En français s'il vous plaît!

Big data: Future predicting data

Prédire l'avenir

Text by Bertrand Lirette

Illustrated by Jérôme Lessard

1939. Germany invades Poland. During that period, remarkable efforts were put together simply to obtain information pertaining to the troops’ next move: specialized war strategists understood the importance of information. Some say it even had the power to promise victory to those that beheld it...

The goal of this article is to popularize concepts in order to share information and especially promote conversations and exchanges. The ideas and layout underlying this article were largely inspired by the excellent blog entitled “A List Apart”.

Among other things, I am currently working as a technician for teaching and research projects in the undergraduate program of graphic design at Laval University in Quebec. My laboratory classes in the undergraduate course “user’s interface and interactivity” offer stimulating experiments in order to help students master their knowledge in this specific field of information technology. I learned this technique in the 3 year program of multimedia integration techniques at Cégep Ste-Foy. I perfected my knowledge in integration, programming and project management for more than 5 years at an advertising agency called “Triomphe Communication marketing”. I have been committing to the principles of breakdancing (B-boying) and spend a lot of time (perhaps too much) working for the non-profit organization that I founded: Quebec B-Boys.

Suggestions/Comments
hey@bertrandlirette.com

Let’s fast forward to the nineties: Internet made its greatest breakthrough! Being able to communicate not only vocally, as it was already possible with the telephone, but also by exchanging documents and corresponding with numerous people, turned this new means of communication into a revolution. In a brief moment, we could contact a multitude of people regardless of their geographic location and do all that almost instantly.

In order to facilitate navigation through all this information, a markup language and web navigation programs had to be created. From this time forth, it was possible to display data in a way that made it easy to read. The birth of HTLM markup language and web navigators such as Mosaïc allowed researchers all over the world to broadcast information in a structured manner.

A few years later, people worldwide could access this power. Internet access was mainly democratized with high speed connections that allowed us to navigate more rapidly through this vast information.

After that came a massive change pertaining to information found on the Internet. The ease of broadcasting information in a text format and even through videos improved Internet thanks to contents provided by people across the globe. People no longer needed to be technical geniuses to broadcast information (zealots called this the “web 2.0”era).

Since a few years, we have witnessed data transferred automatically online-not entered by users but by sensors that are surrounding us increasingly. They can be found in those cameras aiming at our highways, the GPS in our cell phones, pedometers in the soles of our shoes, etc. For instance, combined with the analytics capabilities of today’s computers, these sensors can suggest an alternative route to avoid a traffic jam on Charest Boulevard, let you know that you attained you goal for your daily footsteps or verify if Carl met his friends at Le Boudoir. The bridge between the virtual world and reality is now an automatic process.

All these events are observed on a daily basis. All these new sources of information combined with computers’ power of calculation will behold a multiplied potential in the near future. Crossing data can be defined as taking a single data and associating it with a fact, often in order to draw a conclusion. For instance, by observing the exact days and time that Jerome buys the delicious Starbucks’ “Venti”, we notice that most of his purchases are normally done within a minute from Fred’s purchases. Crossing data would allow us to conclude that there is a connection between these 2 individuals. What?! Are these 2 colleagues taking their break at the same time? You will most certainly conclude that this is a simplistic example and I would respond positively. However, in pedagogy, it remains a principle: we start with a simple concept and gradually increase the level of complexity. Please have the courtesy to follow me down the “rabbit hole”...

Let’s continue with another example. Alex is a young student and like most of his colleagues, owns a cellphone. Among other purposes, he uses it to check the bus schedule. This morning, he took the number 15 (depending on your location) to attend his design class, like he does so every week. Unfortunately, when he got off at Revenu Québec, he realized that his bus transfer to take the number 7 wasn’t available. There was a traffic sign indicating this change so Alex used his phone app to find an alternative route because his usual trajectory was unavailable. This action, though quite common for Alex, generates information that the app designer could use in an effective manner.

Accessing an app is an action easily identifiable by the app itself. With an ability to record previous data that would make George Orwell shiver, apps have been able to record users’ behaviour for ages. For example, an app can compile a user’s habits of errands and whereabouts. Consequently, using that information, the app can identify all the people taking the modified route and send them a message indicating an alternative route before they find themselves in a frustrating situation or arrive late.

Ok now.

Indeed, there are certainly a few obstacles: being able to flawlessly distinguish people who are actually taking the route from those who are simply checking the schedule. However, at this point, it’s only a question of data size and data analysis. Mathematics, crossing data and logic –a lot of logic.

In sum, the grounds are set for great accomplishments resulting from the use of a large amount of data, as long as it is high quality (but that is another topic). If we wish to avoid a traffic jam on Charest Boulevard and intervene before it happens by referring to the warning signs, it is now possible from a technological perspective. All you need is the right equipment and data to begin processing them.

Predicting the future? Why shouldn’t one dream. “The truth is out there“ as they would say. However, I prefer the following statement: “The future is out there”...


Useful links:

Let's discuss and share: