Data

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.

Our CEO, Stephane Monsallier was interviewed for the podcast Sesame Asie by Raphael Seghier . The interview is in French. With 17 years of experience in China, our CEO reflects on the many changes in all the Chinese society’s layers. From his first visit to Shanghai in 1998, the time he settled down in Shanghai in 2003, to today, he lived through one of the most significant business and societal transformations in recent history.

Companies collect, store, process, and analyze data to make decisions. But the data is lying, the decision may not be the best, despite great care and effort. Why would data lie to you? There are many reasons why the data is lying. That could be the result of one of several mistakes at any stage of the process. That could be conscious or unconscious bias from one of the actors of the processing chain. There could be an agenda behind the data manipulation, or it could be an unfortunate coincidence. As companies are more and more data-driven, there is a tension between automating as much as possible the data management and processing, and the need for a bit of caution. There is a strong incentive to trust the data, but there should be a healthy suspicion about the data. Data must be treated as questionable until proven trustworthy. The issues with implementing this strategy are:

The current crisis has changed the way we do business forever but in hindsight, it has also given us the time to reflect on our habits and lean more towards efficient business practices, towards a data-driven corporate culture.