In this briefing, four of our experts offer Big Data Analytics Strategies for entrepreneurs and the mid market.

Enterprise has been focussed on Advanced Data Analytics has been around for a few years now. In the networked, digital world, ‘Big data’ refers to data sets whose size is beyond the ability of commonly used software tools to capture, manage, and process within a reasonable time. Big data analytics strategies help business unearth treasure by combining their usual structured data with the invaluable insights available in unstructured data… e.g. from social media, call logs, customer records, meeting notes, maintenance reports, news articles etc.

Four Big Data Analytics Strategies

1. Use it for personalised services: Dr Stephanie Hussels, Lecturer in Entrepreneurship at Cranfield University believes that entrepreneurs are really smart about using big data. They can analyse customer profiles from it and tailor products and services. But she says there needs to be process in place to stop the data becoming overwhelming.

2. Embrace artificial intelligence: Pauf Hofmann of SAP Labs argues that there can never be too much data. There is a unique opportunity to take data and make sense of it and create more value from it. He say’s Artificial intelligence can help with this and therefore could soon become as commonplace as television.

3. Make it relevant:  Nigel Huddleston, Industry Head for Travel at Google thinks the key to big data analytics strategies is finding an intelligent way to make the information relevant. It is very important to the hospitality industry who are trying to bring data from different sources together and track in it a meaningful way.

4. Prove something first: According to John Halpin, head of customer analytics at Tesco Bank, big data is about social media, blogs, videos and news. From a company perspective he suggests dealing with customer communications and regulations on data first. Then, only if you can prove something with the data you already have, you can encourage investment in software to start working with the big data.

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