When I believe, for example, that our clients are simply looking for a BI solution, when I look more deeply into the reality of these companies and some of their initiatives, I can understand how much many of them have already understood that the success of their projects – and, consequently, the market growth of their businesses – will depend, to a large extent, on the assertive prediction of facts, and on discoveries capable of providing a basis for efficient decision-making.
Another interesting point that I have noticed is the fact that some companies want to see even further: not content with uncovering scenarios about their own businesses, these organizations are also concerned with knowing what their customers' decisions will be.
In other words, for them it is not enough to simply whatsapp saudi arabia historical data and create an information base like someone looking in the “rearview mirror”. In addition, these companies seek glimpses of the future, through the study of behavioral data and countless previously unforeseen variables.
All this desire to “see ahead” enables the emergence of business cultures based on investments in innovation, research and development, the creation of partnerships, knowledge exchanges and even the movement of huge companies opening agendas with recently opened startups that offer some valuable insight or solution. All this, in favor of thinking and seeing further ahead.
Taking this scenario into account, I can say that the raw material for any future discovery is data, whether it is data already “recorded” or data yet to be recorded.
Thanks to this premise, a data scientist today has great value, after all, he is the one who can use mathematics to make discoveries, crossing countless variables to obtain better sales, greater efficiency, less waste, better allocation of resources, greater operational speed, in short, all the managerial pursuits of any company that aims to grow. And all this, regardless of the segment.
The great truth is that mathematics combined with data is capable of generating powerful algorithms when applied by a skilled data scientist, a professional who will be one of the most sought after in the future and who, today, already plays a strategic role in more visionary organizations.
To conclude, it is worth noting that the companies mentioned throughout this article are also concerned with how to create access to data recording in their customer contact channels, how to store information in the best way, and how it is possible to further optimize data mining, cross-referencing and extraction, also using mathematics to predict different realities.
We are, therefore, truly on the path to the future. And with our foot on the accelerator.