The Latest

19 Nov 2020: During its annual summit, Snowflake announces a series of new capabilities: a development environment called Snowpark, support for unstructured media, row-level security for improved data governance and a data market.

Why it’s Important

Of Snowflake’s recent announcements, Snowpark clearly reveals the vendor’s strategy to leverage its Cloud analytics platform to enable the development of data-intensive applications. Snowpark allows developers to write applications in their preferred languages to access information in the Snowflake data platform.

This represents an inversion of how business intelligence / analytics teams have traditionally viewed the role of a data warehouse. The rise of data warehouses was driven by limitations in computing performance: heavy analytical workloads were shifted to a dedicated platform so that application performance would not be impacted by limits of database, storage and compute power. With Cloud-native data platform architectures that remove these limitations, it is now possible to leverage the data warehouse (or at least, the analogue of what the data warehouse has become) to service applications.

Who’s Impacted

Development teams
Business intelligence / analytics architects

What’s Next?

Snowflake's strategy is evidence of a seismic shift in data analytics architecture. Along with Domo, AWS, Microsoft Azure, Google and other Cloud-based data platforms that take advantage of highly scalable, federated architectures, Snowflake is empowering a flip in how data can be leveraged. To take advantage of this flip, organisations should rethink the structure and roles within BI / analytics teams. IBRS has noted that many organisations continue to invest heavily in building their BI / analytics architecture with individual best-of-breed solutions (storage, databases, warehouse, analytics tools, etc), while placing less focus on the data scientists and business domain experts. With access to elastic Cloud platforms, organisations can reverse this focus - putting the business specialists and data scientists in the lead. 

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