The ability to effectively analyse data can be the difference between success and failure for a business. Collecting data is one thing, but if insights aren’t being gathered and applied to make positive business transformation then its largely meaningless.
Its therefore no surprise that we’re seeing more and more chief data officers (CDOs) featuring on executive boards as businesses of all sizes see that being data-driven is key to becoming a digital business.
As part of this, enterprises recognise they require a coherent data analytics strategy in order to reach the full potential of what they can do with data. But what’s essential is that they don’t fall into the trap of fixating on whether their deployment model should be cloud, on-premises or a hybrid approach as the first step. Infrastructure decisions are important, but they are just one factor to consider.
Developing a clear data strategy and data-driven culture led by CDO has to come first, as this avoids a disjointed approach to data and prevents employees feeling disillusionment or distrust in business processes.
In fact, people should be at the heart of every data strategy because the most powerful results happen when the whole organisation is involved in driving the strategy forward. Furthermore, the most successful strategies are those which are integrated and communicated from the beginning as part of a business’ overall strategy. This step makes sure data is being managed and used as an asset, with business-wide processes, practices, and common and repeatable methods.
Making data accessible
With common practices in place, employees at every level can have access to real-time data and know how to use data to make faster and better decisions – which potentially open up new business possibilities. Democratising data in this way empowers employees with relevant, customised, up-to-date analytics on key metrics, which involves and empowers them in moving the business forward.
And here is where the technology infrastructure comes back into play. Anything that thwarts an organisation’s ability to become data-driven needs to be reconsidered. Businesses can’t let their infrastructure stand in the way of data democratisation.
When we surveyed 2,000 global data decision makers in our recent report, Data strategy and culture: paving the way to the cloud, it revealed that 81% of businesses with hybrid cloud models found employees at all levels had sufficient access to data to improve decision making. For many this is because a cloud model allows data to be shared at scale, eliminates data silos, and is secure and cost-effective.
Analysing the cloud
However, it’s not that simple if we take a closer look at the results. For some organisations, it is difficult to make data accessible across the business. When we asked respondents if their current IT infrastructure makes it challenging to democratise data in their organisation four out of five agreed. Barriers to success also included too many sources of data (25%), a lack of relevant data skills (24%) and performance limitations (21%).
This is concerning. We’re all operating in a real-time world where we’re amassing data at breakneck speeds, which makes fast data analysis even more paramount. Limitations such as incumbent systems, poor technology infrastructure and a lack of employee buy-in can’t stay unaddressed. Business leaders need to tackle accessibility, integration and employee knowledge challenges now in order to compete. And with a robust data strategy in place as step one, the important decision of what deployment model comes next – to ensure your infrastructure doesn’t hold you back from making data available across the business.
This doesn’t necessarily mean that you need to run straight to a cloud solution though, as it might not be the right choice for every workload. It can be an instrumental part of an effective data strategy, but your decision needs to centre on how the business will evolve in the future and what requirements there might be that may mean some data needs to stay on-premises.
In the highly regulated financial services sector for example, an on-premises approach can work better. Whereas if you have predictive/prescriptive analytics and data science workloads or need to speed up the adoption of software and services, you would be better suited to the cloud.
Some of the benefits of the cloud include improved ease of access and shareability of data, and faster query/response times. 73% of decision makers in our survey that have migrated data workloads to the cloud have seen a positive impact regarding what they can do with their data.
Ingredients for success
Ultimately, the deployment model an organisation chooses needs to enable every worker across the business to access the insights they need in real-time. In my experience a hybrid cloud approach can really deliver on this objective; sensitive workloads can be kept on-premises and public cloud offerings can be used to manage less crucial information.
As a result, greater agility is achieved, enabling firms to not only quickly adapt as their business evolves, but also turn their data into value faster than ever before with the speed and performance hybrid brings. Get your data strategy in place now and then pave the way to the cloud!