Snowpark Unleashed: The Data Leader’s Guide to Revolutionizing Collaboration & Efficiency in the Snowflake Data Cloud
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“By leveraging the power of Snowpark as well as other tools in the modern data stack, a healthcare startup was able to leverage machine learning at scale to deliver cancer prevention data to employers.”
Legacy Technology vs. The Snowflake Data Cloud
One of the biggest challenges facing organizations today is the shrinking availability of tech talent. As technology becomes more complex, the demand for skilled workers is outstripping the supply. As a result, many organizations struggle to find the specialized skills they need to maintain and develop their technology infrastructure. Those hit hardest by this shrinking supply and heightened demand environment are those organizations that rely on legacy solutions.
What is Snowpark?
If the availability of tech talent is the problem, Snowpark is the solution. For leaders struggling to build a team that’s versed across an entire host of coding languages and unique technologies, Snowpark makes it easy for teams to apply their skills to diverse business needs by providing a new developer framework for Snowflake, composed of both a client-side library and a server-side sandbox. Snowflake brings deeply integrated DataFrame-style programming to the languages that developers like to use, such as Java, Python, and Scala.
Delivering Dramatic Improvements
When it comes to performance, Snowpark is capable of delivering high quality outputs with increased efficiency. In fact, Hakkoda clients that migrated to Snowpark off of alternative platforms saw a 96% performance improvement. So how is Snowpark able to deliver these dramatic improvements while also saving you money? Through centralization, speed enhancements, and simple solutions paired with sophisticated tooling.
Innovating Swiftly
Snowpark helps drive results and innovation with machine learning for data science and AI-driven applications. Snowparks performance speed, a critical factor in supporting robust ML models, married with its tight integrations to Spark, Python, Qubole, etc., makes it an indispensable machine learning technology. Moreover, Snowflake’s partnership with Anaconda gives users curated data libraries where datasets are FAIR (Findable, Accessible, Interoperable, and Reusable), adding value by enhancing data sets for current use and future reuse.
Delivering Dramatic Improvements
With Snowpark, you can create data clean room environments where custom code can be executed to perform advanced analytics and transformations on data while ensuring data security, privacy, and isolation. Snowpark also makes it easy to implement data clean room workflows. No matter what language or library your team prefers to work with, they’ll be able to implement directly within the cloud.