November 1, 2021

Why You Need Next-Gen OLAP

Before You Break Up with OLAP While relationships can be challenging at times, they are hopefully worth the effort. When your significant other repeatedly leaves the cap off the toothpaste or leaves dirty dishes in the sink, it might drive…

Posted by: Dave Mariani

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

October 12, 2021

Bridging Business Intelligence & Data Science in Snowflake

This is the first of a three part blog series discussing the power of AtScale and Snowflake to help enterprise data science teams scale and leverage the agility of a cloud based infrastructure.  We have written before about the power…

Posted by: Daniel Gray

October 7, 2021

How to Leverage the Power of AtScale with Ad Hoc Analysis in Excel

No matter how sophisticated and agile an enterprise BI program may be, there is always a need to go deeper than canned reports and dashboards. Business analysts’ primary role is to figure out what the data is saying and support decision…

Posted by: Mario Mathiss

September 28, 2021

Reducing Query Complexity with MDX and AtScale

In the previous blog in this series on Excel + AtScale, we demonstrated how to connect Amazon Redshift to an Excel Pivot-Table. AtScale is able to leverage Microsoft’s MultiDimensional eXpressions (MDX) protocol to natively deliver a dimensional analysis experience to…

Posted by: Mario Mathiss

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

November 1, 2021

Why You Need Next-Gen OLAP

Before You Break Up with OLAP While relationships can be challenging at times, they are hopefully worth the effort. When your significant other repeatedly leaves the cap off the toothpaste or leaves dirty dishes in the sink, it might drive…

Posted by: Dave Mariani

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

October 12, 2021

Bridging Business Intelligence & Data Science in Snowflake

This is the first of a three part blog series discussing the power of AtScale and Snowflake to help enterprise data science teams scale and leverage the agility of a cloud based infrastructure.  We have written before about the power…

Posted by: Daniel Gray

October 7, 2021

How to Leverage the Power of AtScale with Ad Hoc Analysis in Excel

No matter how sophisticated and agile an enterprise BI program may be, there is always a need to go deeper than canned reports and dashboards. Business analysts’ primary role is to figure out what the data is saying and support decision…

Posted by: Mario Mathiss

September 28, 2021

Reducing Query Complexity with MDX and AtScale

In the previous blog in this series on Excel + AtScale, we demonstrated how to connect Amazon Redshift to an Excel Pivot-Table. AtScale is able to leverage Microsoft’s MultiDimensional eXpressions (MDX) protocol to natively deliver a dimensional analysis experience to…

Posted by: Mario Mathiss

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