Data orientation is an inevitable movement and as as each day goes by, it becomes vital for the daily actions of people and companies. This indicates that a data driven mindset will be the competitive differential in a world where Big Data and data intelligence are increasingly in use.
“Data Science is a cross-sectional, multidisciplinary science by nature, which means that it reaches all players in the chain and the most diverse areas”, explains Luiz Paulo Fávero, author of the worldwide adopted book Data Science for Business and Decision Making.
As a concept that is here to stay, the data driven mindset is inherently associated with technology and the decision making process.
Data oriented culture
Data science involves aspects related to data analysis itself and the tools for the capture and recognition of standards, such as Analytics and machine learning. In this we can also include softwares, the internet of things (IoT) and network connected devices, which generate and integrate information.
Whether for organizational or personal purposes, data science gives an insight into the data driven mindset. This concept, according to Fávero, causes the understanding that data can, in a correct way, be treated for the allocation of resources, pointing to trends.
“In fact, we need to focus on data in order to be increasingly focused on trends, as we improve the decision making process from the data behavior. ‘Data driven’ comes precisely to improve the methods of companies that had this mentality”, explains Fávero.
What do you need to have it?
If you ask yourself about what it takes to have a data driven mindset, check the following points:
Objective: whether short or long term, a defined objective helps to select the information that will really be used in Big Data.
Value per area: the objectives set are guided by the areas that add more valued and impact directly on decision making within the company.
Data: data storage is as important as its generation, so they should be treated adequately for future analysis.
Analysis: there are several ways to analyze data, so the importance of correlating and comparing variables, in addition to a series of evaluations during a period. Analysis will also be important to define the presentation of a data set and the value they will have for decision making.
Action: with a decision taken, it is necessary to ensure that it is fulfilled. A data driven mindset is limited to acting in this way, concluding goals from data orientation.
Specialization is important
In an analogy, Fávero compares the formation of a data scientist to a quilt. A professional in this area can be trained in human, exact, biological and social sciences, for example, but add fast courses to your knowledge that bring the aptitude to programming.
So, why is it important to do a specialization?
The answer, according to the author, requires the review of the three pillars of data science, starting with its foundations. “Whether with statistical, economic, algebraic or underlying calculations, every algorithm needs to be taken seriously in a course, because without this it is very easy to add to the software a code of wrong programming”, he says.
On the other hand, he continues, with the fundamentals, codes are done with ease. A person with this domain can learn more quickly new programming languages, with them being the second pillar.
Finally, a specialization finalizes this tripod, because it adds a differential that few fast courses have: analytical and management thinking. Knowing how to obtain data is different than knowing what to do with them, and a more complete course allows the construction of this vision.
Does your daily life allow you to develop a data driven mindset ? We want to hear you, share your experiences on the subject in the comments.
