Data is critical to success. For for this reason, organizations have understood how important it is to create value from these, becoming Data Driven.
But what does data driven mean? What does it mean to implement a “data-based culture” in the company?
I made a podcast on this theme, in which I draw the concepts of Data Driven and Data Inspired.
You can listen to it below:
See Podcast transaltion
I’m Marco Barbiero, Axiante’s Senior Functional Business Analyst and in this podcast I’ll talk about the concept of “data driven”.
We often hear about the trends of 2021 in computer science, such as Augmented Analysis, Dataops, data literacy… precisely tendencies, yes. But only if in the right hands.
Let’s start by saying what can be obvious: organizations want to create value from their data, to be data driven.
But what is the meaning of data driven? What does it mean to implement a “data-based culture” in the company?
Let’s get started!
We start searching on Google, analyzing the trends and weekly research worldwide on the terms “big data”, “data driven”, “AI” and “machine learning”.
We can see a high interest in artificial intelligence. What does it show? In my opinion, it highlights the lack of awareness of the data driven concept, and the preference for other more “famous” words, heard more often and perhaps more popular at the moment. But words like big data, data scientist and AI all have one thing in common: they hide an important concept, the “data driven”.
Being data driven does not mean having the latest big data innovations or a fleet of data scientists. Although all useful, before arriving at destination you have to undertake a journey.
The data are examined and organized with only one purpose: to improve business strategies. To understand whether a company is really Data-Driven and not Data-Inspired, we need to evaluate its decision-making processes. Decisions must not only be based on data, numbers and graphs must not only be marginally involved, but must have a real influence on the decision to be taken.
We are often led to confuse quantity with quality.
In order to be used effectively in a decision-making process, it is important that the data is clean and clear.
Many sectors are changing their way of operating, based on data: in this way they have the real opportunity to significantly improve the efficiency of organizations. However, there are many challenges, both human and technical, that need to be addressed in a way that fully exploits these potentials.
The way we work, we think of the tendency to work on your customer and not on the shared database, but also the presence of disorganized data, without data lineage, which make them unavailable, or available only after a very expensive and probably unplanned cleaning.
In short, remember: every challenge you will encounter during your data project, will reveal the level of maturity of your organization in the data driven field and will allow you to evaluate the actions to take to achieve your goals. But going in order, following all the stages, until you reach your destination.
For this episode of the Axiante’s podcast is all, thank you for listening and see you next time!
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