Nobody can deny we swim in an information’s world, likewise it is true that most of us get overwhelmed about everything that exists “around”; but is is also true, on the one hand, the fact that so much noise is being generated, much invalid, untrue, uncertain information is being generated, and, on the other hand, the fact that we can not handle the good ones.
Alejandro Asúnsolo. @content_mk

Fuente: rutgers.edu

Yes, it is another usual concept in present posts, tweets and articles. And like every concept, almost every one of them, it is something that exists from long time ago, but something that is being formed and adapted to the new reality. The thing that confers Big Data that so-much special character in these times is that it is introduced like that thing we all understand to be necessary but that very few people know how and wht to do about. It is XXI century’s disease: you know you are doing it wrong but you keep on doing it because you can not stop to think about it too long.

What Big Data is?

So many things, but, to be understood, Big Data is when we go from the thought that our information can be hosted into a conventional data base to the thought that it is no longer enough, and, therefore, that we need resources, method, software, hardware and many other things so we can see the light among all the information we receive, notice, see and also disclaim about our environment.

Governments, scientific institutions and multiple players put big resources, from long time ago by now, into the right management of all the information they have. Obama himself did get a profit from it due to his reelection.

As for companies, Big Data appears when you actually go from considering a stocktaking or a reference of your items to pondering that the information you manage includes, besides, your CRM’s information, your logistic line, your interactions in Social Media, your Content Marketing campaigns, your loyalty club, the imputs of the coventional media…, and so on to something so big that becomes… Big.

Big Data exists, as we said before, from much more time ago than its own name does, but current technology makes a must from it inside big companies’ world, so much more inside those ones involved in ecommerce or presented as omnichannel companies. But it is not a company matter. Governments, scientific institutions and multiple players put big resources, from long time ago by now, into the right management of all the information they have. Obama himself did get a profit from it due to his reelection.

McKinsey said that a retail company could make their operational margins grow a 60% due to Big Data.

Therefore, Big Data is much more than software: it is planification, it is knowledge, it is hardware (beware of the hosting I will talk about later), it is specific resources and profiles, it is investigation and development, it is legal issues, it is time, time and time. And that is money, money and money. I will not discuss if it is investment or cost. If you consider the second one, then do not keep on reading.

You will have to decide which information you choose instead of another one, to make a priority among your necessities of information, to turn your quests into sequences due to the available resources.

There must be something when companies like Oracle, Microsoft, SAP, HP, Dell are investing hundreds of millions in resources and investigation of Big Dta, and there are already very many head hunters desperate for finding profiles in a level enough to approach to the responsability of managing the big data of a company.

Some more details:

• It makes much more transparent, clear, the stored  information. It classifies, clarifies, administrates. It is, clearly, Ordena, clarifica, administra. It is, clearly, one of the most important values into current company.
• It allows to enlarge the information’s circle of lifw with new variables we did not know before or we did not include before, it also manages the transactional elements.
• Due to the stored and managed information we can take those business decisions much closer to customer’s reality.
• Current digitalization strengthens the “just in time” of the information, and, therefore, of the companies’ reaction about what is happening.
• It is and it will be an element which makes a difference versus the rivalry. The company to manage better the huge existing amount of information will be ahead the one that has stayed around the concept of Business Intelligence or the personalization of messages.
• It is a window to the future, The complex and improved systems in variable measurement and behaviour studies are ingredients of a Big Data that will allow to overtake possible necessities into business issues, possible deviations about the estimation and, as I said before, to hit into decissionmaking.

What is “also” Big Data

But there are some basics we can not forget. It is clear the easy thing is to understand that a good management of the information is something useful, sure, but you must consider at least this elements:

• Big data also is to host many interferences, many incomprehensible data, or, in the positive side, so many information that you will have to decide which one you prefer, the priority of your necessities about information, the sequences of your consultations to that information due to the available resources. I talked about planification before. That is.
• It is a global environment, it is just not referred to the information of one of the elements you are about to consider. You have to consider every element of your data’s chain as a not independent part of the rest at all. An incidence captured in the chain supply has to fall on your call center information, a complaint in Facebook has to have a direct impact in your data base, or an improvement in the management procedures of the cash desks has to be seen and measured in your information system. And you can manage variables with different timing, different behaviour models. This is science, there is no doubt.

Current supply chain management must be concerned with multi-dimensional data that includes temporal and geospatial elements. Examples of temporal data are the acquisition of data from sources such as the Internet, speech and video data, real-time imaging from satellites, and ground-based sensors. Such inputs can be difficult to analyze because the different sources that comprise the data stream have different latencies. Moreover, the amount of temporal data is growing exponentially. Geospatial data, on the other hand, tracks location, whether that of a storm, a car, or a tornado that may render impassible to your trucks certain highways, thus demanding quick redirection to avoid time lost and equipment damage. For shippers, for example, both elements come into play: it is useful to know the location of ships, containers, and even packages in real time and/or two days prior in order to see if interim movement in is unusual and requires action. Coupled with temporal data, a logistics analyst can make informed decisions as events in his supply chain unfold.

Five Steps To Master Big Data and Predictive Analytics in 2014. Forbes.

• Data are sensitive. Who is going to hace access, which data you are hosting, and where and which use you are going to give them. These are basics in any environment of more or less delicate information management, but if we talk about of Big Data you will have to propose that we talk as well about a Big sensitivity. You must ensure this issue well if you want in medium term to get over an audit that probably will give you many problems.
• Knowledge takes place. And so much. One of the current problems is, clearly, that one that refers to data hosting. Wallmart handles 1.000.000 of transactions or every of their customers per hour, or Facebook, that has more than 50 billions of images. It is considered that companies duplicate their onformation in 1,2 years. And where do we put all this. There are so many solutions in the market place, pero they are expensive and they worth the cost, or are you going to be silly about the security copies?
• It is not a place for rookies. Do not leave Big Data in unknown hands, just in the the most known hands. The required profiles have to be multidisciplinary, specialist, and they have to know so well the frameworks on your business’ model. There are necessities in the business and technical knowledges, you will need a very full team oriented to improve the hosting systems, processing, testing, depurating and development.
• To have many data without  brains is the same than to not have data at all. Another big mistake is to enter the Big Data world and to have a lack in resources, time or even business sensitivity, and, to be well-used, you will have to go from Big Data to Smart Data, a not-so-easy issue if you can not do it.

As you can see, it is an issue you can not put aside, and you can not think it is simple, easy and answerable with a good software, as good as the company that tries to sell it to us can be.