located in a table footer that are calculated at a table's highest aggregation level. A common use case of summaries is ad-hoc aggregate calculations on one or more columns without requiring a table level grouping. Summaries can also be created in the footer of the underlying table that appears in maximized pivot tables and visualizations.


A way to organize and manage users. Admin user accounts can grant data source permissions and folder and document permissions to entire teams. To view and interact with user-backed embedded workbooks, a user must be assigned to at least one team in your organization.

Sigma Teams are what Business Intelligence software typically refer to as groups.


A feature that lets users with the appropriate permissions save a workbook as a template for convenient reusability and shareable workbook structures. In addition to templates you create, Sigma provides organizations with a set of example templates and Snowflake usage templates all of which are available in the Template gallery page on the left navigation panel of your home page.

UI element

UI elements are one element type supported by Sigma workbooks. These elements are used to provide added context, styling, and navigation to workbook pages. They include buttons, dividers, images, spacers, embeds, text, and plugins. 

Underlying table

The underlying data that makes up a visualization or pivot table element is displayed in the element's maximized view. Changes applied to the underlying table of visualizations or pivots are automatically reflected in the element itself. Data elements can be maximized in any workbook mode, but can only be edited in Edit and Explore modes.


A database union is a method for combining the results of two or more SELECT queries.

Usage Dashboard

A set of Sigma-built dashboards that Admin accounts or custom accounts with appropriate permissions can access to monitor how their organization uses Sigma. Users can modify the supplied controls to filter usage data or maximize data elements for more Explore mode capabilities. See Usage overview for update intervals specific to each Usage Dashboard.

Version Tag

A feature in Sigma Workbooks that allow users to employ a software development lifecycle (SDLC) to manage, control, and organize multiple iterations of their workbooks. Admin user accounts or workbook owners can create and assign tags to a workbook to control which workbook versions are viewable by your users. This lets users modify workbooks at different stages or versions without affecting the experience of those using the Production version, where finalized changes on the Development copy can be easily migrated to Production with tag reassignment.

Warehouse view

Warehouse views are virtual tables written to your warehouse's write access destination that users can query using Sigma or other applications in your data ecosystem. In Sigma, warehouse views can be created on workbook elements and are automatically created on datasets sourced from write access enabled connections. These tables act as views representing SQL query logic defined by the data element, input table, or dataset from where the view originated. Workbook warehouse views are automatically updated each time the workbook is published to reflect the latest published element data. For more information, see Create and manage workbook warehouse views.


A Sigma workbook is a document consisting of one or more pages home to data elements, control elements, and UI elements. Workbook Creators can use raw warehouse tables, Sigma datasets, uploaded CSVs, written SQL, or existing workbook data elements as the source for data elements. Workbooks evolve through draft, publish, and explore lifecycle states to support collaborative ad hoc data exploration and reporting across your organization. The Edit, Explore, and View modes a user has access to on any given workbook depend on the workbook permissions and the user's assigned account type. Workbook version history is a list of edits for all prior publications and are helpful for reviewing drafted changes, reverting to previous publications, or identifying the user responsible for a specific set of changes.


In Sigma, a workspace refers to a top level folder. Workspaces provide a way to organize and share content with specific members or teams within your organization. Items placed in workspaces can be accessed by individual users or teams who have permission to that workspace. A team can be granted different levels of access to different workspaces, and multiple teams can be granted different levels of access to a single workspace.