The race to data-driven business is, arguably, really only on its first lap i.e. we are now building intelligent IT stacks to drive software architectures that will power data-driven applications and analytics services… but we need to get ready for the long haul.
To carry the motor-racing analogy forward (if this is the first lap), then we need to think about how we are going to operate in the intensity of the 24-hour race that lies ahead. Whether you are a fan of Nascar or Formula 1, the concepts are the same. The data-driven road ahead has obstacles, chicanes, tight turns and the competition is going to be breathing down our necks the whole time.
Racetrack rationalisation
Let’s stay behind the wheel for a while. As the speed of data gathers, it’s important to be able to divide the known-knowns, the known-unknowns and the unknown-unknowns. There are some common behavioural elements that specific data flows will exhibit in regularly occurring applications and services. In Nascar, we only turn left, so keeping that core knowledge of direction front of mind is important.
We also know the degree of racetrack banking, the length of straight-way and the average speed of most of the vehicles around us. Data-driven applications and services also exhibit similar commonalities. What’s harder to predict is the way the car (or data) will react to real time elements such as temperature, humidity and the exact nature of the competition on any given day. Being able to work with those more random factors and navigate in an agile way around fast-moving oncoming obstacles is as key on the racetrack as it is up and down the server stack.
But just as there are no totally safe bets at the racetrack, there are unique elements of business operation that will be unique to every organisation.
As organisations get out on their first lap and embrace their forward development path with a data-centric infrastructure, they can quickly gather speed and look to start performing some moves to overtake others around them.
AI for users… and inside IT systems
Looking forward, we need to embrace a mix of next-generation data management that encompasses smart use of Artificial Intelligence (AI). We will need to remember that AI doesn’t just ‘surface itself’ in smart application functions built by developers, it also has an important role to play in automating key data management development and operations activities.
What do we mean by next-generation data management? Well, just like you wouldn’t put cheap low-grade fuel into a racing car, you wouldn’t (or shouldn’t put) poor quality information into a data-centric mission-critical business process or workflow in a high-performance organisation. Data quality matters more now than at any time in the past.
Data innovation continues to develop at a rapid pace throughout the industry by those of us who believe in the power of intelligent enterprise information management.
All truly successful businesses have a driver, a leader and a figurehead (although in the real world where we recognise meritocracy properly that could be more than one person)... and in every case there will also be a supporting pit crew with access to all the right tools and safety equipment.
Driving with a web-scale mindset
The question of scale is also vitally important here. The data-driven business has to operate with a ‘web-scale’ mindset from the get-go. What we mean is, if one single business process takes a defined number of processor cores, analytics functions, storage requirements and input/output channels, we need to remember that that’s just today.
If that same single business process needs to be scaled for significant (perhaps sudden) disruptive opportunities and business growth, then we have to be ready to move upwards and be web-scale i.e. as wide and expansive and interconnected as the web itself.
Winning the race to data-driven business success is all about knowing the racetrack and the nature of all the environmental factors around you, but ultimately, the race comes down to the engine and the skill with which it is handled. In the world of IT, that means making sure you run on a scalable and flexible data management infrastructure.
