While the frequently proposed model of volume, velocity, and variety has been well publicised, to harness the potential of big data, businesses must understand the challenges that come with both collecting and analysing it.
The CIO/CDO, as the chief orchestrator behind its adoption, must assess the current organisational capabilities to determine where the gaps are and whether they are ready to start the adoption as well as ensuring a uniform approach across the entire organisation to ensure alignment.
In today’s digital age, having huge volumes of data is hardly a rarity. The boom in smartphones ensures that companies can gather more data on consumers than ever before while the rise of the Internet of Things is only adding to this on a daily basis.
Looking ahead, businesses will have even more information on customers as they begin to use one-on-one messaging channels to interact directly with them.
This is throwing up game changing evolutions in the fields of healthcare, scientific research, agriculture, logistics, urban design, energy, retailing and crime reduction to name just a few.
> See also: Machine learning set to unlock the power of big data
Yet, despite the huge strides made in the adoption of big data, much of the business and public sector world is still playing catch up. Many are only just waking up to the realisation that data is a valuable asset that needs simultaneously protecting and exploiting.
The fact is, data is not simply collected – it is manufactured. There are always questions about how businesses choose what to measure, how they measure it, where they get it from, who will do the analysis and what it adds to the bottom line.
How does a business even know it is ready for big data? Here are five areas to look at when considering big data adoption:
In almost all businesses today, technology is prevalent somewhere. That much is clear. However, when it comes to big data, in order to fully take advantage of what it can offer, a business must be able to integrate big data technologies to its existing infrastructure without compromising or overburdening legacy systems that were never built to manage such a workload.
This poses a further challenge. Namely, how to choose the right big data tools that can be integrated and build an architecture that is scalable and able to grow with the accelerating pace of emerging big data technologies? It is vital businesses have the capacity to grow alongside the volume and variety of data that is being process in order to to deliver meaningful insights.
Businesses looking at operational improvement should look no further.