October 31, 2024

5 Common Data Challenges & How a Semantic Layer Can Solve Them

In today’s fast-paced business environment, the ability to make quick, informed decisions is a critical differentiator. However, organizations often face significant data challenges when it comes to data-driven decision-making. These challenges typically stem from the absence of a semantic layer,…

Posted by: Dave Mariani

October 24, 2024

How to Choose a Semantic Layer and the Technical Features to Look For

Businesses increasingly turn to semantic layers to bridge the gap between raw data and insightful decision-making in the rapidly evolving data landscape. The right semantic layer can be the linchpin for achieving faster data accessibility, improving collaboration between business and…

Posted by: Brendan Peterson

October 21, 2024

How to Optimize Modern Data Models Without Sacrificing Proven BI Techniques

Tabular models and the Data Analysis Expression (DAX) language offer Microsoft Power BI users enormous analytic and visualization capabilities. As powerful as these tools are, when using them, it can feel like one is reinventing the wheel to solve basic…

Posted by: Daren Drummond

October 10, 2024

How AtScale’s Semantic Layer Enables Trusted, Real-Time Customer-360 for Top Retail Companies

In today’s data-driven retail environment, organizations constantly collect and analyze vast amounts of customer data to better understand behaviors, preferences, and interactions. However, making this data actionable presents significant challenges, often requiring complex data engineering, aggregation processes, and pipeline management.…

Posted by: Albert Zhou

September 17, 2024

Modernizing Data Teams With a Semantic Layer and Hub and Spoke Model

In today’s fast-paced business environment, data is a crucial asset. Data teams must be modernized with advanced frameworks and technologies to leverage this data effectively. One such approach is integrating a semantic layer and employing a Hub and Spoke model.…

Posted by: Brendan Peterson

September 10, 2024

Introduction to SML – A Standard Semantic Modeling Language

It’s been over ten years since my co-founders and I launched AtScale to democratize analytics for everyone. We quickly realized that we needed to create a business-friendly view on top of the technical data so that ordinary business users could…

Posted by: Dave Mariani

August 22, 2024

Automatic Semantic Model Generation in AtScale

In today's data-driven world, making data accessible isn't just about providing raw datasets; it's about making it understandable and usable for everyone, not just for those who can write SQL or navigate complex databases. To achieve this, organizations need a…

Posted by: Dianne Wood

August 15, 2024

Why a Semantic Layer is Critical in Manufacturing

Adam Conway (SVP of Product at Databricks) recently published a blog titled “Big Data Is Back and Is More Important Than AI” and argues that the most important revenue-generating or cost-saving workloads depend on massive data sets. This is especially…

Posted by: Kieran O’Driscoll

October 31, 2024

5 Common Data Challenges & How a Semantic Layer Can Solve Them

In today’s fast-paced business environment, the ability to make quick, informed decisions is a critical differentiator. However, organizations often face significant data challenges when it comes to data-driven decision-making. These challenges typically stem from the absence of a semantic layer,…

Posted by: Dave Mariani

October 24, 2024

How to Choose a Semantic Layer and the Technical Features to Look For

Businesses increasingly turn to semantic layers to bridge the gap between raw data and insightful decision-making in the rapidly evolving data landscape. The right semantic layer can be the linchpin for achieving faster data accessibility, improving collaboration between business and…

Posted by: Brendan Peterson

October 21, 2024

How to Optimize Modern Data Models Without Sacrificing Proven BI Techniques

Tabular models and the Data Analysis Expression (DAX) language offer Microsoft Power BI users enormous analytic and visualization capabilities. As powerful as these tools are, when using them, it can feel like one is reinventing the wheel to solve basic…

Posted by: Daren Drummond

October 10, 2024

How AtScale’s Semantic Layer Enables Trusted, Real-Time Customer-360 for Top Retail Companies

In today’s data-driven retail environment, organizations constantly collect and analyze vast amounts of customer data to better understand behaviors, preferences, and interactions. However, making this data actionable presents significant challenges, often requiring complex data engineering, aggregation processes, and pipeline management.…

Posted by: Albert Zhou

September 17, 2024

Modernizing Data Teams With a Semantic Layer and Hub and Spoke Model

In today’s fast-paced business environment, data is a crucial asset. Data teams must be modernized with advanced frameworks and technologies to leverage this data effectively. One such approach is integrating a semantic layer and employing a Hub and Spoke model.…

Posted by: Brendan Peterson

September 10, 2024

Introduction to SML – A Standard Semantic Modeling Language

It’s been over ten years since my co-founders and I launched AtScale to democratize analytics for everyone. We quickly realized that we needed to create a business-friendly view on top of the technical data so that ordinary business users could…

Posted by: Dave Mariani

August 22, 2024

Automatic Semantic Model Generation in AtScale

In today's data-driven world, making data accessible isn't just about providing raw datasets; it's about making it understandable and usable for everyone, not just for those who can write SQL or navigate complex databases. To achieve this, organizations need a…

Posted by: Dianne Wood

August 15, 2024

Why a Semantic Layer is Critical in Manufacturing

Adam Conway (SVP of Product at Databricks) recently published a blog titled “Big Data Is Back and Is More Important Than AI” and argues that the most important revenue-generating or cost-saving workloads depend on massive data sets. This is especially…

Posted by: Kieran O’Driscoll