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April 25, 2024

AtScale Announces Major Upgrade To Its Semantic Layer Platform

In today’s data-driven world, organizations are constantly seeking innovative solutions to extract maximum value from their data stack. However, with the rise of AI, organizations are dealing with increasingly complex data structures and models. This has made it more challenging for them to have a unified and accessible data stack that engages both technical and non-technical stakeholders. 

Semantic layers help simplify the complexity by providing a foundational framework for a consistent way of interpreting and analyzing data. With semantic layers, self-service users can find and share data without needing to know how to code. 

AtScale, one of the leading providers of semantic layer solutions, unveiled next-generation product innovations aimed at advancing the capabilities of its platform and ushering the industry into a new era of data-driven innovations. 

The product’s innovations were announced at the Semantic Layer Summit – a one-day virtual event that features enterprise data leaders & top industry technologists. 

AtScale’s next-gen platform now features a Universal Semantic Hub that supports all AI and business intelligence (BI) tools. This enables teams to work with their preferred data products while having access to consistent views of live cloud data. This will help break down data silos, minimize data duplication, and increase accessibility to business-ready data. 

The update also features improved collaboration capabilities with better discoverability, oversight, and reusability of semantic objects. This upgrade enables more efficient collaboration between business stakeholders. This means that business analysts, data engineers, and other stakeholders can now collaborate on semantic modeling under a unified platform. 

 “The semantic layer serves as a key technology enabler for delivering the best of both worlds; business-friendly, self-service analytics, but with governance and control. By supporting traditional BI teams alongside a new generation of analytics users, our ‘plug and build’ approach accelerates data-driven innovations in a unique way.” said Dave Mariani, founder and CTO, AtScale.

AtScale has also launched a free public preview version of its semantic layer platform called the Developer Community Edition, signaling a major leap in democratizing analytics. The Developer Community Edition is a free version of AtScale’s full-featured semantic layer platform and features a new modeling language called semantic modeling language (SML). 

The new release also features a public GitHub repository for pre-built and reusable semantic models, allowing community members to learn, share, and innovate together. The pre-built model libraries can be used for various applications including operational efficiency in finance, advanced analytics transitions, and insights enhancement for retail organizations. 

Data that is enriched with business context is significantly more valuable to an organization. The latest version of the platform features a metadata hub to simplify the process of integrating any model or approach with GenAI and LLMs within the appropriate business context. 

(metamorworks/Shutterstock)

This allows companies to give business context to both traditional AI as well as GenAI models. They can use the metadata hub to enrich their labeling and vectorization of unstructured data objects. 

AtScale now offers seamless integration with dbt by adding its SML translator for dbt. Teams can use dbt semantic models to work with AtScale’s support for Excel, Tableau, Power BI, and other consumption tools. We can expect AtScale to add more integrations to its platforms, including integration with vector databases and other elements of the GenAI ecosystem. 

The announcement of new product innovations and the public preview of the AtScale Developer Community Edition are an indicator of AtScale’s commitment to helping organizations create value from their data and AI investments, and to making analytics benefits accessible to all. 

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