NB: This is a guest article by Larry Smith, a partner at US-based Thematix.
Data is always plural, and it can be big in many ways. Huge, enormous, gigantic, epic – you get the idea.
It can be raw data, it can be interpreted into information, and it can be elevated through the association with other data into knowledge.
As semantics enables machine learning, a new level – wisdom – is possible, as IBM Watson has demonstrated.
Using a hotel as an example, raw data might be the latitude and longitude of the property and facilities, the information might be interpreted via a street and mailing address, while the knowledge is that you’re walking distance to a tourist site or office building.
Wisdom comes from adding police reports about area crime or location of the nearest hospital for food allergy treatment to keep the family safe.
Every minute of everyday, there are billions of data points being created about travel and tourism.
These data come from people offering social commentary, blogs, and surveys; from participants including GDSs, government, banks and credit card feeds; from automated things like remote weather sensors and traffic cameras; the list goes on.
The data may be captured, stored, and shared in structured or unstructured ways, then crunched to expose similarities and differences, illuminate trends, and predict future outcomes.
But Big Data is not only about volume and magnitude, it’s about quality and richness — and that’s where immediate opportunities and ROI can be found.
Examination of travel data
Think about your data: you can create it, add value, and expose it as enriched information, knowledge, and wisdom within your domain. The more you add and share, the more value is created, and the bigger it gets.
For example, your hotel is hosting a trade conference of musical instrument manufacturers.
A link from the association to the hotel booking page with a discount code is standard, so you’ll know the names of people booking, why they’re staying with you, and that their interests involve a love of music and its performance.
Depending upon the transaction process you might know about the train, plane or automobile they took, their party size suggesting business or family intentions, and any upgrades they might have purchased.
The data package is hugely valuable to you and many others in your trading partner ecosystem.
So as a practical business matter, the issue is how to transform this data into customer loyalty, competitive advantage, and revenue.
Practical applications
There is no want of ideas: is it time to test out Karaoke in the bar one night of the conference, suggest some special movies on demand, work with local tour operators and music performers to expose events, and give away a few free iTunes download cards in exchange for e-mail addresses and cell phone numbers.
Also, consider what data you create and how to expose it to more people in interesting and usable ways. All the data that is generate by operations, food & beverage, housekeeping, billing and accounting, etc. are sources for knowledge when combined with other data and a specific business requirement and use case.
Use caution when considering the need to generate new data (especially if new or incremental work is required) unless there is a very specific need or well thought out usage.
For initial pilots the data you already have is most likely enough to achieve some immediate and satisfying results.
Also, don’t work alone with data – it’s plural, and it works best in partnership. Look to your employees and every vendor, business partner and supplier for assistance and input; good data insights benefit everyone involved.
One of the best and easiest ways to begin is with a pilot that exposes events and activities in and around the hotel. In testing schema.org mark-up, we discovered immediate and lasting return on investment; read more here.
The results have been so impressive that we’ve published an extended set of open (and free) mark-up tags, available as an OWL file upon request.
These tags permit one to go beyond the basics to referencing hotel specifics such as a room, features, services, amenity, and room rates, thereby further informing the search engines (Google, Bing, Yahoo) in greater and more precise details.
While hotels have been an example, there are similar benefits for everyone in the travel industry. Trains, planes and automobiles can consider integrating themselves into an entire journey, not just the points of transportation they supply.
Tours and attractions can use and supply data from others by discovering what consumers value.
So when you think about Big Data, remember that while you can add to its volume, you can also make it Big in its value.
NB: This is a guest article by Larry Smith, a partner at US-based Thematix.
NB2: Big data and lock image via Shutterstock.
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Good article … information is power … leveraging good information is powerful …
This is a good article. The other important aspect of unlocking Big Data is transforming it into very simple and digestible formats so that consumers see the Big Value. Vayant has done that with our latest FastSearch product for airfare search. It would be fantastic for somebody to come up with an equivalent for hotels!
What has changed? is this ‘big data’ a recent phenomenon, or is it just a play with words. To me its just useless as a workable concept for the small (travel) business – unless someone can tell me how do do it, and economically, instead of just pontificating about it.
its like social media, just another solution looking for a problem.
From an implementation point of view I really prefer Facebook’s proposal for adding semantic meaning to webpages, https://developers.facebook.com/docs/opengraph/ – it’s a lot simpler than the schema.org way of doing things. If you check your Open Graph semantic markup via Google webmaster tools they grudgingly recognise the open graph markup but it’s not certain how they use it.
