Count
count.co
  • Getting Started
    • What is Count?
    • Count FAQ
    • Intro to your workspace
    • Example canvases
    • Getting started guides
      • Set up your workspace and projects
        • 1. Review workspace settings
        • 2. Create and organise your projects
      • Canvas orientation
      • Your first ad hoc analysis
        • 1. Examples and templates
        • 2. Build your first queries
        • 3. Create visuals
        • 4. Caching, local cells and scheduling
        • 5. Collaborating with a stakeholder
      • Your first report
        • 1. Examples and templates
        • 2. Filters and control cells
        • 3. Sharing your report
        • 4. Alerts
  • Connect your data
    • Database connection overview
      • Athena
      • Azure Synapse
      • BigQuery
      • Databricks
      • Microsoft SQL Server
      • MySQL
      • PostgreSQL
      • Redshift
      • Snowflake
    • Refresh database schema
    • Upload CSV files
    • dbt integration
      • ☁️dbt Cloud integration
      • 👩‍💻dbt Core integration
  • Import & Export
    • Import from other tools
      • Import Miro files
      • Import SQL files
      • Import Google Sheets
      • Import Jupyter notebooks
    • Export code and results
      • Export compiled SQL and Jinja-SQL
      • Export CSV files
      • Export images and PDF files
  • THE CANVAS
    • Navigating the canvas
      • Canvas tool bar
      • Data sidebar
      • Customizing the canvas
    • Canvas objects
      • Cells
      • Text and markdown
      • Shapes and tools
      • Sticky notes
      • Frames
      • Images
      • Embeds
      • Stamps
      • Grouping objects
      • Object order and alignment
      • Locking objects
      • Scaling objects
      • Shared styles
    • Overviews
    • Templates
    • Count AI
    • Alerts and subscriptions
      • Slack integration
    • Keyboard shortcuts
  • Querying data
    • Cells overview
      • Dynamic query compilation engine
    • SQL cells
      • Referencing other cells
      • Jinja templating
      • SQL formatting
    • Python cells
    • Visual and low-code cells
      • Calculations in visuals and low-code cells
      • Joins in visuals and low-code cells
    • Control cells
      • Single and multiple selects
      • Date controls
      • Text, number, and boolean controls
      • Custom control cells
    • Local DuckDB cells
      • DuckDB on the server
    • Query caching and scheduling
    • Manage queries and results
    • Troubleshooting
  • Visualizing data
    • Visualization overview
    • Templated visuals
    • Custom visuals
      • Marks
      • Facet
      • Subplots
      • Style
      • Filters
    • Formatting a visual
      • Axes
        • Secondary Axis
      • Colors and labels
      • Legends
      • Tooltips
    • Column summaries
    • Dynamic text
    • Every Visual Under the Sun
  • Presenting and Reporting
    • Reports and Slides
  • Count Metrics
    • Intro to Count Metrics
    • Build and edit a catalog
    • Views
      • Creating views
      • Customizing views
    • Datasets
      • Creating datasets
    • Save changes to the catalog
      • Catalog validation
      • Version control
    • Exposing catalogs to the workspace
    • Caching in Count Metrics
    • Using the catalog
      • Explore from cell
  • Sharing and Permissions
    • Real-time collaboration
    • Comments
    • Sharing permissions
    • Shared links
    • Embedding canvases
  • History and Versions
    • Version control
    • Duplicating and merging
    • Data snapshots
  • Settings and administration
    • Workspace settings
      • Workspace members
      • Groups
      • Tags
      • Billing
      • Single sign-on (SSO)
        • Okta
        • Entra ID
        • JumpCloud
        • Google
        • Generic OIDC
      • Brand
    • Connection settings
    • Project settings
    • User settings
    • Roles and permissions
  • Quick guides
    • Interactive control guides
      • Date ranges
      • Date groupings
      • Search
      • Select All
  • Resources
    • Join the Slack community
  • Blog
  • Security overview
  • Terms of use
  • Pricing FAQ
Powered by GitBook
On this page
  • Creating a dataset
  • Schema
  1. Count Metrics
  2. Datasets

Creating datasets

Creating your first Count Metrics dataset.

PreviousDatasetsNextSave changes to the catalog

Last updated 2 months ago

Creating a dataset

To create a dataset:

  1. Click the + next to Dataset in the catalog builder.

  2. Select one or more views to include.

  3. Define the relationships between the views, specifying join conditions (e.g., one_to_many, many_to_one, etc.) and the appropriate join type. You can find more information on available join types in the Schema on the right-hand side.

Schema

The schema displays a list of available options you can use in the dataset YAML file.

Show the dataset YAML schema

name The name of the dataset. This must be unique within the catalog. Defaults to the file name. Optional.

label A user-friendly label for the dataset. This is what is displayed in the UI, and defaults to the name. Optional.

description A description of the dataset. Optional.

from The name of the base view of the dataset.

join A list of joins that are applied to the base view. Optional.

join[*].view The name of the view that is being joined to the base view.

join[*].constraint The condition that the join is made on. This is defined in the dialect detailed .

join[*].relationship The relationship between the base view and the joined view. This can be one of one_to_one, one_to_many, many_to_one or many_to_many.

join[*].type The type of join. This can be one of inner, left, right, or full. Optional.

here