Birst’s core strategy focuses on being a seller of ‘networked BI’ in the cloud – the idea being that most enterprises have little, or no, insight into the data across their entire organisation. Companies build data silos in an attempt to get some structure, but ultimately they’re still silos, which either sit in multiple systems, data warehouses or on users’ desktops. As a product, think of Birst as a fabric that sits on top of all these silos, tapping into them and linking them all together to provide predictive insights. Sitting down with Birst’s VP of product strategy, Southard Jones, in San Francisco this week, he said: You want to solve a use case problem, like address the way that purchasing happens across a 78 country company that’s highly decentralised, across 29 ERPs. That’s not a desktop discovery tool. That’s an analytics solution. It’s great to have a discovery tool that can give an end user a faster, beautiful way to answer questions on a spreadsheet. But to address and create value for the organisation and to deliver millions of dollar of value, we need a platform that’s going to address a larger problem. And IT and business are both going to team together to make that purchasing decision. Jones believes that although enterprises are interested in the latest data technologies, such as #Hadoop and #AI, ultimately they’re more interested in fixing the fundamentals of their data structures. He argues – and I tend to agree with him – that companies seek relief from just getting some governance in place, and getting a better understanding of their entire data portfolio. AI and Hadoop are nice to have, but ultimately they can’t do a great deal if you don’t even know what data sits where. Jones said: Birst was built on delivering automated machine learning capabilities. So, under the covers, we had this already. What we are hearing is that companies want a pragmatic approach to enable those end users, who are operational in nature, to leverage the intelligence of machines and AI. I wouldn’t say it’s the number one thing they’re asking for though. We talk about it, but the chief purchasing officer, for example, says ‘that’s great, that’s nice, I want to do that some day’. ‘But let me at least understand how many purchases, by supplier, in all countries, across all ERPs, are happening on a daily basis. I will be ecstatic if I can get that’. That’s a hard problem for me to solve. After you solve that problem, yeah let’s talk about this AI stuff. Let’s not get the cart before the horse.
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