It would be great if the big players could get together on semantic markup but it looks to me as if we’re headed for another confusing round of multiple standards in web development.
Good article, however just jumping on teh Big Data bandwagon. There’s a lot of hype around this buzz word, RG is right, this is nothing new. In fact, the travel industry has been doing this for years. I should know, as Teradata has been the #1 big data company since its inception. The largest airlines around the world, along with Sabre and ARC, use Teradata to glean “wisdom” and make fact based decisions daily in near real time at a scale that is unmatched. Why all the hype in 2012? Not that I’m complaining. It’s all good.
There are two issues facing the widespread use of big data: 1) opening up data for consumption 2) making it easy and inexpensive to consume and manipulate the data. Right now, the consumption, manipulation, and utilization of big data is for big or highly technical organizations. SMEs are still trying to wrap their heads around the Internet.
@Robert @Tony it may well be true that the kinds of activities described in the article have been done before to an extent using previous technologies. Big Data is not inherently superior for all data analysis, and especially might not be the right tool for a given job or for small and midsize companies. But it is generally far superior in performance when dealing with huge data sets where time sensitivity is of primary importance. There are other techniques to improve DB performance in general, like using SSDs and In Memory databases. But we should be careful to say that these different technologies are the same or just ‘old wine in new bottles’ (I hate that phrase, but can’t think of something better right now).
It’s like when some people said that Cloud Computing was the same as the old mainframe time sharing. It was easy for them to make the comparison in their minds by using familiar reference points, but the technologies are not similar…other than the part about not having to buy your own hardware.
So yes, Big Data may be hot, may be an overinflated sector even. But if you’re tired of hearing about the hype, don’t hate the player, hate the game.
To fully appreciate Big Data you need to understand that never before in the history of mankind have a billion people been able to create, curate, and access data in the same “web application” environment.
Big Data growth is driven by people – you, me, Aunt Betty – using Facebook, Twitter, LinkedIn, Google+, et al. Call it what you may, the fact is it never hurt to find, engage, and hug customers and prospects.
Finding your few customers in this vast ocean of data may prove difficult as @Joyce points out. But as @Gruber suggests this is new wine in new bottles simply because of the magnitude of sources.
If you don’t like the yin (dark side of data analysis), then as I’ve suggested above, engage the yang (light side of data magnetism) by enriching your data “honeypot” to give it more visibility when people seek your benefits.
Big Data is not the same thing as big data. The latter consists of massive curated datasets of past behavior, usually analyzed to identify potential sales patterns. Big Data is spread all over the web and is characterized by diversity of shape and nomenclature.
Big Data is useful when trying to find information that is relevant to a question and the technique for finding a direct answer is not known in advance. An example question for travel is “What is there to do in X (a city) on a Tuesday evening. I like popular music.”
Answering this question depends on practical linguistics – “what is there to do…” is a formulation that in the travel context restricts “the what” to types of entertainment. Once the question is understood, the answer is found by searching the web. Search engines do this, but have some difficulty understanding what a page on a site is about. Google and other engines are now quite sophisticated in looking at word profiles to determine the substantive content of a page. Extracting the fine details is still a challenge.
Semantic markup (in its various forms) was invented to help search engines make sense of the fine details of a page. Today, the search engine providers drive semantic markup toward sales of product. Thisshould not be a surprise given that the SEPs are funded by product advertisers. Travel and entertainment, as a business segment, have failed to drive the semantic markup agenda toward the fine details of the business and pleasure traveler.
One of the key components of this agenda is the establishment of common vocabulary for items of interest to travel providers, arrangers and customers. This will not happen without strong industry support.
Another key component is the creation of a shared semantic information base about offers, events and other information of interest to these stakeholders. At the moment, the industry seems willing to leave this to Google and its sisters, and so will continue to be at their mercy. This shared information base can be used by any travel industry participant with a website. Because its answers will be of better quality than those provided by Google et al., interested parties (travelers and business partners) will find their way to these sites. Once there, the answers naturally lead to bookings.
One massive issue no-one seems to have mentioned in the Tnooz discussion on Big Data is consumer privacy. Big Data is not all good. Many consumers will like the feeling they are being tracked and their privacy potentially being compromised.
sorry what I meant of course is that many consumers will NOT like the feeling they are being tracked etc…
Perhaps we should get the new EU cookie law out of the way first, in Europe, before we worry about big data (or, apprarently Big Data – which is different I’m told)