diff --git a/site/sigmaguides/src/Fundamentals 10: Data Modeling/assets/dm_19h.png b/site/sigmaguides/src/Fundamentals 10: Data Modeling/assets/dm_19h.png new file mode 100644 index 00000000..3b3ec20c Binary files /dev/null and b/site/sigmaguides/src/Fundamentals 10: Data Modeling/assets/dm_19h.png differ diff --git a/site/sigmaguides/src/Fundamentals 10: Data Modeling/assets/dm_37.png b/site/sigmaguides/src/Fundamentals 10: Data Modeling/assets/dm_37.png deleted file mode 100644 index b84606bd..00000000 Binary files a/site/sigmaguides/src/Fundamentals 10: Data Modeling/assets/dm_37.png and /dev/null differ diff --git a/site/sigmaguides/src/Fundamentals 10: Data Modeling/assets/dm_38.png b/site/sigmaguides/src/Fundamentals 10: Data Modeling/assets/dm_38.png deleted file mode 100644 index 54a22af3..00000000 Binary files a/site/sigmaguides/src/Fundamentals 10: Data Modeling/assets/dm_38.png and /dev/null differ diff --git a/site/sigmaguides/src/Fundamentals 10: Data Modeling/fundamentals_10_data_modeling.md b/site/sigmaguides/src/Fundamentals 10: Data Modeling/fundamentals_10_data_modeling.md index 123f4bd9..6b44bd43 100644 --- a/site/sigmaguides/src/Fundamentals 10: Data Modeling/fundamentals_10_data_modeling.md +++ b/site/sigmaguides/src/Fundamentals 10: Data Modeling/fundamentals_10_data_modeling.md @@ -2,27 +2,23 @@ author: pballai id: fundamentals_10_data_modeling summary: fundamentals_10_data_modeling categories: Fundamentals -status: Hidden +status: Published feedback link: https://github.com/sigmacomputing/sigmaquickstarts/issues -tags: -lastUpdated: 2024-10-23 +tags: default +lastUpdated: 2024-10-24 # Fundamentals 10: Data Modeling ## Overview Duration: 5 -Many Sigma users are used to creating a new workbook and then adding raw warehouse tables as the foundation for their content. This often requires the user to do extra work joining tables together and adding calculated columns. +Many Sigma users are used to creating a new workbook and then using warehouse tables as the data source for their content. This often requires the user to do extra data preparation work, like joining tables together, renaming fields or creating aggregations. This modeling logic is bound to a single workbook and is not reusable across your Sigma deployment. This can lead to duplicated effort and inconsistent reporting. -Data models avoid that work and provide business users a curated set of data with all the relevant tables, columns, and calculations pre-configured for them. This accelerates their work and also ensures that the data conforms to corporate standards. +With Data Models, you can define your data transformation and semantics in one place, and use them anywhere in Sigma. This avoids duplicating effort, and provides a single source of truth for your Analytics Engineering team to collaborate on key business logic and metric definitions. -Data modeling in Sigma allows you to structure, join, and prepare data for exploration and analysis—without writing SQL. +In this QuickStart, you'll learn how to: -By creating and defining relationships across your data sources, you empower teams to analyze clean, consistent data and leave data governance concerns to the modelers. - -In this QuickStart, you’ll learn how to: - -- Understand Sigma's data modeling philosophy +- Understand Sigma's data modeling philosophy and features - Create a data model using sample data - Define relationships across tables - Add custom columns and formulas @@ -30,14 +26,12 @@ In this QuickStart, you’ll learn how to: - Use column-level security - Use column folders - Materialize a data model -- Publish reusable models for analysis +- Deploy reusable models for analysis ### Our Modeling Approach -A primary design goal for Sigma data modeling is to make it as easy as possible to create a model so your business users spend more time focused on which data to expose, to whom, and what the standard calculations need to be. +A primary design goal for Sigma data modeling is to make model creation seamless so your data team can move fast, without managing additional complex code, and deliver governed analytics to stakeholders. -Sigma works directly on your cloud data warehouse and models data on top of the source tables, without copying or extracting it. Your data stays in your warehouse. - -Sigma models are collaborative and versioned—ideal for both data teams and business users. +Business users can focus on gaining insights from data without needing to worry about its physical structure, and can also contribute directly to the data model through Sigma’s UI. Sigma models are collaborative and versioned—ideal for both data teams and business users.