Snowflake Summit 2024: Highlights and Must-Know Updates
The Snowflake Summit in San Francisco took place last week with many exciting announcements aimed at breaking down silos, developing and distributing modern apps, and enabling teams to build AI applications with their data assets
In case you missed it, this is what you need to know:
- Expanded partnership between Snowflake and Nvidia: extensive collaboration on enabling AI innovation.
- Enterprise AI: Snowflake reinforced its commitment to allowing companies to store and process any type of data and to facilitate AI and ML application development within the Snowflake boundaries without the need to move the data out.
- Snowflake Arctic: The LLM model developed by Snowflake focused on solving Enterprise use cases with the highest efficiency
- Document AI, targeted at helping enterprises make more use of unstructured data, will be Generally Available soon. Enhanced pipelines will accompany this (Public Preview), allowing file processing during Data Ingestion (COPY command).
- Dynamic Tables are now Generally Available. They were announced some time ago as a way to simplify the real-time processing of data coming from streaming pipelines.
- Iceberg Tables(generally available): gives users of the Apache Iceberg open table format full storage interoperability.
- Polaris Catalog (soon in public preview) is a vendor-neutral cross-engine catalog for Iceberg that will be released to open-source this summer.
- Expansion of partnership with Microsoft: Microsoft now added support for Iceberg, and Data in One Lake will be accessible from Snowflake.
- Snowflake Horizon announcement focused on Data Governance.
- Universal Search (now Generally Available). It works across all of the data that a customer has in Snowflake, including internal tables, external Iceberg tables, data from third-party providers, and data from the Internal Marketplace.
- Internal Marketplace (private preview): It will allow various departments of a company to curate and publish data products, including datasets, machine learning models, applications, and other functions.
- AI automatic Object descriptions (Tables, fields, etc) leveraging Cortex AI
- Data Classification Interface with Custom and Auto Classification based on tag propagation.
- New Object Insights Interface with Governance, lineage details, and Data quality.
- New Trust Center (Generally available soon )
- New Cost Management Interface
- Snowpark Container Services is now Generally Available, and public preview of availability for Native apps
- Announcements target to simplify DevOps:
- Git Integration is now in Public Preview
- Snowflake Notebooks (public preview): enables customers to write SQL and Python code, and supports functions such as scheduling and integration with Git. It will also integrate with the new Snowflake Copilot.
- Snowflake Copilot is now Generally Available: a text-to-SQL assistant that combines Mistral Large with Snowflake’s proprietary SQL generation model to accelerate productivity for every SQL user.
- Machine Learning announcements aimed to enable companies to run their entire ML operations within Snowflake without the need to copy data out.
- Snowpark Pandas API (public preview): enables Python developers to work with pandas syntax for advanced AI and pipeline development within the Snowflake environment.
- Snowflake Model Registry (generally available): a unified repository for an enterprise’s machine learning models. It’s designed to enable users to centralize the publishing and discovery of models, streamlining collaboration between data scientists and machine learning engineers. It also allows customers to govern the access and use of AI and ML models.
- Snowflake Feature Store (public preview): allows customers to better manage the individual features that go into an ML model. This capability is targeted at data scientists and ML engineers to help create, store, manage, and serve consistent ML features for model training and inference.
- ML Lineage (private preview): allows enterprise teams to trace the usage of features, datasets, and models across their complete lifecycles.
- Enhancement to Cortex AI. This service makes it easier for organizations to discover, analyze, and build artificial intelligence applications in the Snowflake Data Cloud. It enables easy access to the most broadly used models and Snowflake Artic.
- Cortex Fine-Tuning in Public Preview. This will enable companies to optimize a model to better serve the purpose of their organization.
- Studio: No code interface for Machine Learning and AI. Snowflake has simplified the process so “anyone can build a chatbot”
- Cortex Analyst (soon in public preview): allows customers to securely build applications for their users so they can ask business questions about their analytical data on Snowflake and get accurate answers.
- Cortex Search (soon in public review): Service that will help you index documents and other text-based datasets and easily create a chat experience.
- Cortex Guard (soon to be generally available): filters and flags harmful content across enterprise data and assets, such as violence and hate, self-harm, or criminal activities.
- And finally, the most celebrated announcement…. The new DARK MODE is now Generally available!
We are looking forward to playing with all these very soon! Feel free to reach out if you have any questions about how these announcements may impact your organization.
The Dynamic Data Team