An adaptive business needs adaptive information
First, we had data, then we had information, then we had big data… and not long after that, we witnessed the renaissance of artificial intelligence (AI) and its sister discipline of machine learning (ML).
The latest iterations of ML are promising to be able to learn so much from our ‘data footprints’ and ‘digital workflows’ that we will barely need to code software application logic anymore.
Instead, we will simply ‘expose’ datasets to ML and it will work out what we need from the apps on our desktops and smartphones.
ML-driven apps will do everything they’re supposed to and businesspeople will be able to mold the way their favorite software works through the use of low-code and no-code platforms. But this is not another low-code story; this is a tale of what happens next for information itself.
After all of those data and information flavors referenced at the start, we can now ready ourselves for the age of adaptive information.
As the emphasis in the software industry continues to shift from applications themselves towards the information ‘use cases’ those apps exist in, we will see IT move even more markedly towards assessing where information can be applied with business value and, conversely, where its very processing does not provide enough return on investment.
The age of adaptive information is all about knowing what data is supposed to go where, to do what, when and how. Typically, in a modern web-facing cloud-empowered business, we will see that different data-intensive applications have to perform different tasks.
Some data tasks will be focused on operational procedures, others will be forward-facing, and look to provide predictive intelligence… and yet other areas of data processing will be tasked with working in deeply machine intelligent roles such as data science.
Drowning in data
That’s a lot of different apps, with different data streams being carried around and transported by different data sets, in different data formats, supplied at different levels of verified, deduplicated and structured (as opposed to unstructured or semi-structured) preparedness. How on earth are we supposed to know which pieces of information should go where at any single moment in time?
The answer coming from the data management platform vendors is, relax, as Micky Blues Eyes (and most of the movie-based mafia cognoscenti) would say, ‘forget about it’.
Okay perhaps it’s not quite ‘forget about it’, but it’s certainly don’t worry about the complexity factor. Data management vendors are aware of the complexity of the underlying substrate that makes data DNA what it is and they are now working hard to try and make sure that data platforms are capable of solving multiple different use cases from the same platform.
Deep in the engine room
So how do these data platforms do what they do?
Internally, this is management software that has been built with intelligent algorithms and ML functions designed to make an appropriate level of system recommendations so that users themselves can be abstracted from the lower levels of complexity.
In terms of actual usage, technical staff will now able to take advantage of a data management layer that is ‘inherently adaptive’ to the underlying runtime infrastructure required by the different types of data-intensive applications a firm will want to run.
To put that in more straightforward terms with an automotive analogy, your organization’s software team will able to use changeable (multi-gearbox, if you will) software management engines that tune to the speed and topography (the underlying runtime infrastructure) that your apps need to run in.
To continue the analogy, adaptive information is more than just an all-purpose fuel that runs at any octane grade; it is all-purpose fuel that fits any engine size for any terrain because the data management platform is handling the freeway speeds and the off-road four-wheel drive demands as and when they come up.
There’s no quick fix here and you don’t simply plug these systems in and turn them on. Everything needs road testing and there’s going to be plenty of grease and dirt on the road to bringing adaptive information to the front line.
All that being said, we do have a map and pretty soon we’ll be in a self-driving vehicle, so get ready for what should be a smoother ride.