Advanced analytics is a complete customary of analytical techniques and methods. Big Data, Artificial Intelligence, Machine Learning, Continuous Intelligence. It allows better predictive analysis and provides information on the change, giving a broader vision that enables organizations to develop better responses and act on more accurate forecasts and plans.
It is a valuable resource for businesses because it allows a company to get more functionality out of its data, regardless of where it is stored or in what format. Advanced analytics can also help solve some of the more complex business problems that traditional BI reports can’t.
By combining consumption models with historical data and artificial intelligence (AI), advanced analytics can help businesses find accurate answers to these questions.
Differences between Business Intelligence and Advanced Analytics
Advanced Analytics answers multiple questions and contains multiple business intelligence components.
This type of advanced data analytics emerged to help answer the question, what has happened in the business? It is a preliminary stage of data processing. In this stage, a summary of the historical data provides helpful information and prepares the data for further analysis. Finally, a graphic display or BI layer is a form that generates visible and easily understandable reports.
This type of advanced data analytics emerged to help answer the question, Why has this happened in business? It is the second stage of data analytics. In phase, after finding anomaly, failure, and expected data, the data is processed to locate the root of the problem. Finally, the situation has to pinpoint. Then, a report generates that only details the problem and how to solve it or apply the following two analysis phases. If we use predictive analytics, we will be able to see how this point affects the business in the future, and if we apply prescriptive analytics, we will be able to see how to act.
This type of advanced data analytics emerged to help answer the question What will happen to the business? This third phase of data provides tools to estimate business data that is unknown or uncertain or that requires a manual or costly process to detect. This type of analytics allows you to strengthen business decisions and, for example, will enable you to anticipate customer demands or detect fraud in electronic payments.
This type of advanced data analytics emerged to help answer the question, How can we make the scene happen? For this, prescriptive analytics. This type of analytics also helps fulfil the procedure to follow to achieve an objective. It is complete through process optimization and business rules.
In addition, It is essential in the digital transformation of many companies because, thanks to the exhaustive analysis of data, we will be able to base the decisions we make on real-time information and not on assumptions, instinct or points of view.
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