One of the most discussed concerns surrounding big data today is privacy. While many powerful analytics are possible with the detailed data that is now collected on each of us, the sensitive nature of much of that data requires rethinking data practices and applications.
It is challenging to make big data simple to access and easy to analyze. While there are many reasons for this, the one I want to focus on here is that handling big data, given how big data projects are usually implemented today, requires users to learn new tools and technologies. This makes adoption a difficult and lengthy journey.
In the past few months, in addition to my usual travel around the United States, I have had the pleasure of visiting both Europe and Asia to meet with customers and discuss analytics and big data. It was very interesting to me how similar the conversations were regardless of where I was in the world.
At first glance, the idea of starting small with big data sounds like an oxymoron. It just doesn’t sound right, does it? I believe that if you take the time to think about it, you’ll realize that not only is it the way to go, but it is simply an extension of a method that has been successful in working with new data sources for many years.