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Product Strategy

#Big Data for everyone


My attention has been recently drawn to some headlines in the European IT specialized press that were mainly focusing on Big Data strategies and innovation. In fact, this type of headlines has become more and more frequent in recent months. What does Big Data mean or how can we take advantage of it? According to the EU’s digital agenda for Europe, generating value at different stages of the data value chain might stand at the very core of future knowledge economy. In fact, improved analytics and data processing, and Big Data in particular, are able to increase efficiency at multiple layers of society.

There are still some questions to be asked:Are we really talking about Big Data?

The main difficulties company co-managers are faced with in 2014 are related to the innovation of their products and marketing practices. Already used to massively send their clients paper documents, they have decided to implement a Data Mining solution to better target the sending of thematic catalogues.

It’s a sort of the forbidden fruit: as long as we don’t deprive ourselves of it, we’ll always be asking for more. One can only imagine that the next steps will be increasingly digital and based on a more important real-time approach.

Is Big Data for everyone?

Without simplifying or reducing its scope, Big Data is an extension of Business Intelligence. In BI, we are dealing with a post-analysis of a (not necessarily big) data collection for obtaining indicators. Based on its multi-V (Volume, Variety, Velocity, Veracity, Value) approach, Big Data allows companies to have a real-time perspective on more massive, diverse, variable, real-time data, as well as to predict facts (sales, production, etc.).

If there were cases in which indicators enhanced the decision-makers’ flair, now they can help the latter take statistical approaches one step further. Nowadays, decision-makers must be able to reinforce predictions with facts. That is where might lay the first problem. It’s still the time of evangelization but we shouldn’t do things just for the sake of doing them. Beautiful experiences are now shared.

The profile of a Big Data expert

The extension of a BI team’s perimeter will not take place naturally since skills differ greatly across groups. If for BI we (obviously) need persons able to communicate, for Big Data we need tools practice and especially a good knowledge of business data, not to mention the following extra-skills:

  • Data Scientist: Besides knowing the data, we should also be able to exploit it.
  • Technologies: The technologies used are different from and complementary to BI. We should thus master its new capabilities.
  • Mathematics & Statistics: There lies the greatest change of all. This skill isn’t the simplest since the necessary basis isn’t negligible. It’s precisely at this point that one must be able to anticipate (training) or even recruit.

Big Data to be found where least expected

Not all companies will make Big Data but they will surely move one step closer to it. The issue of DATA becomes central to various activities, even in everyday life since we have ceased to be the only ones in charge of what we want. We’ll have to get used to it.

On the other hand, I’ve recently had an exchange with the owner of a hardware maintenance service. I warned him about the need to collect a maximum amount of remote equipment data that his company was maintaining at that point. He thought he was miles away from Big Data but if that equipment is connected to send use data in real-time, the maintenance service can be pro-active. He can equally offer a better proximity service through targeted counselling on best practices. This is already a reality in various fields in order to achieve an improved customer satisfaction.

The cost of the solutions and implementation actions are not yet accessible to everyone but new values are at reach. You should thus go searching for the innovation where least expected. Your data is valuable!

If you have been confronted with real-time data, volume, or prediction research issues, Pentalog has the answers to all your questions. Just contact me!

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