November 15, 2022
How to Streamline Data Science Workloads and Feature Engineering in SnowflakeOur partnership with Snowflake has drastically sped up our customers' data processing capabilities by eliminating the need for tedious data engineering tasks. By driving workloads directly to Snowflake, users can create accelerated time-to-prediction rates and a more efficient method to…
May 3, 2022
Performant Power BI Analysis on Snowflake with AtScaleWe've learned a lot working together with top technologists & strategists like Arun Ulag for Power BI (the leading BI tool) and Michael Gregory & Simon Field for Snowflake (the most popular data warehouse). In this blog post, we’ll recap…
February 17, 2022
Using AtScale’s Semantic Layer with Data Science Use CasesAtScale’s semantic layer allows users to have one single place to define business constructs like KPIs (i.e. time series calculations) and first-class dimensionality/hierarchies (i.e. time, geography, product, customer, etc.). Whether you are on the business intelligence (BI) or data science…
October 12, 2021
Bridging Business Intelligence & Data Science in SnowflakeThis 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…
September 14, 2021
Building Time Series Analysis on Snowflake with a Semantic LayerIn 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…
July 27, 2021
Augmented Analytics: The Convergence of BI and Data ScienceOne 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
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,…
June 16, 2021
How Insurance Companies Can Merge Foursquare Places Data with First-Party DataMany insurance companies are looking to tap the power of third-party data to gain critical insights into their potential customer base. By blending third-party data with first-party data, these insurance providers can improve their decision-making capabilities through advanced analytics and…