The first time we heard about this concept was in 2006 from Neal Ford. At that time the concept was new and developers were NOT comfortable with this. However, over the period what we have realized is that it is very subjective on how organizations and developers feel about polygot programming. At Intentwise we built our platform with the belief that to be successful you need to use the right tool for the task. The developers at intentwise comes with a strong background in building distributed scalable systems and have worked with peta bytes of data and have architected and built data platforms in the past.
What we have learnt is that to be successful you have to bring great people into the organization, who are open to using the right technology. So when you build a platform there are multiple things to consider, for instance we wrote about Web frameworks in our previous post. Now coming to the areas of data processing we can’t expect the same technologies to be used across the board. So we reviewed a bunch of things on what makes sense to leverage for our machine learning algorithms. JVM based technologies are an an obvious choice for lot of organizations. However, we felt that python with its lots of stats and algorithm support makes a lot more sense to leverage. The ecosystem around libraries and developers are pretty good. There were many choices but in the end we picked up python to help build all our core algorithms.
As you noticed within a span of 2 core areas we ended up with 2 completely different programming languages. This is the fundamental principle of Polygot programming. Some of the core issues raised by developers such as this is something which we feel are different for organizations and very situational. We feel that developers are always trying to learn new things and the geekiness comes in when they can do something new in a totally different platform. This is a very important aspect of Polygot programming that we leverage to build our foundation.
I have barely scratched the surface of things that we do at Intentwise. We are very excited to leverage a lot of technologies which solve real problems for our customers.
At Intentwise, we provide SAAS software that helps with AMS Reporting, AMS Analytics, and AMS recommendations based on our machine learning based recommendation engine. The Intentwise tool will help maximize your PPC returns while optimizing spend. If you are interested in trying out the tool that supports Amazon’s AMS automation, schedule a Demo now!