Updated February 17, 2022
Using AtScale’s Semantic Layer with Data Science Use CasesAtScale’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…
Updated February 10, 2022
How to Turn Unstructured Medical Records Into Actionable InsightsPatient 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…
Updated February 3, 2022
How to Use a Semantic Layer Platform to Make Smarter Data-Driven Decisions at ScaleAtScale’s semantic layer platform makes data more accessible and business-friendly, and bridges the gap between business intelligence (BI) and data science teams. A semantic layer presents a consistent set of business metrics for teams across your organization to enable everyone…
Updated February 1, 2022
A Business-Oriented Semantic Layer for Your Databricks LakehouseA 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…
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…
Updated December 14, 2021
Data Insights for Everyone — The Semantic Layer to the Rescue*Author’s Note This article was originally posted as a LinkedIn article by Kirk Borne. Kirk Borne is the Chief Science Officer at Data Prime and has been an influential globally recognized leader in the data science space for 20 years.…
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…
Updated September 22, 2021
How a Semantic Layer Turns Excel into a Sophisticated BI PlatformMicrosoft 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.…
Updated September 14, 2021
Building Time Series Analysis on Snowflake with a Semantic LayerIn a recent post, we discussed how a semantic layer helps scale data science and enterprise AI programs. With massive adoption of Snowflake’s cloud data platform, many organizations are shifting analytics and data science workloads to the Snowflake cloud. Leveraging the…
Updated August 17, 2021
Making Raw Data Analysis-Ready with Dimensional ModelingTurning raw data into analysis-ready data sets for Business Intelligence (BI) and analytics teams is a challenge for many organizations. While collecting and storing information is easier than ever, delivering data sets that are fully prepped for analysts and decision…
