Boston, MA — September 10, 2024 — AtScale, a semantic layer technology pioneer, announced the open-source release of the Semantic Modeling Language (SML), a universal standard designed to promote interoperability and foster a vibrant community of semantic model builders. This significant milestone marks a new chapter in democratizing data analytics, empowering businesses and data scientists to create, share, and reuse semantic models across various platforms and tools.
Since its founding in 2013, AtScale has led semantic layer innovation, enabling business users to interact with data using familiar terms. “We realized early on the need for a business-friendly view on top of technical data,” said David Mariani, CTO & Co-founder of AtScale. “To achieve this, we created an independent, universal semantic layer compatible with any tool or platform.”
The demand for a standardized semantic modeling language has grown as the industry has evolved. AtScale is open-sourcing the SML specification to meet this need, aiming to foster model portability and collaboration. “By standardizing on a single language, we hope to inspire the creation of shareable semantic models across platforms,” added Mariani.
Introducing SML: The Semantic Modeling Language
SML represents over a decade of hands-on development, addressing customers’ needs across finance, healthcare, retail, manufacturing, and more. SML is a comprehensive, multidimensional semantic modeling language that supports metrics, dimensions, hierarchies, semi-additive measures, many-to-many relationships, and cell-based expressions.
Key features of SML include:
- Object-Oriented: SML promotes composability and inheritance, allowing semantic objects to be shared within other semantic objects and across organizations.
- Comprehensive: Built on over a decade of modeling experience, SML handles multidimensional constructs and serves as a superset of existing semantic modeling languages.
- Familiar Syntax: SML is based on YAML, a widely adopted, human-readable, industry-standard syntax.
- CI/CD Friendly: SML is compatible with Git and CI/CD practices, supporting version control, automated deployment, and software lifecycle management.
- Extensible: SML syntax can be enhanced to support additional properties and features.
- Open Source: SML is Apache-licensed, free to use in any application, and open to community innovation.
AtScale’s open-source initiative includes several vital components. Based on YAML, the SML specification supports both tabular and multidimensional constructs and is now available to the public. A GitHub repository contains pre-built semantic models, such as industry-standard data and marketplace models. In the coming months, AtScale will release helper classes, tools designed for the programmatic reading and writing of SML syntax, and semantic translators that will enable the migration of existing semantic modeling languages to SML, supporting legacy and modern tools.
AtScale’s commitment to open-sourcing SML reflects its dedication to advancing the semantic layer ecosystem. By coalescing around a single semantic modeling standard, AtScale aims to accelerate analytics adoption, facilitate migrations between proprietary vendor solutions, and bring data and analytics to a broader audience.
For more information and to access the SML specification, please visit AtScale’s GitHub repository and read this blog post.
About AtScale
AtScale enables smarter data-driven decisions by bridging the gap between data and analytics, simplifying and extending BI and data science capabilities. With its Universal Semantic Layer, AtScale empowers enterprises to create business-friendly data models that ensure consistency and accuracy across various BI and AI tools. With over a decade of innovation, AtScale continues to lead the industry, transforming how enterprises utilize and analyze their data. For more information, please visit www.atscale.com and follow us on LinkedIn.
Media Contact:
Nicole Francoeur
nicole.francoeur@atscale.com
AtScale
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