A gift, a technique or something obvious? How to simply analyze data

Just start with an observation: "we live in a world increasingly full of data, we use it every day, we keep it, we share it, we transform it, we destroy it, we create it."

Is it therefore utopian to believe that we can understand them simply by analyzing them? The shortcut is to believe that a piece of data is simply information that isn't entirely accurate.

Data, by definition, is raw information, but without context, it cannot be used.


In terms of volume, you must be able to orchestrate the data so that it progresses to a stage of data culture, where it can be analyzed to make decisions.

As a result, it is not a gift and even less obvious.. Reporting, dashboards, algorithms, and intelligence become critical allies in achieving an efficient analysis result.

Consider the professional world, where an organization's incapacity to understand, evaluate, and utilize data hinders it from fully contributing to employee contentment, and hence the business.

With data volumes constantly increasing, are we not on the verge of seeing some people drop out? Improved data literacy provides three major advantages to businesses and employees:

• Making better decisions for organizations: Understanding and analyzing data enables businesses to make faster, more informed, and smarter decisions.
  
• Create a data culture: mastering data is an essential component of establishing a data culture within an organization; it can serve as a knowledge charter.
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• Boost productivity and confidence: Data-savvy employees are more productive, motivated, and self-assured when performing tasks.
  

Data in credit management

For optimal management of the trade receivable which combines a multitude of data, it is clear that software such as My DSO Manager is essential to centralize and implement this culture which contains, among other things:

• Customers data, accounting data (invoices, notes, ...), users details.
  
• Financial information, credit insurance amounts, payment methods.
  
• Payment behavior, cash collection KPI, etc.
  

The scope is wide!