Analytics is not just a game for big businesses. It just happens that bigger businesses have traditionally created, stored and managed big data repositories.
Some organisations have gotten to grips with their data resources in a spectacular fashion.
There are businesses, like well-known, long-established manufacturing giants who
practically went to bed one night the manufacturers they always were, and woke up holders of big data. One great example of this is Ford Motor Company, and you can read about their journey toward digital transformation here. Such businesses have the great fortune to look back on customer and product data stretching back many years, and then to mine that using new big data and analytic tools.
In fact, just as all big manufacturers are now big data companies, most organisations, whether big or small, have found that they too, whatever their industry, and whether big or small, have untapped data, and as such, hold the potential to compete on analytical insights.
In fact, one of the top ten largest employers in the world uses the Alteryx analytic platform to help manage its 2.5 million employees, and help them run ethics and compliance investigations – as well as legal audits.
Not just for big business – the cloud equalises opportunity
But analytics is not just a game for big businesses – far from it. It just happens that bigger businesses have traditionally created, stored and managed big data repositories.
As now cost effective and very accessible cloud services have become well established, it becomes a much simpler task for a business to gather and analyse big data, even without a large, skilled IT team to help bring an organisation’s data to light.
This holds true even where there are no data scientists or quantitative analysts in the team. Most businesses don’t have them anyway – but they do have analysts in the ‘line of business’ who know the business problems the best. These are simply the people within the business who already use data within their daily roles, but don’t necessarily have advanced data/statistical, or programming skills – or are even necessarily Microsoft Excel power users.
They are the people who often have to dig deep in order to get their tasks at hand done – they want more information, they need to use what they already have more effectively, and they need ways of extracting insights that they may not have ever had any kind of training for.
This is where access to cloud-based solutions are making a mark. Designed for a new type of user, and for the speed of modern business, they enable fast and easy set-up, collaboration and management.
With cloud infrastructure such as provided by Amazon Web Services or Microsoft Azure, it’s possible to offload the storage tasks of a big data project to a reliable and always-ready platform that meets IT’s need for control, but doesn’t require them to actively manage the processes involved.
Many cloud services providers are geared to allow the deployment of pre-configured analytics solutions from a preferred supplier as on-demand, pay-as-you-go options that don’t need any physical infrastructure within the corporate environment. It can turn the IT team into a provider of oversight and experience rather than the project deliverers needing to run at the enthusiastic pace of new data analytic converts.
Some cloud services even allow a customer to spin up computing resources to install a server virtually using the existing server licenses that the business holds. Using a cloud service in this way generally saves days – if not weeks – of work for in-house IT staff by removing the need for any in-house hardware and maintenance.
Kicking off a data project using the cloud
So, what will organisations find if they are just starting their data exploration projects?
For a start, whilst it’s easy for the passionate business adopters to drive forward with incredible speed, experience shows that if they work collaboratively with their IT department sooner rather than later they see greater success. Those line of business analysts (and bear in mind their role and title may not have ‘analyst’ within them) would do well to run a small trial, gain a success, and then present a business case to enable a wider roll-out in the business in partnership with IT – not despite them – even though self-service analytics tools are exploding in use.
In some ways it is up to those analytically minded workers to help their IT team, or their CIO, see that liberating the organisation’s data to generate faster, better business insights is not scary – it’s efficient and it’s a driver of marginal values as impact is made and ROI proved.
Discovering how small scale uses and pilot analytics projects can scale will be crucial to showing how the wider business can expect to manage bigger rollouts, in-line with compliance regulations, and in-line with business priorities and budgets.
Business users making use of cloud-delivered services can browse the apps they have permission to run, and customize and execute workflows on demand, without interrupting a data analyst who may have originally created it, and without IT support, saving time and effort. For a business looking to leverage their data assets to empower analysts and business users to more easily consume data and make more informed business decisions, the cloud makes project delivery an enticing option.
The goal is to enable the business to become a modern data management company – whether they make use of cloud or on-premises data cataloguing systems and analytic platforms – in order to execute every departmental need quickly, with access to the facts and insights that means they are as well-armed as possible to meet the needs to the competitive environment in front of them.