Dave Mariani

October 28, 2021

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…

September 9, 2021

Data governance is a broad topic with a lot of players offering commentary and strategy across the data and analytics space. Governance isn’t only about security and access control, or who can access what; it’s also about how data is…

August 26, 2021

AtScale can help BI users and data scientists operate more efficiently by getting more from their semantic layer solution to support sophisticated analyses like predictions, forecasting, and analyzing pattern anomalies as examples. In this post, we’ll discuss how to leverage…

August 17, 2021

Turning 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…

August 12, 2021

Using AtScale to establish a semantic layer on Amazon Redshift delivers several important benefits to modern data and analytics teams. As a single source of governed metrics, and dimensions, AtScale extends the value of Redshift for business intelligence and data…

August 10, 2021

Modern organizations increasingly rely on their analytics programs to help them stay competitive. And, while most every organization is leveraging the massive amounts of data available from their enterprise applications and from 3rd party data providers, it is increasingly common…

August 5, 2021

Many enterprises today choose the Microsoft stack because it fits seamlessly with the Windows OS and existing business applications. That’s why AtScale has partnered with Snowflake to streamline reporting and analytics with Power BI. If you haven’t seen our previous…

July 29, 2021

Self-service data analytics is a major milestone for many enterprises, but it often requires an iterative approach to data and analytics architectures to get there. Learn more about how a multi-billion dollar consumer packaged goods leader built a world-class self-service…

July 13, 2021

The use of data aggregations (i.e. aggregates) to accelerate query performance is a common practice for data engineering teams, but the question remains how to balance resources like time and compute consumption in the aggregation process. Rather than relying on…

July 8, 2021

In the first post of this series on Data Fabrics, we defined the enterprise data fabric design pattern and how it can transform your data and analytics operations into a self managing, data factory. And, in our second piece, we…

July 7, 2021

In our first post of this series, we explored the notion of a Data Fabric as a design pattern for assembling technologies and processes to support modern data and analytics infrastructure.   Now that we better understand what data fabric is…

June 29, 2021

Introduction to Data Fabric We have written about the concept of the “Data Fabric” in the past. While not new, it is an increasingly cited topic to help organize the many technologies and strategies employed by enterprise data teams to…