By James Eiloart, VP EMEA, Tableau Software

Businesses have access to more data than ever, collectively generating 2.5 billion gigabytes of information per day globally. Organisations are drowning in a deluge of data from email, research, website analytics, infrastructure logs, sensors, and numerous other sources. But this data is only valuable to a business when it can be used to inform decision making.

In rapidly evolving markets, where high-pressure decisions have to be made almost instantly, one of the strongest weapons in the corporate arsenal is data analytics.

This is why business intelligence has taken on new importance in the corporate agenda in companies of all sizes. Traditionally, the business intelligence industry was built primarily to serve large firms that could afford a full suite of software and large teams of number-crunching analysts. Since then, the industry has evolved, technology has improved, and software has become more agile, nimble, and powerful. What this means is that business intelligence solutions are not just accessible to large enterprises and multi-nationals, but also to small and medium-sized businesses. Companies already have access to the data they need to solve business problems, but managers simply don’t know the most effective way to use this information when confronted with a huge spreadsheet or database and no context.

A new suite of software capitalises on “the visual”, turning data into aesthetically stunning graphical representations so business users can instantly identify trends and share reports that their colleagues can make sense of. If any of the variables are tweaked, the entire visualisation adapts, making it easier for people to make connections and draw conclusions based on what the raw data is telling them, in real time.

These visual data discovery tools are expected to grow 2.5 times faster than rest of the business intelligence market, according to IDC’s most recent prediction. Just as the industry noted the quick adoption of DIY data collection in recent years, we are now seeing the development of self-service data exploration, analysis, and visualisation products. Self-service business intelligence offers a customisable way to extend the depth and reach of analysis, while also creating a decision-making environment for everyone on staff. And being self-service, the products are much more accessible to firms lacking an analytics department staffed by statisticians.

Smaller businesses are agile by definition, having to bob and weave within their respective industries. With data visualisation, firms can find quick answers to simple questions that help mould business decisions that work. For instance, Shopitize, a UK-based direct-to-consumer mobile promotional platform, started off as a robust, tight-knit small business. Using the Shopitize mobile app, shoppers browse the offers and scan the product barcode in-store. Once the receipt is uploaded to the Shopitize app, shoppers receive cash rewards directly to their bank account. This real-time view of consumers’ shopping baskets is used by Shopitize’s brand partners to optimise campaigns in real-time and increase marketing return on investment.

Understandably, it took Shopitize a significant amount of time to make sense of this large-scale and complex retail data.

They turned to interactive visualisations to make the most of data, creating detailed reports on consumer buying habits across the six major UK supermarkets—all based on the original shopping receipts. The intelligence about what customers are buying, when and alongside which other products is all wrapped up in a visual, easy to understand format, and is used by brand owners to improve key areas such as marketing spend and stock levels.

Small and medium sized businesses rely on efficient time and resource management, and visual data discovery to deliver just that: from allowing employees instant access to the information they need, to cutting down red tape around otherwise straightforward operational decisions. It’s easier for business users to digest and react to data when they see it mapped out visually. With the right tools, anyone, at any level of a business can play with data and draw their own business conclusions from it, without having to undergo years of training. This is crucial, as the onus for accountability and performance increasingly lies on every employee across the business - not just those with “analyst” in their titles.

More often than not, the IT department is a one-man show in smaller firms, and by encouraging all employees to make evidence-based decisions centred on their own analysis of the company’s data, the IT staff can be left to optimise business-critical operations. Similarly, C-suite executives can have instant access to the functions and output of deployed projects on hand for when they need to take stock of performance. Employees can pitch ways to tackle issues that would have otherwise remained in the boardroom. This self-service approach to data analytics empowers everyone to drive their organisations forward from the bottom up, and is open to all sizes of business who appreciate making data-informed decisions.