Self-service kiosks have rapidly become a staple in the retail landscape, symbolizing the growing trend toward automation in customer interactions. In 2023, the global self-checkout market was valued at approximately $4.5 billion, with estimates suggesting it could reach between $5.2 and $6.0 billion by the end of 2024. This surge is driven by increasing consumer demand for convenience, technological advancements, and the pursuit of more seamless shopping experiences.

Financial services organisations are constantly pressured to streamline operations while maintaining stringent security and compliance standards. As back-office processes become more complex, a flexible, scalable, and automated integration platform becomes essential. Linx addresses these challenges by providing an advanced platform that delivers highly customisable solutions tailored to each organisation’s needs.

Software applications constantly evolve, with frequent updates, bug fixes, and new feature additions. However, these changes can introduce new issues or disrupt existing functionalities. Testlio September 26th, 2024 Explore the Differences Between Smoke Testing and Sanity Testing According to the Systems Sciences Institute at IBM, in addition to potential damage to your brand’s reputation, the cost of fixing a bug post-release can be up to 100 times more than during the design phase.

How are AI governance and data governance related? Better still, what’s more important for an organization to focus on, AI-powered data governance or AI data governance? These are important questions, but before we answer these, let’s understand how AI and data governance are related to each other.

The journey from a great idea for a Generative AI use case to deploying it in a production environment often resembles navigating a maze. Every turn presents new challenges—whether it’s technical hurdles, security concerns, or shifting priorities—that can stall progress or even force you to start over.

While data lakes make it easy to store and analyze a wide variety of data types, they can become data swamps without the proper documentation and governance. Until you solve the biggest data lake challenges — tackling exponential big data growth, costs, and management complexity — efficient and reliable data analytics will remain out of reach.

Computational chemistry relies on large volumes of complex data in order to provide insights into new applications, whether it’s for electric vehicles or new battery development. With the emergence of generative AI (GenAI), the rapid, scalable processing of this data has become possible and critical to investigate previously unexplored areas in catalysis and materials science.

In this Digital era, getting your own hands into every operational activity is not the right thing to do. There are IT transformation consulting experts whose experience and skill set can be leveraged to reduce time, effort, and cost for your organization. In that context, today’s organizations are delivering more and more into cloud-based infrastructure.