There is so much hype surrounding big data and a lot of noise around its importance to the future of business and the data industry. But where do you start? Ironically, I believe the best place to start is with small data and small problems.
For me, and the company I work in, there is still a lot of uncertainty around the myriad of technologies and methods which go hand-in-hand with Big Data. How do we integrate diverse data platforms into our enterprise stack? Can advanced analytical algorithms yield greater value from our data?
My plan is to start small. Find an opportunity within our current services that we can improve upon using some facet of the Big Data toolkit. Perhaps by breathing new life into our dashboard, or delivering data to our team in innovative and informative formats we can demonstrate value and build trust in new methods.
There are two really important words in “Data Science”. The first is data – and we have plenty of that! And the second is science. The nice thing about science is that it is very rarely perfect. Science is an iterative exploration and that is exactly what this journey should be. Over the next few months I will post about this journey and share my small steps to Big Data.