Advancements to data programmability, global data governance, and platform optimizations empower more users than ever before with extensibility and choice
Snowflake, the Data Cloud company, unveiled its latest product innovations that redefine what’s possible in the Data Cloud. At its annual Snowflake Summit, the company announced innovations in data programmability, global data governance, and platform optimizations to empower organizations to bring more data together in the Data Cloud, achieving deeper value from data and powerful business insights.
“Snowflake enables us with a flexible, scalable toolset and processing power to bring together granular data and build upon the data we already have”
Recommended ITech News: Sentry Bolsters Enterprise Offering With Custom Dashboards And Automated Ticket Creation
Data programmability innovations:
- Snowpark. With initial support for Java and Scala, Snowflake’s developer experience, Snowpark, allows data engineers, data scientists, and developers to build using their preferred language and familiar programming concepts, and then execute these workloads directly within Snowflake. Currently in private preview, with public preview coming soon.
- Java UDFs. With Java user-defined-functions (UDFs), customers can bring their custom code and business logic to Snowflake for better performance and expanded use case capabilities, all while reducing management complexity. Currently in private preview, with public preview coming soon.
- Unstructured data. Snowflake is bringing accelerated time-to-value to unstructured data, enabling customers to store, govern, process, and share file data alongside their structured and semi-structured data and unlock new revenue opportunities. In private preview, with public preview coming soon.
- SQL API. The Snowflake SQL API enables custom and off-the-shelf applications to call Snowflake directly through a REST API, without the need for client-side drivers, thus reducing the complexity and administration overhead requirements. In public preview.
Snowflake customers like Sainsbury’s are already leveraging Snowflake’s data programmability capabilities. “Snowflake enables us with a flexible, scalable toolset and processing power to bring together granular data and build upon the data we already have,” Sainsbury’s Senior Data Viz and Automation Manager, Steven Henson-Tyers said. “With Snowflake’s Data Cloud, our data scientists have more access to the near real-time information needed to build and iterate on models more quickly and effectively.”
In addition to Snowflake’s core innovations in this area, it continues to expand and deepen its partner ecosystem. The new Snowpark Accelerated Program provides partners who integrate with Snowpark with access to technical experts and additional exposure to Snowflake customers. Data science partners like Dataiku and DataRobot also continue to enhance their integrations with Snowflake. In addition, Amazon Web Services (AWS) has launched Snowflake integration with Amazon SageMaker Data Wrangler. Starting today, you can now use Snowflake as a data source in Amazon SageMaker Data Wrangler to easily prepare data in Snowflake for machine learning.
Global governance capabilities:
- Classification. Snowflake’s classification capability automatically detects personally identifiable information (PII) in a given table and leverages the tagging framework to annotate the data, allowing role-based policies to be used to control access to the data. Classification is in private preview.
- Anonymized views. This new capability can be used to protect privacy and identity in a dataset, while still retaining its analytical value. The private preview of anonymized views is expected to be released soon.
Recommended ITech News: AVANT and UJET Announce Strategic Partnership to Deploy Next Generation of Customer Experience
Platform optimizations:
- Improved Storage Economics. Recent changes to Snowflake’s storage representation of data have resulted in better compression, and reduced storage costs. This enhanced storage technology is available transparently, with no user action, no configuration changes, and no application or query changes. This is already rolled out to all Snowflake customers and will apply to newly written data.
- Improved Support for Interactive Experiences. The new set of updates released for high volume and low latency workload requirements can result in up to a 6x improvement on query throughput on a single compute cluster; and up to an 8x improvement in average query duration for those workloads. These enhancements are in private preview.
- Usage Dashboard. The new usage dashboard helps customers better understand usage and costs across the platform, making it easy to manage Snowflake accounts across the entire organization. The usage dashboard is in public preview.
“Snowflake’s unique architecture has not only redefined what’s possible with data in the Data Cloud, but it has given us a strong foundation to continue to build and innovate on,” Snowflake SVP of Product, Christian Kleinerman said. “This foundation powers Snowflake’s leadership across six key workloads with blazing performance, reduced operational complexity, and hardened security, and it also enables us to create a global experience across clouds and regions.”
Recommended ITech News: BlueConic Launches Tool to Assess Organizational Readiness for First-Party Data Future
