The need for accurate, comprehensive, and easily accessible data is paramount. Ensuring that data is not only available but also meaningful and trustworthy is a challenge that many organizations face.

Today, we are excited to announce the preview release of the Semantic Catalog, a new capability designed to simplify data discovery and exploration. Let's dive into what Semantic Catalog offers and how it allows anyone to search and reuse connected data assets.

What is Semantic Catalog?

Semantic Catalog is a groundbreaking innovation that provides a comprehensive, unified view of connected data assets. It is self-documenting and continuously up-to-date by default, based on the data models you define. This means that as you adjust and refine your data models within Cube Cloud, the Semantic Catalog automatically updates to reflect these changes, ensuring that your metadata is always up-to-date. This will be very different to the experience that Data Engineering teams have had previously with data catalogs, which require a great deal of manual entry and maintenance and invariably become stale. This is why we believe the semantic layer is the perfect place to have a catalog. Metadata from the semantic layer is in production and is kept current as a byproduct of engineering work.

Key Capabilities of Semantic Catalog

1. Unified Search of Connected Data Assets

Previously, data engineering teams would look through the asset lists of multiple tools in their data stack to find specific objects. With Semantic Catalog, users gain the ability to search through a unified view of connected data assets seamlessly.

Whether you are looking for modeled data in Cube Cloud, downstream BI content, or upstream tables, you can now find it all within a single, cohesive interface. This reduces the time spent jumping between different data sources and platforms, offering a more streamlined and efficient data discovery process for both engineers and consumers.

2. Insights into Data Lineage and Relationships

Understanding the relationships and lineage of your data has often been a complex and time-consuming task. Semantic Catalog simplifies this by providing clear insights into the lineage, entities, relationships, dimensions, and metrics of your data. This is crucial for data governance, as it helps you ensure the quality and integrity of your data throughout its lifecycle.

Additionally, this understanding empowers data analysts to make more informed decisions based on a comprehensive view of the data's history and interconnections.

product screenshot: data graph from source tables to cubes and views

3. Exploration of Downstream Content

Before Semantic Catalog, it was hard to know what the impact of engineering changes would be on downstream data assets like reports and dashboards. Engineers would have to check the code being run in these downstream tools to see what upstream assets they used.

Semantic Catalog facilitates the exploration of downstream charts and dashboards across all BI platforms. This means you can easily visualize how data flows from source tables through various transformations and into the reports and dashboards that stakeholders depend on. By visually navigating these connections using a Data Graph, you can quickly identify the impact of engineering work to upstream data on downstream analytics, helping you to proactively manage and mitigate potential issues. For data analysts, starting with a Semantic Catalog search will help them find trusted data faster and also understand whether BI content already exists, rather than starting from scratch.

Reducing Duplicate Efforts and Enhancing Collaboration

One of the standout benefits of the Semantic Catalog is its ability to reduce duplicate efforts in data modeling and analysis. In many organizations, data engineers and analysts often find themselves working in silos, leading to redundant work and inconsistencies in data interpretations.

Semantic Catalog fosters better collaboration by providing a single source of truth that both data engineers and analysts can rely on. This unified approach not only increases productivity but also ensures that everyone in your organization is working with the same, trusted data. Increasing the discoverability of data assets also reduces the likelihood of duplicate versions being created organically by different engineering teams or by analysts and engineers separately.


The introduction of the Semantic Catalog marks a significant milestone in our ongoing commitment to empowering data-driven organizations. By providing a broad view of connected data assets, centered on the semantic layer, this product addresses some of the most pressing challenges in data discovery and management. From reducing duplicate efforts and enhancing collaboration to offering clear insights into data lineage and relationships, Semantic Catalog will greatly enhance the way your organization interacts with data.

We invite you to preview the Semantic Catalog and experience how it can improve data discovery. Stay tuned for more updates and enhancements as we continue to innovate and expand the preview capabilities. Contact sales to learn more about Semantic Catalog and how it can connect your organization with trusted data.