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The Count Metrics semantic layer closes the gap between your data and how the whole organization wants to use it.
Use governed metrics, datasets and aggregations to define how the organization uses its data, and create a trustable environment for analysis.
Count Metrics views and datasets are configured in simple YAML, tracked by version control, and give you full control over how users will interact with data.
Even more than before, Canvases are jumping off points for exploration.
With a single click, users can jump into Explore view for a visualisation, introduce filters and new dimensions to get under the skin of the data, before reverting back, or creating a whole new canvas around their work.
Views and datasets are defined as YAML files and stored in Git for easy iteration, complete with commits, rollbacks, and viewable history to aid governance.
Whenever you update definitions, Count Metrics will check every dependant cell across the workspace, highlighting what will break, what will remain broken, and what will be fixed.
Speed up the organization's canvases by caching the entire semantic model to a scheduled defined by a flexible Cron-syntax.
Create consistency across the organization by defining how each metric will be displayed, avoiding confusion and misrepresentation.
Use catalogs to expose specific parts of your data to the right people on a project-by-project basis.
Maintain correctness in metrics like averages, totals, and ratios regardless of how data is subsequently grouped or filtered.
Stay up to date with all things count, data and problem solving.
