The 10 Most Hi-Tech Cities in the World

When asked the question “which are the top 10 hi-tech cities in the world?”, even the most “tech savvy” candidates tend to have a hard time comparing and/or imagining what is happening on the other side of the globe. In this way, the question is worth asking, and frankly, is far from easy to answer. When searching on the web, most of rankings found in Shakespeare’s language, such as the Popsci or the Wired rankings, tend to focus exclusively on American cities. Personally, the ranking I found the most interesting was one published on the website of The Age, a mainstream newspaper from Melbourne, Australia. Based on six criteria (1. Broadband speed, cost and availability; 2. Wireless internet access; 3. Technology adoption; 4. Government support for technology; 5. Education and technology culture; 6. Future potential), here is their conclusion:

1. Seoul, South Korea;
2. Singapore, Singapore;
3. Tokyo, Japan;
4. Hong Kong, China;
5. Stockholm, Sweden;
6. San Francisco (and Silicon Valley), USA;
7. Tallinn, Estonia;
8. New York, USA;
9. Beijing, China;
10. New Songdo City, South Korea.

The presence of four cities (Seoul, Singapore, Hong Kong, New Songdo City) from the Four Asian Tigers is not surprising. However, the presence of cities like Stockholm (Sweden), Tallinn (Estonia) and New Songdo City (South Korea) is certainly something that yields the most expressions such as: “oh”, “ah”, “what’s that”, “are you kiddin’?”, “really?”.

The presence of Stockholm makes sense when looking at rankings that classify the city as the one with the fastest broadband speed in the OECD countries. Moreover, Stockholm is acting as a pioneer in the use of green technologies such as RFID technologies, and paired with the high number of engineers due in part to the presence of Ericsson, those could be factors that contribute in making this city’s ranking first among cities outside Asia.

The city of Tallinn, mostly unknown to North Americans, except for those who have learned the world’s capitals after the fall of the USSR, is known as the Silicon Valley of the Baltic Sea. The city is also known as being the first to organize an election vote on the internet using smartcards, as well as for its free wireless internet facilities across the city. Tallinn is also recognized for the well-known start-up Skype.

Finally, New Songdo City, situated 60 kilometers East from Seoul, is certainly the most fascinating city in this ranking. The city was built from scratch by Gale International, a real estate development and investment firm, and is considered by technology experts as the ultimate digital city of the future. Even if the city is still upon completion, it is already considered in the top 10 of the most hi-tech cities in the world.

New Songdo City - A New Worldwide High-Tech City Built from Scratch
New Songdo City - A New Worldwide High-Tech City Built from Scratch

I can briefly conclude this post by noting that it is nothing new for North America to be limping way behind Asian countries in terms of hi-tech development, and this ranking is only a glimpse of what’s coming next in technology development….

Jean-Francois Belisle

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What is Big Data? From Bytes to Petabytes

This post is the first of a series of posts related to Big Data, since I thought it was worth going in-depth with this topic. Big Data is a big word, a big buzzword, some might even call it big bullshit, since many components revolving around Big Data, and especially the ones on the analytics/methodology side, that we can label Big Data Analytics, have been around since more than a decade.

Monday June 18th 2012, I went to the Big Data Montreal event #5 as it is written on my Foursquare feed (yes, I used it sometimes!). The event involved presentations mainly on programming and on what where the best software frameworks to use to correctly tabulate all of these data. The conversation was about software frameworks such as Apache Hadoop, Pig, HiveQL and Ejjaberd, all software frameworks I’ve never programmed with, and that have for objective of cleaning the mess in unstructured data. Personally, this is a part of Big Data I’m less familiar with, and what I’m better at is what follows these steps in the process, “Big Data Analytics”. But what is really Big Data?

As defined in “Big Data: The next frontier for innovation, competition, and productivity”, a 143-page report that will become a classic report, the well-respected consulting firm McKinsey suggests that “Big Data refers to datasets whose size is beyond the ability of typical database software tools to capture, store, manage, and analyze” (p.1). So what does this mean? It means that Big Data is only a term that refers to a big dataset, and what revolves around this database are only supporting concepts to Big Data.

Why Should We Care About Big Data?

Yes, Big Data are everywhere, similarly to cheesy teenager’s pop bands that all sounds the same. But do you remember the sentence: “You can’t manage what you can’t measure” by management Professor Peter Drucker? If you don’t, then you should from now on. However, in this Big Data era, the competitive advantage should emerge from the following sentence: “you can manage what you can measure with the right method and the right software”. A little longer and less sexy than the one by Drucker, but at least it is a great follow-up.

Big Data
Big Data are Everywhere

Theorizing vs Observing?

Is Big Data killing science? Is it killing theory? Psychologists create and develop theories by testing on small sample sizes. Big Data analysis is based on the model of Physics which suggests that a different pattern may emerge from any Big Data, which means that there is no point of having a new theory, what we care about is the pattern that is specific to a particular case. In 2008, in a provocative article entitled “The End of Theory”, Chris Anderson, Wired editor-in-chief, made a statement about how Big Data are becoming more and more important in many fields of study. Related to this point of view, I completely agree even though Chris Anderson might be biased since he’s a physicist by training. In anyways, I think that a pattern that emerges from Big Data might be explained by a theory or a series of theories, which would reconcile both points of views.

Conclusion

Big Data may sound simply like a buzzword for many of us. However, even if many of the components that revolve around the concept have been around since many years, as previously mentioned, I agree that the software and programming software used for big data extraction are way much newer than the analytics methods associated with Big Data. It’s so hot at home, I’ll enjoy a big glass of water and prepare for big work tomorrow. I raise my big glass to Big Data!

Cheer up!

Jean-Francois

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