Businesses Using a Semantic Layer for BI and AI Initiatives Cut Costs by 50% and Complete Analytics Projects 4 Times Faster

AtScale, the leading provider of semantic layer solutions for modern business intelligence and data science teams, released the results of a new report entitled “Business Impact of Using a Semantic Layer for BI & AI.” Conducted by the DBP Institute, a data and analytics research firm, the report quantifies the business impact of using a semantic layer for a company’s business intelligence (BI) and artificial intelligence (AI) initiatives.

A semantic layer maps complex enterprise data into well-defined business metrics, creating a single, consistent, structured, integrated data product (dataset) ready for analysts and data scientists to consume. A semantic layer enables centralized governance while supporting distributed data product creation across teams.

Businesses using a semantic layer realized a dramatic improvement over the base level performance of those not using a semantic layer. Respondents cited a greater than 4 times improvement in time-to-insights, scale and cost savings from data and analysis projects.

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Key findings about semantic layer use included:

• Lowers Costs: Using a semantic layer reduces the cost of analytics and AI/ML projects by 50%.
• Speeds Time-to-Results: A semantic layer cuts the completion time for a typical project to one quarter of the typical length, from 4 months to just 4 weeks.
• Fewer Resources Required: The research showed that semantic layer use resulted in a 46% reduction in level of effort needed.

“The semantic layer is a proven, trusted software component within the modern cloud data platform technology stack that focuses on improving the speed to actionable insights for BI and AI/ML,” said Prashanth Southekal, managing principal, DBP Institute. “This research, based on actual experience from senior enterprise data and analytics participants who have chosen to deploy the use of a semantic layer, quantifies the actual benefits of using such a solution to realize the benefits of achieving speed, scale, and greater cost savings to deliver actionable insights from AI and Business Intelligence (BI).”

Businesses using a semantic layer generated a 4.2x improvement in performance, with less than half the effort required.

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This is a significant order-of-magnitude improvement in performance, as well as a dramatic reduction in effort and cost, when measured against the base level performance of not using a semantic layer.

Performance improvement was significant and consistent across every measure:

• Speed – 4.4x improvement in time-to-insight (e.g., insights and analytics development)
• Scale – 4.4x improvement in number of self-service users, data sources, and metrics consistency
• Performance – 4.2x improvement in cloud analytics performance
• Productivity – 43% fewer hours required to complete a typical project, saving resource costs
• Cost Savings – 3.7x improvement in cost savings

“This research validates what leading organizations have already discovered – that leveraging a semantic layer within their analytics infrastructure can have a tremendously positive impact on overall success,” added David Mariani, CTO and co-founder of AtScale. “More robust projects can be accomplished in less time, with fewer resources, making it easier for analysts to drive value from a business’ data assets.”

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