Mark Flaherty: Now, are we dealing with unstructured data as the input source or is it more traditional structured data? Yes and no. We typically work with more traditional structured data. However, we have a lot of customers doing very inventive things with unstructured data and doing some translation on it to get it into a structured data format, but for example, doing fraud analysis across emails and other unstructured data things like that.
And they will use InetSoft to do analysis on, for example, that frequency of words and different emails and the frequency of sending the emails. So traditional structured data, but there is a huge opportunity to use unstructured data as well. We are hearing a lot about Hadoop and of course, before that we heard a lot about MapReduce, but Hadoop in particular is a very effective means for gleaning value from unstructured data.
But there is a bit of a process that you have to work around. It’s not quite a straightforward as with traditional data warehousing. The Hadoop Technology (when it kind of entered the market a while back) created an awful lot of buzz and it has really great capabilities, but with that said working with the Hadoop open-source stack, it can be somewhat complicated it’s not quite as easy as advertised
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. And when you get vendors like InetSoft and others that have created ways to speak Hadoop stack and access that Big Data, they are really kind of solving some of the problems for you. And it’s certainly a trend that I have seen in the space that more and more of the innovative vendors are addressing the Hadoop stack in a way that’s kind of eliminating some of these scarier skill sets that might be required to get out that information and making it a lot simpler to utilize.
I think Hadoop is a great piece of technology, I think that works extra well when coupled with other technologies that are helping adapt and utilize the powers that be within the technology stack. And as you mentioned the MapReduce abilities that come with the Hadoop stack certainly make things move faster over semi and unstructured data in the stack, it’s just a matter of finding ways to access the information on InetSoft and others are doing good work there.
In terms of security, is InetSoft actually leveraging the security features within other applications like databases or BI tools. We do have a server product which allows you to collaborate with others and security is enforced across the desktop and the server product. And the way it’s enforced is in a couple of ways. We enforced data security that exists at the database level. So if you have limited certain people from seeing certain regions or certain product types they won't be able to see that in InetSoft either. We also integrate with Active Directory and for security that way. And then finally there is a layer of security in InetSoft where you can make certain workbooks viewable to a certain people. So again some customers want work some way, some want to work another and we want to be flexible to that.
The term “Business Discovery” is being used a lot more these days with some of these tools, and unlike, perhaps, some of the monitors that get thrown around. I feel like there is a real good reason why we have that specific category or term because we have had data visualization software for a long time, that people have been able to play around with visualizations and try to recognize patterns, of course that’s what data mining is really all about. But this concept of Business Discovery really winds up dealing with a lot different kinds of data that we have in the traditional BI world, in part because of how much work it takes to move something through the data warehouse enrolled into OLAP etc.