Advanced Analytics Consulting

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Advanced data analytics for businesses

Tras la ingente cantidad de datos que se generan hoy en día en las empresas se esconden grandes dosis de información. Esta información es lo suficientemente valiosa dentro de una empresa como para invertir tiempo y dinero en localizarla y hacerla entendible. De este punto se encarga la analítica avanzada de datos.

La analítica avanzada de datos extrae la información importante residente en los datos que se generan a nivel, tanto organizacional como externo, realizando cruces de datos y mejorando así la información y las conclusiones obtenidas.

What is advanced data analytics?

Data capture refers to the process of compiling information from any type of structured or unstructured document to convert the data into a legible format that can then be processed and analysed.

It involves, therefore, transforming information into data that can be analysed in order to increase knowledge within a company.

Different methods and tools may be used in the data capture process. Companies can use data capture tools that are compatible with their systems, organise work flows and allow data to be transferred swiftly to the required recipients. 

Qué es la analítica avanzada
Tipos de analítica avanzada

What are the different types of advanced data analytics?

  • Descriptive analytics: This is the first stage, addressing the question “What has happened in the business?” It involves summarising historical data to provide useful information and preparing data for subsequent analysis. Finally, a graphical visualisation or business intelligence (BI) layer is added to generate visible, easy-to-understand reports.
  • Diagnostic analytics: This stage examines “Why has this happened?” If any anomaly, failure or outlying data point is detected, the data are processed to locate the cause of the problem. Once the problem has been tracked down, a report can be generated that details the problem and how to resolve it, or how the next two stages of data analytics can be applied. 
  • Predictive analytics: This looks at “What will happen in the business?” This third stage uses tools to estimate unknown or uncertain business data, or data which can only be detected manually or using costly methods. This type of analytics allows us, for example, to anticipate customers' needs.
  • Prescriptive analytics: This takes analytics one step further, asking “What do we have to do to make this scenario happen?” This helps the company develop a strategy for achieving an objective, by optimising its processes and business rules.


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