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Transitioning to a set of microservices can seem daunting. This video breaks down how the Designing Event-Driven Microservices course can help you navigate that journey.
80% of data management professionals surveyed cited difficulty accurately forecasting data-related cloud costs (Forrester). Why? They lack granular visibility to allocate costs, the information they need is in silos, and they don’t have AI or automation to forecast spending. With this in mind, Unravel introduces the new FinOps AI Agent. Learn how this new AI agent enables teams to go beyond observing overall spend to taking immediate action with purpose-built AI and automation.
Discover Astera Data Governance, the comprehensive solution designed to simplify and secure your data management processes. With a single platform, manage and govern your data assets efficiently, ensuring data quality, security, and accessibility. Watch our demo to see how Astera Data Governance can centralize your data assets, streamline data discoverability, and empower your organization with robust data access management.
The Snowflake AI Data Cloud is an end-to-end platform that supports all types of data, compute, use cases and personas across an entire organization. By delivering a single, unified platform for all users, it is no surprise that organizations continue to expand their use cases on Snowflake. And therefore, it is extremely important for us to reaffirm our commitment to price-performant queries for our customers on a consistent basis.
API testing is the process of verifying that APIs are working and performing as expected. Developers and QA engineers test APIs by sending requests to various API endpoints and validating the responses against expected outcomes. The goal is to determine if the APIs meet the set standards for functionality, performance, scalability, and security. This process includes testing the “happy path” scenarios and negative cases to ensure proper security checks are in place.
Confluent Cloud, a leading cloud-native platform for building data streaming applications, and BigQuery, Google's serverless data warehouse, are revolutionizing how businesses handle data. Together, they offer a powerful solution for real-time data ingestion, processing, and analysis—now enhanced by BigQuery’s new continuous query. Many organizations grapple with challenges in moving data from their data warehouses to real-time processing platforms.
The purpose of this post is to describe the integration and benefits of combining Google’s new BigQuery Continuous Queries capability with Keboola’s orchestration capabilities. Combining these capabilities enables organizations to react more quickly to external and internal events.
Qlik offers a comprehensive suite of solutions designed to enhance data integration, analytics, and data quality, seamlessly integrating with Google BigQuery. Qlik's data integration tools enable efficient and secure data ingestion from various sources into BigQuery, ensuring real-time data availability for analytics. With Qlik's advanced analytics capabilities, users can perform sophisticated data analysis and gain actionable insights from their BigQuery data.