Mash-ups are not just for consumers anymore. Businesses are getting in on the act and deriving value from their BI solutions they never anticipated.
While it is undoubtedly one of the most clichéd terms in the IT industry today, Web 2.0 has intrinsically changed the way businesses trade, interact and develop their competitive advantage.
One example of this is prevalent in the business intelligence (BI) space, where ‘mash-ups’ are beginning to challenge the status quo.
A mash-up is for all intents and purposes an integrated, often web-based tool that combines data from more than one source to shed light on a topic, add value or represent a completely different view of the data to the one that would be evident by viewing data sources in isolation.
Like most of the Web 2.0 concepts that have made their way into the business space, mash-ups were originally developed to serve the purposes of the consumer.
A common example of one of the most-used mash-ups available online today is the combining of digital photographs that are geo-coded with a mapping service such as Google maps.
The resulting tool represents the photographs in an entirely new way, namely showing a map with pushpins inserted at the locations the photographs were taken.
Mash-ups for business
The concept has however been extended in the couple of years it has been out in the wild and today, companies are beginning to look at ways they can mash their own data sources up so that an entirely new and meaningful view of that data can be created.
But the concept can be extended even further if one considers that in their original form, mash-ups were designed to draw on data sources that were in the public domain.
By mashing their internal, confidential information up with information that is in the public domain, businesses are beginning to realise they can derive additional value, above that revealed by their BI systems, from integrating their data with others’ information.
Suppose a catering supply company’s BI system tells them that in the past, sales of their goods doubled whenever the local cricket team played at home after a winning streak.
Unless the company can get extra stock to the relevant stadium in time for the right game, they are not likely to make any more money than what they did before.
And since the company is not really all that likely to store cricket teams’ results on their intranet or in their business system, they are unlikely to derive meaningful information about where demand is likely to spike, unless they look outside of the safe confines of their corporate business systems.
Luckily there are plenty of places on-line where cricket scores, game schedules and team logs are available.
There are, furthermore, plenty of shipping companies that publish their schedules, routes, prices and availability on-line.
While the BI system on its own might be able to predict a spike in demand based on historical data, or if it is really smart, take into account teams’ scores, it stops just short of making those findings easily actionable.
If the BI system’s findings are mashed-up with external data sources however, suddenly the findings become quickly actionable. Not only will the company be able to predict a spike in demand, they will in all likelihood be able to gauge where that demand is likely to be located and, here is the kicker, how much it will cost the company to take advantage of that increase in demand, versus what the increase in revenue will be.
Cheaper than you think
Mark Whitehorn, a UK-based consultant for a number of national and international companies and columnist for SearchDataManagement.com calls these business mash-up solutions ‘bash-ups’ and through personal experience believes they can be implemented on the tiniest of budgets.
Having recently implemented such a project, Whitehorn says, his solution was completed in five developer days using an already operational BI system, one database programmer and one web programmer.
The programmers created a web service to extract the data from the database, the necessary stored procedures and views on the database, and the ‘bash-up’ that sent the data to Google Earth and displayed the result.
“The Web service and the ‘bash-up’ were each about 75 lines of code, much of which was cut, pasted and modified from existing code,” Whitehorn says.
“It was working within two days – the other three were for testing and tweaking.
“So how much that actually costs will depend on what you pay your developers – but whatever that is, we are still talking about a trivial investment for a major analytical improvement,” he says.
In Whitehorn’s opinion data mash-ups combined with business intelligence are here to stay.
“Have these bash-ups reached their full potential? We have barely scraped the surface,” he says.
“But do not sit back and watch this space – think laterally, do some bashing, and grab some real competitive advantage while it is going,” he adds.
And he is right – in a technology world where competitive advantage is becoming more and more difficult to come by, opportunities like this should not be passed up on.