How can startups make the most of big data?

When people are talking about big data analytics, there's often an assumption that the technology is only for large, established organisations that already have a huge pool of information from which to draw upon and can afford to dedicate large resources to building an effective solution.

However, this is not necessarily the case. Even small startups can take advantage of big data to compete with larger competitors, and if successful, this can lead to rapid growth. In an article for Entrepreneur, John Kelly, managing director at Berkeley Research Group, noted that in some cases innovative use of data can transform an entire industry.

As an example, he highlighted ride-sharing app Uber, which since being founded in 2009, has grown to be worth an estimated $50 billion. It has built this on the back of regression analysis, which determines which neighborhoods will be the busiest and activates 'surge pricing' to get more drivers on the road. As well as using data as a competitive advantage, it has also turned its information into a product by agreeing to sell details of its customers' travel patterns.

Of course, this disruption hasn't been without its controversy, with the established taxi industry mounting challenges to its business model in jurisdictions around the world. And while not every start-up will reach Uber's heights, there are a few ways new businesses can take advantage of their data to both gain insight into their sector and create a new source of revenue.

"Even if startups aren't interested in turning data into a product, they need to use these insights as a competitive advantage," Mr Kelly said. "If they don't, they'll be operating on guesswork while competitors follow the evidence."

He added that many small businesses express concerns about the cost and complexity of setting up big data operations. While he stated that the human element is typically an unavoidable expense, many of the costs related to the infrastructure can be solved by turning to cloud computing solutions, where businesses can secure the exact server resources they need.

Businesses also need to think about how they make their data actionable – and the best way to do this is with strong visualisation. Being able to do this can help users understand data and provide a more "emotional appeal" that makes the information more persuasive.

However, one of the most important steps to making a big data strategy a success is to understand what data needs to be a part of this, and how it relates to the wider business.

Mr Kelly said companies need to ask which insights will have a direct impact on their customers' daily actions, as well as how that information will be gathered. He said: "Will it be structured so it can be analysed immediately, or does it need to be cleaned? Data is nothing without context, so entrepreneurs must translate it so it makes sense to their customers."