Want to do multi-dimensional analysis directly on data in Snowflake AtScale

Anurag Singh
4 min readSep 19, 2022

Want to Unify, integrate, analyse, and share previously siloed data with a near-zero management platform that delivers virtually unlimited scale and concurrency try Snowflake. Snowflake cloud data warehouse is a foundation to build enterprise analytics and business intelligence programs.

AtScale provides the premier platform for data architecture modernization. AtScale connects you to live data using one set of semantics without having to move any data. Leveraging AtScale’s Autonomous Data Engineering, query performance is improved by order of magnitude. AtScale inherits native security and provides additional governance and security controls to enable self-service analytics with consistency, safety and control. AtScale’s Intelligent Data Virtualization and intuitive data modelling enables access to new data sources and platforms without ETL and or needing to call in data engineering..

The combination of AtScale and Snowflake delivers a powerful platform for BI teams to build robust business insight programs by providing a business-oriented data model and semantic layer on top of flexible cloud data infrastructure. AtScale data models support analysts and data scientists working in a wide range of tools making analysts more productive, infrastructures more cost-efficient, and time to insight faster. Teams spend more time delivering insights, less time manipulating and prepping data. AtScale helps Snowflake customers build world-class business intelligence and data science programs while leveraging the full flexibility and capability of the Snowflake Data Cloud.

Below we talk about use cases of AtScale and Snowflake together:

1) How to use AtScale + Snowflake to eliminate data marts like Microsoft SQL Server Analysis Services(SSAS) OLAP cubes and run those workloads natively in the Data Cloud.

Problem Statement

SQL Server Analysis Services (SSAS) is a popular platform for delivering dimensional analysis. SSAS exposes “cubes” to end users which makes data easier to consume for business users.SSAS has several drawbacks, including its inability to handle big data and the complexity of defining and modifying dimensional models. Further, using SSAS requires moving data out of Snowflake which is complex and fails to leverage the power of the Snowflake Data Platform.

Solution

AtScale delivers an architecturally superior alternative to SSAS by allowing you to do multi-dimensional analysis directly on data in Snowflake, without extracting data to pre-aggregate it. Ultimately, this helps organizations deliver better sales analytics velocity and granularity, as well as delivering a powerful platform for BI teams to build robust and usable business insight programs. Removing SSAS from the equation means better agility and performance, faster modelling and accelerated data access. Use the below table for a comparative study between AtScale vs SSAS.

So where does AtScale fit in your Modern Data Architecture?

2) Providing Excel Users with Live Access to Data for BI And Analytics Quickly, Easily and Securely

AtScale is the only solution that allows Excel users to connect in real time to data in Snowflake. Using AtScale when we create a virtual OLAP cube on top of Snowflake keeping the same great SSAS MDX power with a platform that is built for today’s data types and scalability. Excel users can perform rapid querying and multidimensional analysis on this data. This is done through AtScale’s Universal Semantic Layer, which translates MDX queries from Excel into Snowflake-specific SQL instantly. AtScale’s intelligent data virtualization capability allows multiple data sources, both in the cloud and on-premises, to be presented as a single data view to Excel and other business intelligence tools, greatly enhancing users’ data mining power. AtScale provides Excel users with fast, easy access to a consistent data view on Snowflake, while virtualizing data, accelerating query times, and reducing costs.

Benefits of AtScale for Excel and Snowflake Users

· Zero Disruption-Transition from expensive on-premises data warehouses to Snowflake with no user disruption. A primary obstacle to cloud migration is the potential negative impact on business users, including downtime, re-training, and lack of available data. AtScale reduces this risk by providing a logical view of an enterprise’s data that persists regardless of where the data is stored, thereby eliminating the need to re-write applications or re-train employees on new software.

· Real-time MDX connection for Excel Snowflake users

· Optimized Cloud Analytics-4x faster query performance; during high user concurrency, queries are 14x faster

· An intuitive and unified data view through the Universal Semantic Layer

· Force Multiplier-Lower ETL and query costs through autonomous data engineering. AtScale does not require Extract, Transform, Load (ETL) to its platform, eliminating expensive, time consuming and risky processes while speeding query response times

· Force Multiplier-Improved performance and agility through autonomous data engineering

· Cost Control-Reduction in cloud resource consumption and other associated costs

· Cost Control-3.7x cheaper compute costs because of the accelerated automation of data preparation to reach this stage.

· Governance-Customers using AtScale on Snowflake maintain a consistent and compliant view of data across the enterprise.

· Trusted Data-Make higher quality decisions based on trusted, consistent data, even across multiple users and timeframes. Take advantage of rapidly evolving economic conditions.

So where does AtScale fit in with Snowflake?

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Anurag Singh

A visionary Gen AI, Data Science, Machine Learning, MLOPS and Big Data Leader/ Architect