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Writer's pictureJamie Harper

Unleashing the Power of Snowflake: Why Direct Querying Is Essential

Updated: Apr 24


You've migrated your data to Snowflake, the powerhouse of cloud-based data warehousing, ready to unlock its full potential for analytics and reporting. Yet, amidst the buzz, you're bombarded with advice to utilise Power BI or Tableau data import. But pause for a moment and ponder: why go through the hassle of migrating to Snowflake if you're just exporting data out? 


In this article, we delve into the intricacies of this question, exploring the rationale behind direct querying in Snowflake and why it's a game-changer for unleashing the true power of your data analytics endeavors.


Snowflake and legacy on-premise databases like SQL Server and MySQL represent two distinct paradigms in data management. While traditional databases operate on a monolithic architecture, tightly coupling storage and compute, Snowflake adopts a cloud-native approach. It separates storage and compute, allowing them to scale independently across multiple nodes in the cloud. This architecture enables Snowflake to efficiently handle massive data volumes, enabling organisations to work with petabytes or even exabytes of data. Additionally, Snowflake's columnar storage and optimised query processing deliver faster query performance and improved analytics capabilities compared to traditional databases across even these massive data volumes.


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BI platforms like Power BI have historically resorted to scheduled periodic data export to overcome performance limitations associated with traditional databases. Exporting data from these databases allows BI platforms to offload data processing to their optimised engines, providing an “acceptable level” of query performance. However, data export introduces complexities such as duplication, synchronisation challenges, and potential security risks. Snowflake's cloud-native architecture eliminates the need for data export.

By leveraging Snowflake's capabilities for direct querying, organisations can streamline their BI workflows and make informed decisions based on up-to-date, accurate data rather than summarised and stale exported data.

Its highly performant infrastructure can handle complex analytical workloads directly, delivering real-time insights without compromising performance, scalability, security, or data integrity. By leveraging Snowflake's capabilities for direct querying, organisations can streamline their BI workflows and make informed decisions based on up-to-date, accurate data rather than summarised and stale exported data.


The big concern with direct query has always been the cost. Snowflake however, provides a range of query optimisation features that are key to ensuring fast processing and lower costs. Let’s take a look at a couple. Snowflake’s query caching stores frequently accessed data in memory, accelerating query processing and incurring zero compute costs when serving queries directly from the cache. Think about a report that is being hit by multiple users, those second and subsequent users are going to have their data served from the cache, at zero cost. 


In addition, advanced techniques like query rewriting allow Snowflake to optimise query execution plans by leveraging precomputed results or materialised views for efficient data retrieval. The quality and design of your Snowflake data model is key to ensuring Snowflake can deliver lightning-fast queries, reducing compute costs and enhancing overall performance. Snowflake's robust query optimisation capabilities empower organisations to achieve optimal efficiency and cost-effectiveness in their data analytics workflows, making direct querying a great option for accessing and analysing data, particularly across larger data volumes.


While Power BI or Tableau data imports may be the way you have always done it, it's essential to reconsider the true purpose of migrating to Snowflake. The historical reliance on scheduled periodic data export to overcome performance limitations with traditional databases is a thing of the past. Snowflake's innovative approach eliminates the need for data export, enabling real-time insights without compromising performance, scalability, security, or data integrity. Through direct querying, organisations can unlock the full potential of their data analytics endeavors, driving innovation and informed decision-making in today's competitive landscape.


For more information head to our Snowflake Services page or get in touch with us via email at info@pivotanalytics.com.au or calling 1300 475 510.



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