Updated April 26, 2023
High Code v. Low Code v. No Code Data ModelingWhen my co-founders and I launched AtScale almost ten years ago, we set out to democratize analytics consumption for everyone, not just database experts. We were dismayed to see the new generation of visualization tools forcing their users to become…
Updated September 15, 2022
Now Available: AI-Link Lab EnvironmentAt AtScale, we believe in applying data to solve key challenges in the modern data stack for the enterprise. Bringing together key data personas to align on objectives, data, and definitions is crucial for the successful deployment of analytics and…
Updated July 14, 2022
Creating a Time Series ML Model with AtScale’s AI-Link, Snowflake, and FeastExciting news hot off the press: AtScale has recently announced our support for the Feast feature store! This is part of our ongoing efforts to increase the interoperability of our platform to upstream data sources and downstream analytics tools. AtScale…
Updated May 31, 2022
Deliver Self-Service BI at scale with the Semantic Layer + DatabricksI recently had the opportunity to sit down for a tech talk with an extraordinary guest: Franco Patano, the lead product specialist for Databricks SQL. We had a great conversation about how a semantic layer can work with the Databricks…
Updated September 30, 2021
How to Connect AtScale to Excel to Directly Analyze Large Cloud Data SetsLast week, AtScale announced new Excel integrations and we blogged about the ability to use Excel as a powerful business intelligence platform. In this post, we will cover the basics of using AtScale to connect Excel to a cloud data…
Updated September 28, 2021
Reducing Query Complexity with MDX and AtScaleIn 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…
Updated August 12, 2021
Building a Semantic Layer with AtScale on Amazon RedshiftUsing 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…
Updated August 5, 2021
AtScale in Action: How to Make Power BI Perform on SnowflakeMany 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…
Updated July 29, 2021
User Story: The Journey to Self-Service Data AnalyticsSelf-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…
Updated July 20, 2021
Accessing Analysis-Ready Third-Party Data with a Semantic LayerIn 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,…
Updated April 29, 2021
Make Power BI Shine on Snowflake, BigQuery & RedshiftAttention Power BI enthusiasts, what I am about to say is huge! AtScale now lets you get Live Query access to cloud data warehouses within a full, multi-dimensional model. This means you get live access to your cloud data with…
Updated March 15, 2021
Using ‘Data-Sharing’ to Make Smarter Decisions at ScaleI was recently asked “what advice do you have for data-driven leaders on making smarter decisions at scale in their organizations?” I thought it was a fantastic question and there were so many things that came to mind from X…
