AtScale is the leading semantic layer solution for modern business intelligence teams. AtScale insulates data consumers from the complexity of raw data, exposing a business-oriented data model and virtualizing queries that leverage the capabilities of powerful cloud data platforms like Amazon Redshift, Google Big Query, Snowflake, and Databricks. Users access live cloud data through AtScale with no ETL or physical data movement. AtScale delivers the dimensional analysis capability and query performance of traditional OLAP tools (like SSAS) with no practical limitations on the size or physical location of underlying data. Learn more about AtScale below, or read the solution sheet detailing how working together, AtScale and Tableau support self-serve BI for today’s data-driven enterprises.
Solutions
AtScale
Accelerate Tableau performance and adoption with AtScale
Tableau helps people see and understand their data. AtScale delivers live, analysis-ready data to the Tableau platform – no matter what size it is or where it resides. Together, Tableau and AtScale are helping enterprises analyze massive amounts of data at the speed of thought, which is changing the way people are using data to solve their business challenges.
Learn moreOne of our top priorities was to have the ability to run rapid-fire, multi-dimensional analytics at large scale, directly from the BI tools our data users prefer. With AtScale, users can run live queries, straight to Google BigQuery at great speeds. It is not something that we saw anyone else able to deliver.
The buyer's guide to the best semantic layer tools for data and analytics
This guide looks at several technical approaches to implementing a semantic layer for your data and analytics stack. Included is an implementation checklist, technology scorecard, and chart of pros and cons with several example scenarios.
As a data and analytics leader, either on the business or tech side, reading this guide will help you adopt a semantic layer approach for your data assets. This guide explains where a semantic layer fits into modernizing your data and analytics infrastructure. It will help you:
- Drive consistency
- Reduce compute costs
- And improve ease of use for a wide variety of consumption types and use cases