Updated March 1, 2022
How to Liberate Your Data [Scientists] with a Semantic LayerEvery 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…
Updated February 22, 2022
Developing an Enterprise Data StrategyMany 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…
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 25, 2022
How Top Data Leaders Align AI & BI to Business OutcomesMany organizations still view machine learning and big data analytics through a technical prism. Business leaders know that the fundamental value proposition of these methodologies is in achieving better business outcomes. I had the pleasure to discuss this topic with…
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 November 29, 2021
How to Build a Feature Store with AtScaleAtScale was conceived as an independent semantic layer for data and analytics for business intelligence users. Leading BI teams use AtScale to create enterprise metrics hubs, enabling self-serve access to a consistent source of metrics that are tied to data…
