Key elements for an effective exploitation of Big Data

3 min reading
Key elements for an effective exploitation of Big Data


Although Big Data is now in the early stages of integration within enterprises, there is no doubt that it will be an essential element for businesses. To take full advantage of all the added value this trend can provide we are going to introduce you three key elements for its exploitation and three real implementation cases.

Companies and even governments are increasingly starting to extract business value out of Big Data with the collection, storage and analysis of the so-called large data sets that are generated every day.

These are the three cornerstones for a good exploitation of Big Data:

1. Channelling algorithms used by predictive analytics technologies towards those information patterns that best suit the objectives established.

For example, the algorithms used both by eBay and are addressed, among other things, to analyse, understand and predict the behaviour and preferences of their users in order to recommend them the products that better suit their tastes.


2. Although it seems paradoxical, another lesson to keep in mind is to use the data to create more data, as unveiled by Forbes magazine. Google, for example, uses the information about the link or links that are clicked within a set of search results in order to improve future results.

3. Another tip is to adjust the data to a specific target to try to fully satisfy the needs of each client. This is something normally used by advertising companies, but it can be applied in more sectors. In medicine there are companies that are working on ways to customise therapies based on the genetic profiles of patients.

Big Data is virtually applicable to any organisation in any industry, even though among the most active are the banking, healthcare, finance, communications, insurance, energy and retail sectors. These are just three examples of what is already being done harnessing the value of data:

– The lingerie shop True & Co has launched a new technology that combines advanced algorithms to make suggestions to its customers and, just like Amazon, recommend a selection of products from different brands. Using a questionnaire, “Take our quit fit”, the store aims to eliminate the cumbersome process of having to try many products to find the desired one. Instead, thanks to the analysis of the answers given in the questionnaire, the company sends to the client's home five models, which customers can try and return if they don't like free of charge.

– BBVA and the City of Madrid, as part of their collaboration commitment, have shown with a study to what extent Big Data can contribute to develop the Smart City concept. The study analyses the behaviour of visitors to Madrid with an unusual degree of detail, based on the data of payments made with credit and debit cards in the capital's shops. All this information has allowed knowing the different activities carried out by visitors, their profile based on their origin, sex, age, and other sociodemographic segmentation variables. This is something that will gradually change the way cities analyse and manage tourism.

– Earlier this year we saw Generali Insurance take advantage of the Big Data partnering with Telefónica in the launch of the service “Pago como conduzco” (I pay as I drive.) Thanks to Telefónica's M2M technology, Generali analyses the behaviour of each client individually, adjusting the insurance premium to his driving style.

The service is based on the installation in the insured vehicle of a telematics device with M2M technology that collects data of the journeys made, taking into account factors such as the number of kilometres travelled per year, if they are diurnal or nocturnal, urban or interurban, if the driver observes the speed limits or if he accelerates or brakes suddenly. This data is processed by the system in an aggregated form and the driving profile and the resulting score is sent to Generali to adjust the premium.

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