Five main stages of the Data process


there are five essential phases to be evaluated and followed by entrepreneurs so that their companies' data can be converted into results.

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According to the book launched by the pair of experts , there are five essential phases to be evaluated and followed by entrepreneurs so that their companies' data can be converted into results. Are they:

1. Discovery
In this initial stage, the recommendation is: focus on the nature of the problems or opportunities that are ahead of the company, trying to build a clear picture of the scenario in which the company is, in order to determine what actions to take next and predict which will be the impacts generated by these actions.

According to Wells, this discovery phase is the one that will create the basis for understanding the business objectives, allowing hypothetical problems to be created that will be solved even before they become real. "It is the launching pad for the rest of the project," he says.

2. Decision analysis
The second phase involves a more analytical approach to company decision making. For Chiang, it is here to get to the root of the problems, looking for biases that the team may be bringing to the problem in question. This is because it is possible that team members have already made decisions or thought about solutions in advance, and are only looking for data to confirm them.

For Chiang, this second step serves to "be more objective about which alternatives are worth considering, and be more aware of the predispositions that the team may be bringing to the project".

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3. Monetization strategies
After the initial steps are over, it is time to determine whether the proposed solutions are of any value. According to the assessments made by Chiang in his book, in the era of Big Data, "what is constantly missing is the value", and in this part of the process, the entrepreneur must test his analyzes to see if they generate any advantage.

4. Agile analysis
According to Wells, nimbly analyzing your company's data will allow you to make decisions and develop solutions more quickly. And this agility means involving all directors of the company in the process, freeing access to data without having to go through bureaucratic systems that waste time and resources for nothing.

5. Activation
The last phase listed by the pair of experts in their book is the activation stage, which involves "hardening" the process. According to Wells, this step "ensures that the data is valid, that the calculations are correct and that users are engaged in the process". This phase is listed as the last one and comes right after the stage of preparing agile analyzes, because, once the team members are participating in the data collection and analysis, they will trust that information and this will make them commit more with the project.

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