Blog

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 27, 2021

One of the defining themes of digital transformation is the proliferation of AI-driven insights across all enterprise business processes. With the growth of cloud data platforms, the complexity of managing big data has been radically reduced. The availability of powerful…

July 20, 2021

In a previous post, we talked about using AtScale’s semantic layer to merge Foursquare Places data with first-party data. By blending third-and first-party data, organizations can improve their decision-making capabilities using advanced analytics and predictive data modeling. In this post,…

July 15, 2021

I have always been a fan of Tableau, and we have written before on the powerful combination of Tableau and AtScale. With Tableau expanding on  its BI and Analytics position with their Salesforce.com acquisition, the potential for building powerful BI…

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…