Business intelligence or predictive analytics?

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Business intelligence or predictive analytics ? In many organizations, this choice is still planned when, in reality, there is no need to choose between both options: there is no need to deprive yourself of any type of knowledge. And business intelligence is nothing more than a form of analytics, which today has come to be called descriptive because of the results it produces; that are improved thanks to predictive analysis. Predictive analytics augments existing BI capabilities by highlighting that there are differences between both types of analysis. What must be understood is that these are not irreconcilable differences, but rather complementary and necessary qualities, both, for the business and its management. Business intelligence and predictive analysis: main differences Predictive analysis is characterized by: Provide answers about the value of certain customers, the importance of certain products over others or the potential for success of a marketing campaign. You can provide greater richness in your response by introducing the future variable, which is not included in business intelligence.



Its recommendations optimize decision making, minimizing risk by adding the knowledge acquired based on business intelligence. In addition, predictive analysis provides ideas about the business , discovers opportunities and prevents risks, thanks to prediction, a capacity that allows the organization to be informed of what is likely to happen and the reasons why it may occur. Predictive analytics finds and quantifies hidden patterns in data using complex mathematical models that can be used to predict India Part Time Job Seekers Phone Number List future outcomes. For its part, business intelligence: It deals with a retrospective analysis that reports on what happened. It can provide visibility into what is happening. It is also used to look for trends and delve deeper into the data, identifying areas of action based on geographical, temporal, marketing, sales or any business dimension variables. Business intelligence and predictive analysis: inseparable complements Perhaps the easiest way to understand the differences between business intelligence and predictive analysis is by looking at the responses that each analytical modality can generate.





For example, business intelligence allows you to answer questions about the demographics or characteristics of your customers, products, stores, etc., and answer questions about business performance across a number of different dimensions. However, predictive analysis goes further, taking the questions that business intelligence is answering to the next level and dealing with the prediction of performance and the prescription of specific actions or recommendations in each case. The differences are clear but knowing them highlights the need for both modalities of analysis to coexist. Business Intelligence is necessary to know key aspects of the business, but, to gain confidence when undertaking new actions, predictive analytics is essential, due to its approach, completely different from the conventional BI approach , which allows optimizing available resources and not miss any of the opportunities that may arise in the future. Related posts: Internet of Things: comprehensive monitoring as a horizon Artificial neural networks: reality and science fiction in BI Predictive models: reinforcing the value of a good decision.