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…

Posted by: Dave Mariani

September 22, 2021

How a Semantic Layer Turns Excel into a Sophisticated BI Platform

Microsoft 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.…

Posted by: Josh Epstein

September 14, 2021

Building Time Series Analysis on Snowflake with a Semantic Layer

In 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…

Posted by: Daniel Gray

September 13, 2021

10 Ways AtScale Helps Organizations Scale Data Science and Enterprise AI

AtScale has been helping bridge Enterprise BI and Data Science for years, recently announcing AtScale AI-Link to simplify access to our semantic layer platform with a Python library designed for data scientists. We clearly see an explosion of interest around…

Posted by: Josh Epstein

September 9, 2021

How Analytics Governance Empowers Self-Service BI

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…

Posted by: Dave Mariani

August 17, 2021

Making Raw Data Analysis-Ready with Dimensional Modeling

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…

Posted by: Dave Mariani

August 12, 2021

Building a Semantic Layer with AtScale on Amazon Redshift

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…

Posted by: Dave Mariani

August 10, 2021

Breaking the Cognitive Bottleneck with Prescriptive Analytics

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…

Posted by: Dave Mariani

July 27, 2021

Augmented Analytics: The Convergence of BI and Data Science

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…

Posted by: Daniel Gray

July 20, 2021

Accessing Analysis-Ready Third-Party Data with a Semantic Layer

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,…

Posted by: Daniel Gray