Dbt Labs will soon add a semantic layer in the modern data stack

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Headquartered in Pennsylvania, dbt Labs (formerly Fishtown Analytics), which offers an open-source data transformation tool called dbt and is known as a significant part of the modern data stack, is preparing to take things to the next level with a new semantic layer. .

“On our move-the-ecosystem-forward initiative, there is a bunch of iron in the fire. The biggest thing is what we call the Semantic Layer, a brand new way to access a set of business concepts (metrics, entities and more) for Business Intelligence (BI) and analytics tools, “said Tristan Handy, CEO and Said VentureBeat, founder of DBT Labs.

Current architecture

The current architecture of the modern data stack looks at the flow of information from warehouse and lakehouse to AI and BI tools for analysis projects. The problem, however, is that organizations (especially large organizations with complex structures) have different tools for different analysis needs. This can lead to tools for accessing separate copies of data from warehouses and lakehouses.

To address this challenge, a single open semantic layer of dbt code, where business metrics and concepts can be defined and made universally accessible, will sit in between. It will use any current programming structure that dbt authors can express – ref, macro, sources – all BI and analytical tools to provide the same version of truth, simplifying the whole process.

“This will solve one of the biggest problems in our space, once and for all: the” one source of truth “problem. Trying to resolve it, “added Tristan.

Modern Data Stack Architecture of Dbt Labs
Modern data stack with semantic layer


Although the CEO did not share the specifications of Semantic Layer organized by DBT Labs, a blog post he did hinted that the company could take some directions.

“Imagine being able to refer to a model instead of choosing from a physical table name inside your BI tool! This one change will give you local environmental support wherever you work, “the post reads. In addition, members and partners of the dbt community have suggested taking advantage of the level to define semantic entity and create dynamic governance and privacy tooling, among other things.

Ultimately, the company believes the move will create a lot of whitespace to help the enterprise innovate and create better products faster. The bulk of his $ 222 million Series D round will also go to this effort. The investment was led by Altimeter with multiple participants, including Databrix, Snowflake and Salesforce Ventures.

Growth and competition of DBT labs

Dbt Labs claims that its transformation tool is currently used by more than 9,000 companies. In the last year alone, the company’s customer base has tripled while revenue has quadrupled.

“Dbt takes something that was once unreadable, once required a tremendous amount of technical expertise, and turns it into something that anyone with an analytical background can take part in. It bridges the gap between data analysts who are close to the business and understand its data needs, and data engineers who specialize in data technology. DBT’s superpower is to enable these two user groups to work together in the same tool to create product-grade data infrastructure, “said Tristan.

While there are some companies that provide tools for converting and preparing data for analysis, including Datamir and Mozart data, the company does not currently see them as a “meaningful challenger.”

“DBT has become such a standard in the industry – in the last two years it has increased its installed base ninefold to 9000 companies!” In fact, this is not uncommon in the open-source world: most successful open source technologies end up becoming standards. Linux, Docker, Kubernetes, etc. However, like many open-source companies, it (also) means that our biggest commercial competition is our own open-source product, “he said.

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