Challenges of data valorization

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The second step is what is called the Data Lake . The latter is a repository whose role is to store all types of data for an indefinite period of time. The Data Lake step therefore consists of the company making the data to be valued accessible and usable at any time.

The third step groups together three actions which are research, manipulation and analysis . These actions are done using tools. This step consists of responding to the predefined problem by shedding light on the information and trends that respond to it.

The last step is representation and reporting . During this step, you will be required to take direct action to report the conclusions drawn after data processing to the right people. This reporting can be done either in the form of representation or automatically.

In a more condensed way, data valorization is based on three panama whatsapp number database pillars: management, sharing and accessibility. Management refers to the development of your company's capacity to manage the data to be valorized. Sharing is the implementation of policies on the data life cycle. Finally, accessibility is the adaptation between the availability of information and its presentation to meet the various exchange needs.

Data valorization presents major challenges on strategic and technical levels . Among these, we can cite the humanization of data and the quality of information. Another challenge lies in the optimization of data processing. There is also, without context, the connection of all professions. Finally, your company also benefits from the assurance of security of the information collected.

Why is it important to focus on data mining and collection?
When it comes to data itself, its collection and processing are inseparable. It is therefore necessary for your company to know how much importance to give to each.