Before the use of data analytics, it was common for problems on the production line to exist for years without even being notic. However, with the correct use of this statistical analysis model, problems of this type become almost impossible for managers to miss.
A very useful practical example of the application of descriptive analysis would be that affect the continuity of the production line and that could delay the delivery of the service or product offer by the company.
Diagnostic analysis
Like descriptive analysis
previously mention, diagnostic analysis operates in the contemporary context of the company. The difference is that it is more focus and narrow than descriptive analysis.
While descriptive analysis explores the most diverse possible advertising data points, this model ends up exploring only a small part of them, previously determin by the analyst or manager. It is capable of providing answers to questions about problems already known through previously obtain data, so that it is possible to build relevant solutions to these issues.
In general, the use of diagnostic analysis is bas on its use to understand problems that have already occurr in the company — which we ne to prepare for — and that may occur again in the near future.
Data is important correct analysis even
The use of data analytics is essential today for any and in many cases, this is obvious business to achieve the desir good results, and can be us in a variety of ways: forecasting trends, managing crises, solving problems, defining the target The identification marketing list of idle audience for a new service or product, identifying customer and user behavior patterns, among others. The list grows with each problem observ in the day-to-day operations of businesses.