Snowflake unveils features to simplify data & AI management

Snowflake has announced new advancements to its platform aimed at simplifying data and AI management for enterprises.

The Snowflake Open Catalog has been introduced to allow users to adapt to their organisational needs by integrating new engines and applying consistent governance controls. This development is part of Snowflake's efforts to make data governance and management more straightforward and efficient.

"We give enterprises the power of choice when it comes to their data estates, and our industry-leading platform and governance capabilities serve as the data foundation for organisations to build powerful AI apps and models at scale, all with complete control and flexibility over their data," said James Malone, Head of Data Storage and Engineering at Snowflake.

"Our continued advancements around Apache Iceberg and the new Snowflake Open Catalog, alongside their easy integrations with the Snowflake Horizon Catalog, bring increased simplicity to organisations' complex data architectures so they can accelerate value, while reducing the number of steps required to use and govern their open lakehouse architectures," Malone says.

Snowflake's platform enables the management of structured, unstructured, and semi-structured data with increased interoperability across platforms. This provides customers with greater flexibility in choosing the data architecture that best suits their needs, while taking advantage of Snowflake's compliance, security, privacy, discovery, and collaboration capabilities.

The company is also making strides in helping enterprises derive insights from various data types within the AI Data Cloud. The Document AI, now generally available on AWS and Microsoft Azure, uses Snowflake's language model Arctic-TILT to extract information from text-heavy documents and other content.

Vineet Gorhe, Chief Technology Officer of DemandHelm, highlighted the benefits of the Snowflake Open Catalog, saying, "Snowflake Open Catalog gives our global teams the flexibility to integrate all of our tools in one place, with comprehensive read and write support from various engines, while maintaining the unified governance we depend on to effectively manage our open data lakehouse. Snowflake's commitment to true open source without vendor lock-in gives us the confidence to innovate faster, without having to worry about the complexities of setup, maintenance, and updates for our lakehouse strategy."

As part of ongoing improvements, Snowflake has introduced new features for streaming, ingestion, and change data capture pipelines, along with integrations to facilitate cost reduction, performance enhancement, and the transition of data lakes into more accessible lakehouses with Apache Iceberg.

Additionally, Snowflake has rolled out security enhancements to the Snowflake Horizon Catalog, introducing credential theft prevention measures and new programmatic access tokens for API authentication. These measures aim to improve user security and simplify the developer experience.

Morten Lileng, Global Head of Merkury Engineering at Merkle, expressed the importance of Snowflake's security features: "As a leading customer experience transformation consultancy, Merkle relies on the Snowflake Horizon Catalog's robust governance and advanced security monitoring capabilities to safeguard our customers' most sensitive data, preventing unauthorised access and data exfiltration between internal teams, allowing the right people to have access to the right information at the right time. With Snowflake, we have full visibility into our data usage, all of which is critical for protecting our customers and ultimately maintaining their trust."

The enhancements also include the introduction of the Threat Intelligence Scanner Package, designed to identify risky users and provide mitigation strategies, alongside support from cybersecurity partners through custom scanner packages available on the Snowflake Marketplace.