Systems | Development | Analytics | API | Testing

Now you can create and manage your control plane on-prem or on-cloud, regardless of where your data and compute are. We recently announced extensive new orchestration,scheduling, and compute management capabilities for optimizing control of enterprise AI & ML. Machine learning and DevOps practitioners can now fully utilize GPUs for maximal usage with minimal costs.

Choosing between REST API vs RESTful API is pivotal for efficient and scalable business solutions in data integration. Application Programming Interfaces (APIs) are critical in data integration, enabling diverse systems to communicate and data exchange seamlessly. In this landscape, REST (Representational State Transfer) APIs have emerged as a standard, known for their simplicity and effectiveness in handling network requests.

Learn how to integrate Striim with BigQuery ML for real-time data processing in machine learning.

Effective data visualization is an important aspect of creating impactful and actionable reflections of key metrics in today’s business environment. Our five key takeaways are: This piece explores data visualization best practices and core principles, from integration to analysis, and the skills you need to create stunning dashboards, breathe life into your KPIs, and discover the secret to designing data visuals that shine.

Many developers and enterprises looking to use machine learning (ML) to generate insights from data get bogged down by operational complexity. We have been making it easier and faster to build and manage ML models with Snowpark ML, the Python library and underlying infrastructure for end-to-end ML workflows in Snowflake.

ThoughtSpot is taking Snowpark use cases to the next level with generative AI, connecting the dots between ML-powered insights and business action. If you’re new to Snowpark, this is Snowflake’s set of libraries and runtimes that securely deploy and process non-SQL code including Python, Java, and Scala.