Descriptive analytics is a preliminary stage in the processing of
data that creates a summary of the historical data to provide
useful information and prepare the data for further analysis.
To answer the question "What happened in the business?" the
descriptive analytics is used. Thanks to this, the data and the
information to describe the current business situation of a
so that trends, patterns and exceptions become apparent.
This then takes the form of reports, dashboards, etc.
Descriptive analytics helps organizations understand what happened in the past (the past in this context may be from a minute or a few years ago). Descriptive analytics means the relationship between customers and products, your objective being to gain an understanding of the approach that is to adopt in the future: learn from past behavior in order to influence future results.
Descriptive analytics does exactly what its name implies: "Describe." They are analyzes that describe the
past. The vast majority of the statistics we use fall into this category (for example, in the
basic arithmetic: sums, averages, percent changes). The underlying data is generally a
a count of data to which basic mathematics is applied. For all practical purposes, there is a
infinite number of these statistics.
Descriptive analytics is useful for showing things like total volume in inventory, euros spent
average per customer or the year-to-year change in sales of a product. Common analysis examples
Descriptive are reports that provide historical insights regarding production, finances,
operations, sales, inventory and customers of a company.
A film application, for example, would use descriptive analyzes to find correlations between
different movies that your subscribers liked and thus improve your recommendation engine, using the
sales data and customer history.
Therefore, descriptive analysis is an important source for determining what to do next in a
campaign or event.
In the online environment we find web analytics, where descriptive analytics transmits the current situation of the web at the metric level: how many users have come, how many visits have they made, what pages they have seen, from what sources, how long their session lasted.
Descriptive analytics is a preliminary stage of data processing that creates a summary of the data
historical data to provide useful information and thus prepare the data for further analysis. The
Data mining and its processing organizes the data and makes it possible to identify patterns and relationships in
themselves that would not otherwise be visible. In this way, the consultation, information and data visualization are
can be applied to get a clearer view.
Descriptive analytics therefore provides information about what happened. This would be seen, by
For example, an increase in YouTube followers after uploading a particular video. After
the next step of the process would intervene, the diagnostic analysis, a deeper study of the data
to try to understand the causes of events and behaviors. Next comes the analysis
predictive, which is used to identify future probabilities and trends, which provide
information about what might happen in the future. Finally, prescriptive analytics would be used, which
is applied to try to identify the best outcome of events, taking into account the
parameters, and suggest decision options to maximize the opportunity of a future or mitigate
a possible risk.