Data

The migration or merging of databases is a critical moment in the digital transformation of businesses. Without careful attention to data quality, these projects can quickly turn into operational and financial nightmares. This practical guide introduces you to the challenges, mistakes to avoid and best practices to make your migrations a lasting success.

In the modern retail world, the quality of product sheets directly determines business performance. However, their management remains mostly manual, mobilizing up to 30% of the time of product teams. Artificial intelligence is now transforming this constraint into a competitive advantage, while freeing your teams from repetitive tasks to focus on strategy and innovation.

In an economic environment where responsiveness makes the difference, SMEs and ETIs that effectively structure their data gain a decisive competitive advantage. However, the majority of French companies continue to manage their information assets in a dispersed and obsolete manner. This article explains how to transform this data chaos into a real driver of growth, with concrete steps and measurable benefits for your organization.

Data is now considered the new black gold for businesses, but for many organizations, it remains trapped in crippling digital disorder. This data chaos generates invisible but substantial costs: time wasted searching for information, risky decisions based on erroneous data, and compromised agility. Discover how to identify this problem and, most importantly, how to transform this disorder into a true growth lever through a structured approach to your information assets.RéessayerClaude peut faire des erreurs. Assurez-vous de vérifier ses réponses.

It is now possible to use your data effectively without recruiting a data analyst. Thanks to AI and accessible tools, managers, CFOs or business managers can obtain automatic analyses, ask questions in natural language, and manage their business without technical skills.

Many businesses make strategic decisions based on dashboards that are visually flawless but fed by incorrect or incomplete data. This article explores the risks associated with poor data quality, the invisible errors in visualization tools, and best practices for making reliable analyses and making truly informed decisions.