boston–(business wire)– AtScale, a leading provider of semantic layer solutions for modern business intelligence and data science teams, today announced at the Semantic Layer Summit for organizations working to accelerate the deployment and adoption of enterprise artificial intelligence (AI). announced an expanded set of product features for These new capabilities leverage AtScale’s unique position within the data stack supporting popular cloud data warehouse and lakehouse platforms such as Google BigQuery, Microsoft Azure Synapse, Amazon Redshift, Snowflake and Databricks. .

Organizations across industries are racing to realize the true potential of their investments in data science and enterprise AI. IDC predicts that spending on AI/ML solutions will grow by 19.6%, with more than $500 billion spent in 2023. Despite this investment, Gartner reports that only 54% of AI models built make it into production, and organizations struggle to generate business outcomes that justify their investment. Operationalize the model. This disconnect presents great opportunities for solutions that can simplify and accelerate the path to business impact for AI/ML initiatives.

The AtScale Enterprise Semantic Layer Platform incorporates two new capabilities available to all AtScale AI-Link customers.

• Semantic prediction – Predictions generated by deployed AI/ML models can be written back to cloud data platforms via AtScale. The predictive statistics produced by these models inherit semantic model intelligence such as dimensional consistency and detectability. Business users can quickly explore predictions using popular BI tools (AtScale supports connections to Looker, PowerBI, Tableau, and Excel) and incorporate them into extended analytics resources for a wider range of business users can do. Semantic prediction accelerates the business outcomes of your AI investments by making AI-generated predictions easier and more timely to manipulate, share, and consume.
• Managed features – AtScale creates a hub of centrally managed metrics and dimension hierarchies that can be used to create a set of managed features for AI/ML models. Managed features can come from an existing library of models maintained by data stewards or individual working groups. Additionally, new features created by AutoML or the AI ​​Platform can also become managed features. AtScale managed features inherit semantic context, making them consistently discoverable and easy to work with at any stage of ML model development. Managed features are now available directly from AtScale or via feature stores such as FEAST, allowing AutoML and other AI platforms to train models.

Gaurav Rao, Executive Vice President and General Manager of AI/ML at AtScale, said: “The need for AI is huge and research is increasing, but many companies are still unable to take advantage of the predictive insights that AI models can generate. It can be leveraged to streamline and simplify the way companies consume and use AI today, accelerating the time to value from their AI investments.”

These new features are available immediately as part of AtScale Enterprise and AtScale AI-Link.

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AtScale accelerates the flow of data-driven insights to enable smarter decision making. The company’s semantic layer platform simplifies, accelerates, and scales business intelligence and data science capabilities for enterprise customers across industries. With AtScale, customers can democratize their data, implement self-service BI, and build a more agile analytics infrastructure to make more effective and impactful decisions. For more information, please visit www.atscale.com and follow us on LinkedIn. twitter or facebook.