Snowflake's data sharing: Unlocking the power of collaborative analytics

Snowflake's data-sharing feature is a cutting-edge capability that enables organisations to securely share live, governed data with other Snowflake accounts. Unlike traditional data-sharing methods that involve complex ETL processes and data transfers, Snowflake's approach allows seamless sharing of data in its native format. This unique feature simplifies collaboration between different teams, departments, or even external partners, fostering a more agile and data-driven environment.

The data-sharing feature is designed to be secure, performant, and cost-effective. It leverages Snowflake's architecture to provide a virtual data share without physically moving the data, ensuring that organisations can maintain control over their data while still enabling collaborative analytics.

How it works

Snowflake provides two methods for sharing data, namely via Secure Data Sharing and reader accounts. The main difference between them is where the processing of data happens. For Secure Data Sharing, the processing happens in the consumer’s account, whereas with the reader account, the processing happens in the data provider’s account. This means that Secure Data Share is ideal for organisations that have implemented Snowflake, while a reader account provides a viable option for those that haven’t.

Example use cases:

Hedge fund data optimisation

A case study by Northern Trust highlights the effectiveness of Snowflake's data sharing in the hedge fund industry. By leveraging Snowflake's capabilities, hedge funds can streamline their data workflows, enabling faster decision-making and improved operational efficiency. The ability to securely share data with asset managers, administrators, and other stakeholders in real time enhances collaboration and transparency.

Streamlining Asset Servicing

In the asset servicing sector, where data accuracy and timeliness are paramount, Snowflake's data-sharing feature plays a pivotal role. By creating virtual data shares, organisations can provide clients and partners with direct access to specific datasets, ensuring that everyone operates with synchronised information. This not only accelerates asset servicing processes but also enhances client satisfaction.

Streamlining asset servicing

In the asset servicing sector, where data accuracy and timeliness are paramount, Snowflake's data-sharing feature plays a pivotal role. By creating virtual data shares, organisations can provide clients and partners with direct access to specific datasets, ensuring that everyone operates with synchronised information. This not only accelerates asset servicing processes but also enhances client satisfaction.

Other alternative data-sharing mechanisms

While Snowflake's data-sharing is a powerful solution, it's essential to consider alternative data-sharing mechanisms depending on specific use cases and requirements. Traditional methods like FTP (File Transfer Protocol), API-based sharing, and custom ETL processes have been prevalent.

These methods can involve more manual effort and engineering lift, however, for specific use cases may be a better option. QuantSpark’s Analytics Engineering consulting team can provide your Technology teams with expert advice to design the optimum architecture when integrating with third party platforms.

Summary

Snowflake's data-sharing feature is a revolutionary solution for collaborative analytics. Offering real-time collaboration, cost reduction, robust data governance, and effortless scalability, it is a top choice for modern organisations. While alternatives exist, Snowflake's approach has redefined data sharing, unlocking new possibilities for maximising data potential.

Embracing technologies like Snowflake's data sharing is crucial for staying ahead in the competitive landscape of data science and analytics, where data is a cornerstone of business success.