Hello, we are Juxt.io – a startup building Data Analysis software for Business Users. I’m Panch, one of the founders. My co-founder Ram, and I built Juxt in response to the repeated challenges and frustrations we experienced in our past jobs, trying to derive insights from available data at our companies and actually apply them in making business decisions.
Currently, Business Data Analysis tools fall into one of two extreme camps. In one camp, the tools are severely feature-constrained in the name of ease-of-use. This often leaves the user with limited freedom of expression. On the other hand, the tools make no sacrifices in power or performance, but expect the users to be software engineers to even get started.
Neither of these approaches addresses the needs of savvy business users who seek something more expressive than Excel without having to get a CS degree.
In one of my previous roles as a Product Line Manager, I found myself in this predicament. My company collected a great deal of interesting data from various information sources and I wanted to get my hands on this data to, say, build a forecast model or play with some what-if scenarios. But, whenever I started to build anything I ran into all manners of technical issues. The data wasn’t in an appropriate format, or was too large or split across multiple sources, behind API walls and so on. Invariably, I had to seek the help of someone from IT or a developer to get things going. These attempts would usually play out along the following lines:
- I’d write up an informal spec for what I was trying to do
- The IT/dev person would interpret that and code it up, if I could get their time, and that’s a big if
- They run the code, collect the results, and I’d review it
- Sometimes, there’d be bugs that would need fixing, or the data would be incomplete, or I’d discover something new that I’d want to extract.
… whatever the reason, I’d have to go back to Step 1, rinse and repeat. Answering even the simplest questions would take days or weeks, and tight schedules would force me to abandon the data backed approach, and resort to other sub-optimal options.
Perhaps, this scenario is familiar to you as well. It certainly was to a number of my peers.
Ram who is on the developer side of the equation had the mirror image of the problem – too many business guys asking him and his team to run reports etc. He couldn’t understand why the business folks didn’t just tweak a few lines of code since most reporting requests were just slightly different versions of the same problem.
At some point, Ram and I were commiserating over the challenges at respective jobs, and it occurred to us that this was a real problem to be solved. This needed a solution that was easy to use for the business guys, who could apply their domain expertise to drive data rather than rely on IT for everything. The IT guys can then focus their energies on cooler problems rather than run reports all the time.
So our approach to solving this problem was to create a visual representation of data processes with the technology hidden underneath. Now, one can build rather sophisticated data apps with a business process perspective without a technology dependency.
Our interactive data workbench enables business users to integrate diverse data sources & online APIs, apply Business Intelligence & Machine Learning algorithms, with a drag, drop & configure UX.
Over the next few blog posts we’ll cover a number of popular data analysis use-cases and demonstrate the advantages of our interactive data workbench. Using Juxt, business users will be able to easily crunch complex datasets without having to write any code.