February 8, 2022
Developing Smarter, Faster Insights from Business IntelligenceMany companies struggle with making data available rapidly, while structuring and integrating this data effectively to enable the creation of actionable business intelligence insights and analytics. With an ever-increasing amount of data available via modern data platforms, companies need to…
December 16, 2021
AtScale Supports DataRobot Core for Code-First Data ScienceAtScale partner DataRobot today announced DataRobot Core, a program including platform enhancements, resources, and community support targeting code-first data scientists. Code-first data scientists and enterprise AI developers have a specific set of needs from technology providers - requiring the flexibility…
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…
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…
September 1, 2021
How EverQuote Democratized Data Through Self-Service AnalyticsDuring our recent webinar on scaling self-service analytics, AtScale spoke with Kwan Lee, EVP of Engineering at EverQuote about its multifaceted self-service approach to data analytics for business users and machine learning. EverQuote operates a leading online insurance marketplace, connecting…
August 26, 2021
Leveraging Calculated Measures in AtScale for Time Series AnalysisAtScale 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 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…
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…
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…
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,…
