Automated data governance is a relatively new concept that is fundamentally altering data governance practices. Traditionally, organizations have relied on manual processes to ensure effective data governance. This approach has given governance a reputation as a restrictive discipline. But, as organizations increasingly adopt automation in their governance processes, this perception is changing.

Using BigQuery DataFrames with CARTO visualization tools can help Python users access cloud-native analytics and generative AI services.

The mid-sized enterprise is the fastest-growing market opportunity for data storage. But not just any storage system will do. These days, mid-sized enterprises must handle the complexities of unremitting data growth and distributed infrastructure, meet sustainability goals, manage the diverse storage needs of mission-critical applications, and respond to user requirements. Oh, and they need uninterrupted access to their data no matter what.

Welcome to the ultimate resource for mastering load testing! Whether you’re a non-technical business owner, a software engineer, a student, a product owner, a member of a web agency, or a DevOps professional, this article will show you how to approach load testing challenges head on. We’ll progress from the fundamentals to more in-depth strategies, all in a relaxed and easy-to-understand manner. Are you ready to ensure that your website runs smoothly even during peak traffic periods?

As the wave of AI sweeps through the technology landscape, many have hopped on board. Interestingly enough, and often overlooked, is that many AI capabilities are served through APIs. Fancy user interfaces integrate with the actual mechanisms where the magic happens: the APIs. So, when generating revenue through AI platforms, the APIs drive the revenue.

API downtime can cost businesses an average of $140,000 to $540,000 per hour. Maintaining reliable and high-performing APIs has become critical for any digital business’s success, with much at stake. This scenario is where API monitoring steps in. An important part of API management, monitoring API metrics allows organizations to detect issues rapidly and optimize their API performance.

Trying to integrate data without knowing your starting point is like taking a road trip without a map—you’re bound to get lost. To navigate the challenges of data integration, IT leaders must first evaluate their current data setup. This means taking stock of all your data sources, understanding their quality, and identifying integration points. It’s like conducting a thorough inspection before renovating a house; you must know what you’re working with.

Its ability to simplify a variety of tasks such as making HTTP requests, handling responses, and managing network activities, has made Alamofire one of the most popular and powerful networking libraries in Swift. Today we’ll be looking at how Alamofire can be integrated with Bugfender to cut through the complexities of URLSession to streamline networking operations in our apps.

As government agencies work to improve both customer experience and operational efficiency, two tools have become critical: cloud services and data. Confluent and Amazon Web Services (AWS) have collaborated to make the move to and management of cloud easier while also enabling data streaming for real-time insights and action. We’ll be at the AWS Public Sector Summit in Washington, DC on June 26-27 to talk about and demo how our solutions work together.

Data lineage is an important concept in data governance. It outlines the path data takes from its source to its destination. Understanding data lineage helps increase transparency and decision-making for organizations reliant on data. This complete guide examines data lineage and its significance for teams. It also covers the difference between data lineage and other important data governance terms and common data lineage techniques.