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Even the most distinguished scientists sometimes have problems, there is a very common one when it comes to share their findings with the rest of the world. The lack of telling what did happen, what is happening, and what will happen is the ultimate curse of scientific advance. In fact, the inability of telling what the data and/or model suggest is one of a peculiar merits of data science. This is where storytelling comes in to the scene. Although storytelling is used as a nice analogue here, the actual meaning in context is more than telling cases of situations. in order to comprehend the idea of storytelling in data science one must understand a few key points, which have been discussed in our entire website and this particular post.

The Past, the Present, and the Future

The art of listing the outputs now became vital as data became complex; however, data science is not just inputs and outputs. The necessary part is, although it changes across conditions, to understand what data tells. That is, whether you are looking for answers of past, present, or future the data must tell you what you are looking for, not a complex rigidity of frequencies and samples. Thus, as data talk in an open discourse, users benefit more than just looking at it as mere human beings we were evolved to pass our experiences via cases.

Therefore, the past is better learned from collective experience that passes through generations to generations. In the context of data science, the past data is collected for better understanding of patterns and trends. The market surveys, consumer behavior researches and so on are conducted for improved strategies. Nonetheless, the word is easier than the work. To understand the patterns from a complex analysis is not the job of the decision-maker, at least not anymore. To clarify, the latest modelling techniques, tools, and methods should tell about the situation rather than just stating it. Thanks to complexity of current tools, getting informed about the past data have become as easy as we have in present data.

The present data analysis is almost similar to past data analysis in terms of its application, objective, and tools. Although there are some contrasts between them, the ultimate goal of describing situations stays the same. However, the upper hand of present data cases show itself in recent years as tools enhanced enough to form the cases from the concurrent data rather than observing the past and looking answers for future. Merits of present storytelling has now a concrete throne in data science as their help on better understanding of conditions now undiscussable.

Human beings’ cognitive ability backed our evolution as we collect the experience transferred from ancestors before us. The important point here is that, the transferred information is raw and there must be something to add so that raw information becomes knowledge. The prediction becomes the key element here. Cases of future involve more than what we have experienced and more than what we can experience. Therefore, in the discourse of data science, the predictive analysis gives even more than what we can imagine. However, the above-mentioned problem persists here also. The problem, solution, methods everything is complex as prediction mechanism collects complex data and forms complex outcomes.

Nonetheless, the answers for the simplicity of complex prediction about future lies with the predictive storytelling. Everything has its story, even complex models of big data. These cases would always show the correct path when it comes to conduct a comprehensive analysis. All those analyses must be segmented into understandable parts of cases. This is how big data works as one cannot easily understand the whole piece without looking into details. In fact, the detail at user’s scope must be portioned into more categories so that end-user get the whole idea by the virtues of a predictive storyteller.

Consequently, the idea of creating a narrative for complex data cluster so that a story is formed for the sake of better understanding is now vital as conducting a smooth survey or constructing an all-inclusive model that brings all solutions with itself. The predictive story telling is the sole reminder of our evolution that individual cognitive skills of our formation is what makes us what we are today. Data science of predictive statistics shows that the passion for future and the talent of narrative -storytelling- are what we are composed of. As there are no experts of future but only of a past, the predictive storytelling shows the way up to more, always more.

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