How to avoid the pitfalls of big data discovery and 'visualise responsibly'

Consider the limitations of data discovery tools

The business intelligence (BI) and analytics market continues to evolve rapidly under the influence of the world's love affair with data. On one hand, there are increased volumes of structured and unstructured data – big data. On the other, there is keen interest from individuals wanting to easily analyse their own data and for businesses to have a single view of this data deluge, across the enterprise.

As a result, organisations are seeking new ways to leverage information to satisfy the growing demand for accurate, smart decision making to improve the bottom line.

Visualise responsibly

A new crop of data discovery and visualisation tools have emerged to address this need.

Visualisation can make information easier to interpret, understand, and retain. When raw data is depicted through pictures, images, and graphics, it becomes much easier to recognise patterns, dependencies, anomalies and more.

What's more, they're unlike the many traditional BI solutions available to businesses – often these are slow, antiquated and complex. Data discovery promises to free business users from the chains of IT reliance.

Think before you buy

However, before rushing off to make an impulse purchase of a standalone data discovery solution, businesses need to consider this: even though they may seem exciting and novel, data discovery tools only address the information needs of a limited number of users and, in some instances, may actually do more harm than good.

Any business considering data discovery needs to "visualise responsibly". This involves weighing up the pitfalls and limitations of a data discovery tool in order to ensure that they're generating accurate insights with it.

Before diving straight into one of these tools, there are some key questions that businesses need to ask themselves.

1. Can you empower all decision-makers, not just a select few?

Visualisation needs to be part of a fast and flexible BI platform so that businesses can go beyond the limited capabilities and data quality issues of a niche solution, and serve the diverse information needs of enterprise users, partners, suppliers, and customers.

If a business's goal is to maximise the return on investment (ROI) from enterprise information by enabling more people to benefit from it, then typical data discovery tools may not be the right approach. Those tools have limited usability, don't scale easily and can't satisfy operational demands for real-time information.

Current data discovery tools may hinder BI adoption because they satisfy only a small percentage of the user base. Although they allow some more advanced users, like analysts, to perform deep data analysis, they can be too difficult for the typical business user – or, even more concerning – too easy for them to get wrong.

Professional analysts will always want advanced tools, but what about the next wave of thinking professionals like the millennial workforce? Do pilots and surgeons analyse information in Excel when they need to make split-second decisions? Or do they simply glance at equipment consoles to assess the status of current conditions? Like most business professionals, these decision-makers need simple-to-use apps.

To make access to data readily available in the enterprise, users of all types and skill levels should be able to explore and analyse data in the way they're most comfortable. For example, businesses should recognise that generally non-technical business users want simple apps to explore and analyse their data, whereas analysts need easy-to-use, powerful visualisation tools.

To generate the best possible results for an organisation, BI should work on three interconnected levels: strategic, analytic, and operational. Strategic analysis drives analytical BI, which directs the focus of operational initiatives. Operational BI facilitates the kind of day-to-day decision-making that happens at the lower levels of an organisation – the scores of employees on the front lines, on the shop floor, in the delivery van, on the sales team and in the call centre. Operational BI can directly impact a company's ability to reach objectives, such as increased sales or greater profitability.