Big data mining for product feedback
People talking about what they do and don’t like about a product on social media, internet forums and the comment...
Making big data more accessible will open new opportunities for your business – here’s how to make it happen.
Truly, we are living in the age of big data. According to one study, we create 2.5 quintillion bytes of data every day. Even more amazingly, 90 per cent of the world’s data was created in the last two years alone. As you can imagine, these figures are only going to go up – according to Art Landro, CEO of enterprise web app developer Sencha, we’ll create more data in 2017 than we have in the previous 5000 years.
The question is, how to sift through to find the useful information? Company bosses frequently complain that they’re ‘drowning in data’. Luckily, there’s a lifebuoy at hand – all they need do is not be overwhelmed by the scale of the task, and know how to go about tackling it.
A lot of companies gather data with no clear goal in mind. They often keep data in isolation, in a silo, and treat it with the puzzlement and wonder of an animal at a zoo.
Is it any wonder that they don’t see the results they would like?
A successful big data strategy needs a clear goal and purpose from the get-go. If you don’t know where to start – what’s known as analysis paralysis – software company Domo recommends asking yourself two questions: What are the important facts about the business that you have been unable to quantify properly? Of these, which should be quantified using new sources of big data?
Once you know what your goals are, it should be easier to know which data is relevant and which you can ignore. And once you know that, you can make the data work for you.
When exploring the data, stay focused on your goals, but also keep an open mind. That way, you’re more likely to discover new things about the business. If you go in only looking for results you would like – or expect – you’re not going to use the data to its full potential.
Once you’ve found a data subset that’s of interest, you should extract it for further analysis in what’s known as an analytic sandbox. Data should also be exported so it can integrate with other operational platforms. Remember: data isn’t much use when looked at in isolation. You’ll only discover useful insights if you merge data from multiple sources.
You should use your findings to make actionable insights – for example, a new cluster of customers could be a big sales opportunity.
You can find out more about how to unleash the potential of big data in our white paper.
It’s important to share your findings across the whole company in a process that’s known as ‘democratising’ data. This stops it being the preserve of a select few executives, and opens it up to possible further insights. It also prevents fostering an ‘us and them’ attitude among the workforce, and stops different departments from contradicting each other with different data sets or arguing over whose data set is best – all of which is good for company harmony.
We’re living in the digital age, so all decisions should be data-driven. Giving more people access to the data will make the conclusions drawn from it more watertight and will improve decision-making.
So how should you present your data?
Executives are fond of dashboards – these are basically a series of infographics. By presenting the data visually, it will have much more impact, and help to highlight the important points. It will also quickly engage the user, and doesn’t require them to be a data scientist to understand what the data means.
You can personalise the dashboard to the individual to bring out the highly actionable information, although this probably won’t be practical for everyone in the business.
Dashboards should be lean, only highlighting the important information, and be viewable on all devices like a smartphone, tablet, PC, and using any web browser. That way, you’ll cater for a mobile workforce.
Ideally, they should also let the user interact with them, to see what would happen if one data set changed, for example.
Staying on top of big data is a full-time job; some big data, like social media, streams 24 hours a day. To process all this information, you’ll need an elastic and agile cloud business intelligence (BI) platform (for some of the best, check out this guide). This can provision CPU and storage resources as you need them, depending on what kind of – and how much – data you’re exploring.
When the workload subsides, the cloud automatically recoups platform resources and assigns them to other workloads, with no capacity planning required. Cloud BI is also quick and easy to set up.
You can also employ high-performance computing (HPC) to manage the constant influx of big data.
Big data brings enormous opportunities for enterprises, but only if they deal with it in the right way. Making it more accessible to the entire workforce will help you weather future storms and make the most of the sunny days ahead.