Data Modeling in Sigma

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Have a data model? Great! Let’s use it.

No data model? Awesome! 

Use Sigma to create a model or start exploring model-free. It’s your choice.

Why model data in the first place?

Data models can help businesses make more informed decisions by providing a structured way to analyze and interpret data. By using a data model, a business can better understand relationships between different datasets, identify trends, and forecast future outcomes.

Increase Efficiency: A data model can help a business streamline its operations by reducing the time and effort required to access and analyze data. With a well-designed data model, data can be easily accessed and shared across different departments and systems, reducing the need for manual data entry or duplication.

By using a data model, a business can ensure that data is accurate, consistent, and complete. This is because data models provide a standardized way of organizing and categorizing data, making it easier to identify and correct errors.

As a business grows and generates more data, it can become increasingly difficult to manage and analyze that data effectively. By using a data model, a business can create a framework for organizing and storing data that can scale with its needs.

A data model can help a business integrate different systems and databases, enabling data to flow seamlessly between them. This can be especially important for businesses that use multiple software applications or rely on third-party data sources.

How do I model data in Sigma?

Data modeling can be performed in Sigma using a document type referred to as Datasets. Sigma’s Datasets offer a flexible way to build centralized data definitions and guide data exploration. Datasets function as shareable sources of data for workbooks.

Learn more about data modeling in Sigma.

Why use Sigma Datasets?

Sigma Datasets balance administrative control with the freedom for users or content creators to find, add, and trust new data.

Datasets provide a uniform user interface that is very intuitive and fast to create models without the need to know how to write code or scripts.

Where do Datasets get the data?

When creating a new Dataset, you have a choice from all of the sources Sigma has to offer:

For example, you may want to use a Snowflake table, but only use a few columns for your Dataset. When you are creating a new Dataset, you can choose any columns you want. Limiting columns makes it easier for users and also benefits query performance.

Can I adjust data types in my Dataset?

There are several adjustments you can make to Dataset columns. You are able to adjust the name, how the column is made available in Workbooks, the data type, and a text description that end users can see.

Dataset configuration does not affect source data, but rather transforms it as a user accesses a Workbook that uses the Dataset at runtime.

Can I join other Data to a Datasource?

Yes you can! When you are creating a Dataset and the data exists in two (or more) different places, Sigma makes it easy to combine it together. The user does not have to experience writing SQL or other proprietary language to make this work. Simply select the sources, common fields (join keys,) and you're done. Sigma selects the appropriate join type for you — you can also change it if you want.

Learn more about Sigma Join Types.

Columns from the joined data do not automatically appear, but rather are selectable in a Workbook:

Learn more about joining data in Datasets.

Is it hard to add columns I forgot?

Not at all. Simply edit the Dataset and select the columns you want to include (or remove). For example, add “Store City” just by clicking the “+” from the list of available source columns:

Can I add new columns too?

Yes, you can add columns to enrich the Dataset. For example, you may want to pre-calculate Order Total into a new column so that the end user just sees the new column. This saves the user time and also reduces end user calculation errors. 

All of the Sigma functions are available to you when creating new columns. 

Learn more about Sigma Functions.

Can I filter Dataset data before a user sees it?

Yes, you can limit your data to show only rows that meet certain criteria. Sigma worksheet filters live in the dataset worksheet control panel, which is positioned directly to the left panel. This allows you to modify your filter values while simultaneously watching your data respond in real time. For example, a Dataset that only shows “Product Type” of “Computers” looks like this:

Learn more about Dataset Filters.

Do Datasets support the concept of variables?

Sigma calls these “Parameters” and they are supported in Datasets (as well as Sigma workbooks). A parameter is a customizable field that can be added to a worksheet and referenced in formulas. Creating parameters in your worksheets, and referencing them in formula columns, allows you to dynamically replace values used in calculations across a worksheet.

Learn more about Parameters.

Do Datasets support Permissions?

Permission to access a Sigma Dataset can be shared, modified, or revoked by either the individual document’s owner or an organization admin. Datasets support two permission types: Can View and Can Edit.

Learn more about Dataset Permissions.

Is there a graphical view of the source data being used?

This is called “Lineage” in Sigma.

On the lineage tab of warehouse tables and datasets, you can see everywhere your dataset or warehouse table is being used in Sigma, and all of the sources your dataset relies on. This lets you see what will be affected when you make changes to a given Dataset or warehouse table.

Additionally, Sigma provides a graphical representation of data from source to presentation.

Does Sigma support Materialization?

Materialization in Sigma allows you to write datasets and workbook elements back to your warehouse as tables which can reduce compute costs and improve query performance. 

These tables are visible in your cloud data warehouse. However, they're not intended to be used as source tables for other applications. To access this data from other applications, see Sigma’s Dataset Warehouse Views feature.

Materializations are scheduled to refresh table data as configured by your Administrator. 

Learn more about Sigma Materialization.

Can I see what queries are being run?

Sigma allows users (with appropriate permissions) to see detailed information about each query that is made to source data. Business users are not likely to need this information, but analysts may want to see the queries built by Sigma.

For example, to see the queries driving a page in Sigma, click the icon as shown below and select “Query History” here:

Sigma provides detail on how long each operation is taking to fetch the queried data. Additionally, some calculations are made client-side (in the user’s browser) to further improve performance. This results in a better user experience.

Learn more about how to examine SQL Queries.

Can I see the actual SQL script(s)?

Of course, just select the desired query from the “Request Type” list and the actual SQL query will be displayed. You can even copy the script if you want to evaluate it further outside of Sigma.

Learn more about custom SQL in Sigma.

Where can I learn more about Sigma features and use cases?

Our online documentation is a great way to get high-level information on product features along with as much fine detail as you want.

Sigma QuickStarts provide “step-by-step” guides to using Sigma, exploring specific features and use-cases.

We are Sigma.

Sigma is a cloud-native analytics platform that uses a familiar spreadsheet interface to give business users instant access to explore and get insights from their cloud data warehouse. It requires no code or special training to explore billions or rows, augment with new data, or perform “what if” analysis on all data in real⁠-⁠time.