Systems | Development | Analytics | API | Testing

What's New: Supercharge Users With The Snowflake Horizon Catalog

To accelerate development, organizations need to supercharge more users to immediately discover and collaborate on relevant data, apps, and models. At the same time, organizations must ensure the platform they work on is secure and that the right people have the right access. Protecting sensitive and/or Personally Identifiable Information (PII) is critical. The Snowflake Horizon Catalog provides built-in governance and discovery for the AI Data Cloud to make all of this easy.

How to migrate from Kafka to Confluent Cloud with limited downtime

In this short video, a Confluent Solutions Engineering will run through the high-level steps on how to get started with your migration. And even better, once you’re done watching, you can download our comprehensive migration kit for a step by step guide of everything I’ve talked about and more.

EP 1: Exploring the Dark Ages of Data with R "Ray" Wang

Companies have access to more data than ever before – according to IDC, worldwide data will grow 61% by 2025. However, when it comes to adopting AI, there is a difference between companies who merely have internal data and those who have precise, accurate data. The first step to delivering trusted AI is having the right type of data. R "Ray" Wang, principal analyst and founder of Constellation Research, joins The AI Forecast to discuss the value of precision data as we enter what he calls “the dark ages of data”.

Introducing Lenses 6.0 Panoptes

Organizations today face complex data challenges as they scale, with more distributed data architectures and a growing number of teams building streaming applications. They will need to implement Data Mesh principles for sharing data across business domains, ensure data sovereignty across different jurisdictions and clouds, and maintain real-time operations.

9 Best Practices for Transitioning From On-Premises to Cloud with Snowflake

On a day-to-day basis, Snowflake teams identify opportunities and help customers implement recommended best practices that ease the migration process from on-premises to the cloud. They also monitor potential challenges and advise on proven patterns to help ensure a successful data migration. This article highlights nine key areas to watch out for and plan around in order to accelerate a smooth transition to the cloud.

Rightsizing Your Data Infrastructure: Optimizing Databricks Cluster and Workspace Configurations

Join us for another enlightening session in our Weekly Walkthrough series, "FinOps Metrics That Matter," where we focus on the critical aspect of rightsizing your Databricks infrastructure for optimal performance and cost-efficiency. Achieving the right balance between performance and cost is paramount. However, a striking 80% of data management experts grapple with precise cost forecasting and management (Forrester). The primary culprits? Insufficient granular visibility, data silos, and a lack of AI-driven predictive tools.

CDC and Data Streaming: Capture Database Changes in Real Time with Debezium PostgreSQL Connector

In today's data-driven world, staying ahead means acting on the most up-to-date information. That's where change data capture (CDC) comes in. CDC is a design pattern that tracks your database tables, capturing every row-level insert, update, and delete as it happens. This real-time monitoring allows downstream systems to react to changes instantly, without batch-based updates and resource-intensive full scans.