Data

As the adoption of Generative AI (GenAI) technology rises in large companies, IT managers are facing a unique set of challenges and concerns. Although GenAI holds immense potential to streamline operations and drive innovation, it also introduces new complexities in terms of management, security, and control.

Artificial Intelligence (AI) has become a buzzword in many industries, and it is fast becoming a reality for many knowledge workers. Organizations must understand how to best integrate AI to empower their employees. The knowledge worker is a vital asset in any company, and AI can help empower these workers by providing them with the information they need to make better decisions, faster, and focus their energy on higher value creation tasks.

We developed a methodology to help our clients design critical numbers for all their projects. It has become an essential part of our toolbox to ensure that a project: delivers value, serves a business objective, is judged on objective success criteria. This tool is both a business and project management tool, as it aligns both views and objectives.

Good data is the basis of good decisions in companies. Good data is also necessary to enjoy the benefits of business intelligence and machine learning. It is then surprising how much corporates spend on shiny technology versus producing good data. High-quality data can be an asset to companies that know how to use them.

In a world where we have too much data, building an effective dashboard involves many design decisions. This article gives a step-by-step guide to creating effective dashboards. 1. Start with the End in Mind To make sure the dashboard will be effective, you need to place your target first. But what is the goal? How can you define it?

Process Mining merges process modeling and data mining to explain how systems, processes, users, context, and data operate together. It is a specialized branch of data science that delivers more and more insights to corporates.