The phrase “The true voyage of discovery does not consist in seeking new lands, but in having new eyes,” extracted with a certain freedom of synthesis from Marcel Proust’s In Search of Lost Time is perhaps one of his best known and used phrases, in various contexts and for various reasons.
It is certainly evocative and fascinating and, in some ways, reflects a different way of seeing things and dealing with problems, although personally I believe that, in a business context, it might be more accurate to say, “The real journey of discovery is to seek new lands and to do so with new eyes,” to highlight that in a global, fast, fluid, and competitive world, survival is almost always a matter of goals (the new lands) and the strategy to achieve them (the new eyes).
Seeing with Data
We live in a digital world, where data is our eyes, very effective ones, able to embrace a panoramic view, but also to go down to the finest detail, giving us so many stimuli that sometimes it is not at all obvious how to manage them, and we run the risk of losing them or even not being aware of having received them.
Ultimately, we risk not seeing what we are looking at, and this is not because we do not have enough data, but because we have so much that sometimes it becomes very difficult to manage. This is not from the point of view of sending or receiving the correct signals – technology is so mature that it now guarantees that nothing is lost – but because it is difficult for us to be fully aware of what our eyes have seen, as if our brains are not always able to keep up in making their selections.
This is why data needs to be managed as efficiently as possible, and if possible, at the exact moment that the data is generated, neither before nor after, because everything that happens is here and now, and if the goal is to know to act, then to produce the desired effects, the action must be prompt.
Looking vs. Seeing
Rather than more data, of which we already have more than enough, what we need is a new way of seeing, a way that guarantees agility and awareness, one that goes far beyond solving the technicalities related to data access and one that leads, instead, in the direction of the effective use of data, because the value that we can extract from data is in the use we make of it, just as the value of bricks is in the buildings we can build with them.
If we assume that “looking” equals collecting data and that “seeing” equals making use of it, then our efforts must focus on the latter, since everything has been said about the former and, perhaps, the problem is even to limit the bombardment of data, which is often so voluminous that instead of giving us information, they obscure the possibility of doing so.
To see in the best possible way, we must have a reference system that enables us to classify all of the data, because in order to transform the data into information units, we must have a conceptualization that enables us to place each record where it should be placed.
We must also be able to share what we see, because we are part of a system, one in which sharing is a fundamental asset, as that enables us to be a system rather than the mere sum of its individualities.
Given that we have been able to see what we have looked at, we must also gain the ability to adapt what we have seen to what we need. We must be able to combine data from different sources so that it produces those representations that enable us to give meaning to what we have seen and, consequently, act according to what, in John Searle’s words, is our intentionality, that is, the way we use what we know to achieve our goals.
In summary, we must be able to intercept all data, however it is made and wherever it comes from; we must be able to synthesize this data and make it available, to combine it in order to go from looking to seeing; we need to be able to share what we have seen with others, because we are part of a system, and because we often have common purposes and, finally, we need to reduce the barriers to data access, because our goal is the democracy of data, the correct balance between keeping the information for itself (data dictatorship) and making it available without any rules and control (data anarchy).
Data Virtualization and a New Way of Seeing
If we accept the parallel between eyes and data then what we have to do and what we have just described leads us to imagine a data management system that enables us to implement everything we have talked about. From this point of view, to base such a system on a data virtualization approach is an excellent starting point, considering that this would enable us to:
- Reach data easily, wherever it is and whatever format it is in.
- Combine data to produce richer information constructs, to the point of generating knowledge and wisdom;
- Separate the data in its logical and physical component (or intentional and extensional), so that meaning and signifier are clearly distinguishable. In other words, there must be a clear separation between the meaning of the data and resulting realizations.
- Easily consult the data without having to be aware of the syntax that regulates the native format. In other words, for each data set, it must be possible to represent it in a standard format that is reasonably known, easy to read and, of course, semantically equivalent to its native format.
From this point of view, therefore, data virtualization represents a new way both to look and to see, one that enables us to not only manage data more effectively, but also to place data in a wider interpretative context that extends its potential value.