A couple of weeks ago, our CEO Gary had a new heating system fitted, with the new tado° smart thermostat. It’s pretty impressive, carefully reducing the temperature to an optimal level as soon as the last person has left home and calculating how to pre-warm the home most efficiently for your return. It also monitors the weather and claims to cut overall heating costs by 31%. Even more interestingly, tado° announced earlier this year an open API. This got us thinking.
Our developers are not known for their ability to focus on the mundane when a new bit of kit is available in the office, so true to form a couple of them dropped what they were doing and started hunting the web for details on how to access the API. A little bit of fiddling about at the backend and they had it hooked up to DataPA OpenAnalytics. Now we can all keep an eye on the temperature of Gary’s house online and via the DataPA OpenAnalytics mobile app (take a look).
This is all very entertaining, but does illustrate a more useful point. The combination of IOT devices and analytics is set to change our world in many unexpected ways. An analytics tool like DataPA OpenAnalytics will quite happily accumulate data from these devices, display it in any imaginable format and on any device, and raise alerts should any interesting threshold be met. For Gary, he can keep track of his heating system, and receive an alert should the temperature reach a value that indicates an issue. With a few more IOT devices in the home, he could combine that with information on his fuel consumption and the cost of heating fuel. Surely this will offer opportunities to further improve the efficiency of heating his home, perhaps in months to come a few companies offering a monitoring and tuning service?
It’s clear these devices and modern analytics tools are opening up a world of opportunity for new innovation. Our errant developers have now been tasked with building an interface to make it simple for anyone to hook up DataPA OpenAnalytics to these devices and services without having to tinker with the back end. We can’t wait to see where this leads us.
If this is the first you’ve heard about DataPA OpenAnalytics, why not find out more at datapa.com.
Building an analytics platform is about more than extracting data from your business application, it also needs to be transformed into information that is meaningful for the user. This is traditionally part of the process of engineering your data warehouse, deciding what data marts are required and engineering some code to transform the raw data from the business application into these more meaningful data objects. It’s an expensive and difficult process, requiring significant engineering skill and knowledge and is almost impossible to get right first time.
While this approach does have advantages, and there will always be a place for data warehouses in analytics, they can be cumbersome, expensive and a real barrier to agility. It also ignores the fact that more often than not you have already built the logic to transform data, often multiple times, in the application itself. Take one of our biggest partners Infor. The distribution industry survives on margins, so flexibility on the calculation of pricing is paramount. That’s one of the reasons Infor’s distribution system is so popular, it has a hugely flexible pricing module. This means however calculating prices is complex, and requires the application of a significant amount of business logic. That logic has already been written of course, in a stable and robust ABL module that is called from reports and screens across the application. Surely then, our analytics solution should make it simple for us to just call that logic, not force us to re-engineer and maintain it on another platform elsewhere?
We think to achieve a really successful embedded analytics solution integration of business logic at the back end is essential. Not only does it improve agility and save time and effort, but also ensures both the business application and analytics platform show the same figures, calculated as they are by the same code. That’s why we’ve engineered DataPA OpenAnalytics to natively call any ABL business logic at the back end, by calling ABL functions to add calculated values, or going further and running ABL code to receive the entire dataset. We believe in empowering our partners to unlock the hugely valuable asset they have in their robust ABL logic. Allowing them to deliver beautiful, live intelligence when and where their customer needs it.
If you would like to find out more about our partner program, please get in touch.