Why the evolution of data management requires us to remove fragmented thinking

There is a lot of puffery and conjecture around the impact of emerging technology, but one thing is true: data is – and will continue to be – the key to digital business.

Researcher IDC predicts that the global datasphere, which is the amount of information created, captured, or replicated, will grow from 33 Zettabytes (ZB) in 2018 to 175 ZB by 2025.

This never-ending process of information creation fuels digital business. IT departments and data scientists are charged with helping their companies to develop game-changing insight into customer demands, market opportunities and enterprise priorities.

Such is the level of demand for data that analyst Gartner says business leaders require an ever-increasing velocity and scale of analysis in terms of both processing information and providing access to innovation.

Yet recognizing that you need more data quickly is simply a starting point. Companies that really want to make the most of data both now and in the future will need to create a nuanced approach to data collection, analysis, and exploitation.

Breaking down the silos

While business leaders recognize the value of data, they do not necessarily appreciate how hard it is to analyze the right information at the right time. There is a lack of consideration about how information might be used by different people in different circumstances.

Gartner says too many business units undertake data or analytics projects individually. This isolated way of working means data resides in silos. Data is only prescribed for one purpose to a particular team, such as understanding regional sales figures.

That kind of data analysis has a valuable purpose. But what about if the business wants to delve deeper? What about if the finance team wants to compare those regional sales figures with other countries? What about if the marketing team wants to take that comparative regional breakdown and investigate how it can sell products via enticing deals?

If data is locked away in silos, then it is far too difficult to create deeper, cross-organization relationships. That inability to collaborate effectively hampers business growth. As data is the key to creating a competitive advantage, then the proliferation of information silos is a short-cut to failure.

Making data accessible for all that need it

The task now is for business leaders is to find a better route. Organizations that want to make the most of the ever-increasing amount of information need to restructure how they exploit knowledge. They must break down the walls between departments, so that data is accessible for anyone who needs it at any time.

Moving to that location is going to require a significant shift in mindset for most organizations. Right now, many employees fixate on their current challenge – they focus almost single-mindedly on how data can provide an answer to a single question at one point in time.

If they have an effective data-management policy, then they will also think about how this information is stored and backed-up. These considerations are critical for any organization that wants to use its information in a secure and governable manner.

Yet these considerations should also be seen as table stakes. Detailed international and local regulatory requirements, like the General Data Protection Regulation come with the risk of severe financial penalties, meaning every employee should manage data safely and securely as a matter of course. That’s an IT challenge to some degree, but a business process point too.

But what if you want to go deeper? What if you want to use that well-managed data to create cross-business collaborations that will gain your business a competitive advantage? Then the answer must be to focus on how data is recalled, presented, and contextualized, so that the insight you create is useful not just today but also tomorrow. It may even lead to businesses of the future having an analyst within their team, or someone able to be seconded to support a data first project. Whichever way, the data will be more greatly accessible at a function or team level, than before.

Creating deeper insight

Bear in mind that the sources of data will continue to increase. Researcher IDC says the emergence of the Internet of Things is already contributing to significant market growth in tech spending. Within five to ten years, new technologies such as robotics, artificial intelligence and virtual reality will expand to represent over 25% of IT spending.

With that growth in mind, now is the time to think about how your organization recalls, presents, and contextualizes its information. You will need to take data management to the next level of development – one where the cross-business insight you create is drawn from multiple structured and unstructured data sources.

The aim must be to create a unified approach to data where any verified user can refer to a single interface to access all enterprise information. Let us think back to our earlier example: through this interface, the marketer can easily pull together a cross-regional comparison of sales figures to understand how different products sell best in specific locations. Not only that, but they will also be able to draw on disparate sources of information – be that social media sentiment or wider industry trends – to work out why these sales figures are occurring and how the business might exploit these variations to drive new revenues.

In short, to achieve a higher level of data management prowess, you need to elevate the technology and process to a point where users do not even have to think about current protection considerations such as backup and recovery. This new approach creates a single and verifiable version of the truth where users have easy access to the data they need when they need it – and they create deeper and more valuable insight for the business and its customers. It might seem like a stretch for some right now, but in reality, defrag your mindset and your data, and you will achieve the data first vision you seek.

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