The Rise of the Semantic Layer: Enabling Speed, Scale and Cost Effectiveness To Deliver Actionable Insights and Analytics

The rise of the semantic layer

It’s hard to believe that just 15 years ago, big data and cloud technology emerged with the introduction of Hadoop and cloud vendor offerings. Over the past 5 years, most enterprises have moved to the cloud, motivated by the dual need for digital transformation of their business, coupled with embracing cloud-based data platforms and tools to realize the benefits of advanced insights and analytics. Most companies have now migrated to the cloud, or are in the process of doing so, while many companies have made their data available in a cloud-based data lake. Research from Harvard Business Review Analytic Services confirms the transformation and recent acceleration to the cloud:

  • 81% of survey respondents say that cloud is very or extremely important to their organization’s future strategy and growth
  • 67% of senior executives surveyed said their organization has accelerated its plans for cloud adoption, up from just over half the year before
  • 53% of respondents say they increased investment in net new cloud applications, services, and/or infrastructure
  • 41% say their organization has focused on new or different use cases for cloud over the last year, a jump from the 28% who reported doing so as a result of the pandemic
  • 35% of respondents indicate that 60% or more of their workloads are in the cloud, and more than half of respondents (54%) say that 40% or more of their infrastructure and applications are in the cloud today 

The Need for Speed, Scale, and Cost Effectiveness

Why are companies moving to the cloud? According to the same research report, the top five (5) reasons cited by executives are as follows:

  1. Agility – 52% cite increased business agility
  2. Data and Analytics – 42% cite the ability to access/analyze/act on data/provide insights 
  3. Cost Reduction – 42% cite cost reduction / flexibility
  4. Accelerated Innovation – 39% cite accelerated innovation
  5. Standardization and Efficiency – 39% cite increased standardization/process efficiency 

When asked where the greatest focus will be in the near future, the #1 response by executives was “Improving strategy for managing and using data across the technology environment” — essentially companies have moved their “Data” to the cloud, but they have yet to deliver “Actionable insights and analytics” from all of this data being available in a single location.

Fundamentally, we use data to answer business questions. To do so, businesses need actionable insights and analytics. As the amount of data — and its importance — increases exponentially, organizations need a way to deliver these actionable insights in a way that is fast, scalable, and cost-effective. 

Delivering Actionable Insights and Analytics  – Key Drivers of Value





Faster time to insights with fewer resources

More data sources, users, and uses, including self-service

Improved productivity and infrastructure utilization and optimization

Governed access, activities, usage, and compliance 

Actionable Insights and Analytics – Relevant, Actionable, Impactful

Semantic Layer Rising

Over the past two years, there has been a tremendous resurgence in using the semantic layer among large enterprises. This traces to their recent experience migrating to modern data platforms and now experiencing the need to improve speed, scale, and cost savings for AI and BI — being able to generate actionable insight from newly available data sources for many new users and use cases. The good news is that recent research affirms the value of using a semantic layer — and the stark contrast to those who don’t use a semantic layer. The research points to companies realizing the promise of successful, impactful data and analytics programs using a semantic layer, including to deliver effective data governance.

According to a recent report from Ventana Research, organizations that have successfully implemented a semantic model/layer:

  • Are significantly more satisfied with analytics (77% compared with 33% overall)
  • Have more of the workforce engaged in analytics (43% compared with 23% that have more than one-half the workforce using analytics)
  • Find analytics capabilities completely adequate (62% vs. 33% overall)
  • Say data governance capabilities are completely adequate (51% vs. 25% overall)
  • Are more comfortable with self-service (54% very comfortable vs. 14% overall)

Value of Semantic Models - Ventana Research

Further research from DBP Institute cited additional benefits of using a semantic layer.The report found that companies using a semantic layer cite a 4.2x improvement (i.e., a magnitude of 4.2 times improvement over the base level of performance from not using a semantic layer) in performance with less than half the effort required (e.g. savings in both number of resources, hours, project time / duration, and overall cost). This is a significant order-of-magnitude improvement in performance as well as a reduction in effort and cost. It means that typically a project that takes four months to complete could be done in just four weeks using a semantic layer.

Performance improvement was significant and consistent across every measure.

  • 4.4x improvement in time-to-insights (e.g., insights and analytics development)
  • 4.4x improvement in number of self-service users, data sources, metrics consistency
  • 4.2x improvement in cloud analytics performance
  • 3.7x improvement in cost savings

AtScale Semantic Layer: Enabling Actionable Insights for Everyone

AtScale provides a semantic layer, which sits between the data source layer and the insights consumption layer (e.g., AI and BI tools). The semantic layer converts dat a into actionable insights via: 

  • Automation (self-service data access, preparation, modeling, and publishing)
  • Alignment (centralized data product management and governance with a single, consistent metric store)
  • Acceleration (cloud analytics optimization, BI query speed optimization, multidimensional OLAP in the cloud, AI-based data connectors, and automated PDM tuning)

These capabilities support insights and analytics creators, enablers, and consumers without requiring data movement, coding, or waiting.

AtScale Semantic Layer
Enabling Actionable Insights for Everyone
Providing Automation + Alignment + Advancement
With No Data Movement, No Coding, and No Waiting




Self-service data access, preparation, modeling, publishing for AI & BI

Centralized Data Product Management with Single Enterprise Metric Store

10X Increase in Query Performance, Automated Tuning, Cloud OLAP


GigaOm Sonar Chart - semantic layers and metrics stores

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