Updated March 1, 2022

How to Liberate Your Data [Scientists] with a Semantic Layer

Every business decision, keystroke, or mouse click is a potentially valuable data point. Most companies don't have any trouble generating and storing their data these days, and there are mature technologies that help companies break down silos to get all…

Posted by: Gaurav Rao

Updated December 2, 2025

Developing an Enterprise Data Strategy

Many companies face challenges in developing a roadmap for data, insights, and analytics. This blog stresses how an enterprise data strategy is a critical guidepost for articulating an effective set of use cases and a clear roadmap that scales with…

Posted by: Brian Prascak

Updated February 17, 2022

Using AtScale’s Semantic Layer with Data Science Use Cases

AtScale’s semantic layer allows users to have one single place to define business constructs like KPIs (i.e. time series calculations) and first-class dimensionality/hierarchies (i.e. time, geography, product, customer, etc.). Whether you are on the business intelligence (BI) or data science…

Posted by: Daniel Gray

Updated February 10, 2022

How to Turn Unstructured Medical Records Into Actionable Insights

Patient documentation has come a long way since the days of doctors writing patient notes with pen and paper. Today, Electronic Medical Record (EMR) systems can capture, exchange, and store medical records automatically. These advances have been significant for providers…

Posted by: Dave Mariani

Updated February 1, 2022

A Business-Oriented Semantic Layer for Your Databricks Lakehouse

A semantic layer strategy lays the foundation for a scalable business intelligence and enterprise AI program and complements the power of modern cloud data platforms.  Key benefits include: Business metrics stay consistent across the organization.  Analysts can access a broader…

Posted by: Anurag Singh

Updated January 21, 2022

How A Semantic Layer simplifies Your Data Architecture

*This post was originally published by the author, Anurag Singh. You can view the original post here. Making data accessible to everyone within an organization is a challenge that most companies face. For example, data scientists generate forecasts and predictions…

Posted by: Anurag Singh

Updated October 28, 2021

The Universal Semantic Layer. More Important than Ever.

There’s been a lot of news lately about semantic layers. Google and Tableau announced their plans to connect Tableau to Looker’s semantic layer. It’s great to see the industry recognize the importance of the semantic layer in the new cloud…

Posted by: Dave Mariani

Updated September 22, 2021

How a Semantic Layer Turns Excel into a Sophisticated BI Platform

Microsoft Excel has been the workhorse analytics tool for generations of business analysts, financial modelers, and data hacks. It delivers the ultimate flexibility to manipulate data, create new metrics with cell calculations, build live visualizations and slice and dice data.…

Posted by: Josh Epstein

Updated March 1, 2022

How to Liberate Your Data [Scientists] with a Semantic Layer

Every business decision, keystroke, or mouse click is a potentially valuable data point. Most companies don't have any trouble generating and storing their data these days, and there are mature technologies that help companies break down silos to get all…

Posted by: Gaurav Rao

Updated December 2, 2025

Developing an Enterprise Data Strategy

Many companies face challenges in developing a roadmap for data, insights, and analytics. This blog stresses how an enterprise data strategy is a critical guidepost for articulating an effective set of use cases and a clear roadmap that scales with…

Posted by: Brian Prascak

Updated February 17, 2022

Using AtScale’s Semantic Layer with Data Science Use Cases

AtScale’s semantic layer allows users to have one single place to define business constructs like KPIs (i.e. time series calculations) and first-class dimensionality/hierarchies (i.e. time, geography, product, customer, etc.). Whether you are on the business intelligence (BI) or data science…

Posted by: Daniel Gray

Updated February 10, 2022

How to Turn Unstructured Medical Records Into Actionable Insights

Patient documentation has come a long way since the days of doctors writing patient notes with pen and paper. Today, Electronic Medical Record (EMR) systems can capture, exchange, and store medical records automatically. These advances have been significant for providers…

Posted by: Dave Mariani

Updated February 1, 2022

A Business-Oriented Semantic Layer for Your Databricks Lakehouse

A semantic layer strategy lays the foundation for a scalable business intelligence and enterprise AI program and complements the power of modern cloud data platforms.  Key benefits include: Business metrics stay consistent across the organization.  Analysts can access a broader…

Posted by: Anurag Singh

Updated January 21, 2022

How A Semantic Layer simplifies Your Data Architecture

*This post was originally published by the author, Anurag Singh. You can view the original post here. Making data accessible to everyone within an organization is a challenge that most companies face. For example, data scientists generate forecasts and predictions…

Posted by: Anurag Singh

Updated October 28, 2021

The Universal Semantic Layer. More Important than Ever.

There’s been a lot of news lately about semantic layers. Google and Tableau announced their plans to connect Tableau to Looker’s semantic layer. It’s great to see the industry recognize the importance of the semantic layer in the new cloud…

Posted by: Dave Mariani

Updated September 22, 2021

How a Semantic Layer Turns Excel into a Sophisticated BI Platform

Microsoft Excel has been the workhorse analytics tool for generations of business analysts, financial modelers, and data hacks. It delivers the ultimate flexibility to manipulate data, create new metrics with cell calculations, build live visualizations and slice and dice data.…

Posted by: Josh Epstein
Guide: How to Choose a Semantic Layer
The Ultimate Guide to Choosing a Semantic Layer