What is advanced data analytics?
Data capture refers to the process of compiling information from any type of structured or unstructured document, in order to convert it into a legible data format for later processing and analysis.
It means transforming information into data that can be analysed, so that knowledge inside a company can grow.
The data capture process can be carried out using different methods or tools. Companies can use data capture tools that fit their systems, organise workflows and let data move quickly to where it is needed.
What types of advanced data analytics exist?
- Descriptive analytics: this is the preliminary stage, the one that answers what has happened in the business. It summarises historical data to provide useful information and prepare the data for later analysis. Finally, a graphic visualisation or BI layer is created that produces visible, easy-to-understand reports.
- Diagnostic analytics: this answers why this has happened in the business. In this phase, after finding an anomaly, a failure or a figure outside what was expected, the data is processed to locate the root of the problem. Once the problem is located, a report can be produced that only details the issue found and how to solve it, or either of the next two analytics phases can be applied.
- Predictive analytics: the question at this stage is what will happen in the business. This third phase provides tools to estimate business data that is unknown or uncertain, or that needs a manual or costly process to detect. This kind of analytics makes it possible to get ahead of customer demand, for example.
- Prescriptive analytics: this is one step further: how can we make the proposed scenario happen? This kind of analytics helps carry out the strategy needed to reach a goal. It is achieved by optimising processes and business rules.
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