In the digital age, data is the lifeblood of organizations, driving strategies, innovation, and decisions. However, harnessing its power requires more than just collecting the data. It demands meticulous management of data quality, governance, and lineage. These pillars form the backbone of informed decision-making, enabling organizations to transform raw data into actionable insights. According to Gartner, poor data quality costs organizations an average of $12.9 million every year.

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.

Black box testing is a testing method where testers evaluate the quality of a system without knowledge of its internal structures. The system is a “black box”: they know what it does, but not how it achieves those results. In this article, we’ll learn more about black box testing in-depth, the common techniques used, and black box testing best practices.

Making informed decisions on technology adoptions and ensuring the sustained growth and relevance of the organization in the market has never been more exciting than in the current times we live in. The Gartner hype cycle is a valuable tool in this pursuit with all its insights into the timing, adoption, and potential benefits of various technologies.

Due to their ability to enable parallelism and asynchronous execution, threads have an essential role in efficiently utilizing multi-core processors. Without them, handling concurrent tasks in modern applications like real-time inference in IoT or Asynchronous I/O in AI/ML would neither be feasible nor imaginable. The arrival of virtual threads has further grown such possibilities by eliminating the sole dependency on operating system threads.

Gartner predicts that generative AI will be a workforce partner for 90% of companies globally by 2025. However, Alexander Bant, Gartner Finance’s chief of research, expressed a contrasting view at the Gartner CFO & Finance Executive Conference in Sydney in February 2024. He noted, “The large majority of CFOs continue to be displeased with the performance of digital investments across their organization.”

The advent of digital technologies requires industries, including shipping services, to meet the demands of global e-commerce. Accurate tracking, efficient inventory management, and seamless deliveries are now essential components that define successful shipping providers. Shipping providers turn to advanced tools to navigate the complexities of contemporary logistics. These solutions help automate workflows, minimize delays, and optimize customer service.

Cyber attacks are not going away. In fact, the increased frequency in the past couple of years is startling. There were 2,365 breaches in the U.S. in 2023 with 343.3M victims. This represented a 72% increase since 2021, which held the previous all-time record. And the numbers are only expected to grow. Organizations are rightly concerned about their own preparedness and ability to stay operational in the face of these threats.