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/ 6 MIN READ

Cloud Data Warehouse Modeling: Traditional vs. New

New data model advancements (nested and non-scalar data types) for data lakes and cloud data warehouses are a game changer. However, the existing BI and AI toolsets are really not geared to take advantage of these new innovations. AtScale’s Adaptive Cachet will readily accept your existing star schemas and optimize them for the data denormalization and full table scans these data platforms prefer automatically.

Posted By: Dave Mariani

/ 5 MIN READ

Interactive, Large Volume AI/ML Queries At Scale And Without Data Movement for Self-Service Analytics Empowerment

AtScale’s 2019.2 product release introduces a time-series and time-relative analysis capability for large volumes of data across disparate databases and platforms. This enables data analyst and data science teams to easily access large volumes of time-series data and quickly query and configure data for any (BI), artificial intelligence (AI) or machine learning (ML) tool.

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/ 6 MIN READ

Why AtScale Wins in the Cloud Data Platform Ecosystem

“Never make permanent decisions on temporary feelings”. Technology is risky, and architectural decisions can have a considerable effect on the viability of your business. This post lays out strategies to future-proof your data architecture including rules around virtualization, security, reducing complexity.

Posted By: Matt Baird

/ 5 MIN READ

Real-Time Data: Satisfying the Need for Speed in BI

Business Intelligence (BI) transforms how enterprises make decisions by delivering insights across the entire business. These insights are limited only by the curiosity of the people asking the questions and the speed at which the systems and software that support analytics can perform. BI relies on acceleration and performance (a.k.a. “speed”) to enable data exploration and data mining at a tempo that keeps the human brain engaged.

Posted By: Chuck Smith

/ 3 MIN READ

Seamless Adoption of Snowflake in the Cloud: Rakuten with AtScale

Rakuten, a leading cashback and rewards website, initially used AtScale to improve analytics performance on Hadoop. AtScale enabled Rakuten to seamlessly migrate to Snowflake while continuing to optimize performance on their new cloud data platform.

Posted By: Cort Johnson

/ 7 MIN READ

Conceiving Valuable Data Driven Insights

The investment in big data made in recent years by companies has been significant. Many are now looking to capitalize on the insights to be discovered in their expansive data lakes. Developing an analytic solution is a difficult and laborious process.

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/ 6 MIN READ

Bridging the Gap: PowerBI on Databricks

AtScale has a strong history of collaboration and innovation with Microsoft, and was the first semantic layer platform to introduce native support for Microsoft’s Data Analysis Expressions (DAX) query language. This support lets Power BI…

Posted By: Kieran O’Driscoll