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Consumerisation and Application Development

F.Y. Teng | July 12, 2012
The impact of consumerisation on IS organisations and analytics.

The other aspect of consumerisation or consumer behaviour is the emphasis on apps, and being able to have small and specific applications to solve your problems. Those you can just go download and work with very, very quickly. That is a very different approach to software. Previously with software, there was an acquisition. Even if there was a person buying software, he would have to choose the application carefully. It would probably cost a lot of money to buy an application, and take time to learn to use, especially so if you wanted to use all its features. Nowadays, you go to the App Store to download something-it could cost you anything from nothing, it's free, to just a few dollars-and you expect to be able to use it within minutes. Imagine if you downloaded an app and then had to go for a training course to use it. An app that needs a training course-that doesn't make sense.

That's what we make sure to avoid. We don't have training courses for our apps. We have training courses for the developers, yes. But the business user who just browses the QlikView app, he doesn't need training to use it.

Real-time analytics. I'm sure you've heard that expression. What does it mean to you?
It means a lot of questions because what is real-time? If I have any customer that talks to me about real-time, it raises a lot of questions from me. What do you mean by real-time? I don't know what you mean but every customer is going to have a different answer. You have to make a distinction between two types of analytics or intelligence when you talk about real-time. There is streaming analytics-analytics over data that is constantly pouring out of some system and the importance is to analyse the stream-or there is very fast analytics, where every time you query or update the analytics, you're actually updating or looking at an entire data centre.

The reason why those two things are different is first, I have to ask the customers, "What happens when your network cable gets pulled out by accident or your network goes down or the Internet connection is not working? What do you want to happen? What happens about the data that is no longer streamed?"

If the answer is, "Well I will have to be able to pick it up again, and be able to go back in time and recalculate that stream and catch up with all that streaming data." Then that's one type of real-time analytics, because I have to be able to handle the fact that the streaming breaks.

If on the other hand they say. "It's okay because the next time I do a query it will just catch up with that data, then that's a different kind of real-time analytics." Then my response would be, "So is it a stream or is it fast queries? If it's fast queries, we do that very, very well and people can use QlikView in those environments quite successfully. But if it's streaming, that's a specialised area which is probably better handled by CEP [Complex Event Processing] and applications or by some of the highly specialised streaming analytics products that are out there." We have a partner that does a lot of work in financial services and they are present here in Singapore. They have some customers here. They integrate with us quite successfully.  They provide streaming analytics, and so we can refer them to our customers if the need arises. We are quite happy with real-time analytics questions. However, our initial response is often more questions than answers.

 

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