Is Data Scientist a DIY Profession?
When popular technologies arrive, in-demand jobs follow – and no job is hotter in the technology world right now than the role of data scientist. So hot, in fact, that the Harvard Business Review coined it as the sexiest job of the 21st century. GigaOM reported earlier this year that it’s the future of IT. MIT advises that in order to fill a workplace demand for data scientists gap, organizations need to seek out professionals with a unique mix of IT, scientific and analytical skills in order to harness, correlate and act on their growing amounts of data.
In our opinion, any profession that derives insight from data is a good one. But who says that a data scientist is the only one that can do it, in all related cases? Why do you need to be the one behind the algorithm in order to obtain insight from data?
In many cases, you will need some serious computing power and some mathematical prowess. But in many other cases – particularly when you’re looking at a wide variety of data sources – you won’t. The power in unlocking the insight comes from the index. And the beauty of an index is that anyone can use it. The search query allows you to bridge data from all sources – structured and unstructured, on-premise and cloud, social and CRM, etc. When you have all information presented in a unified, correlated format, any user can derive insight from data.
We’re not trying to halt the data scientist revolution – but it should be noted that a scientist isn’t the ‘end all/be all’ of Big Data. If you’re dealing with an insight deficit due to fragmented information, give indexing a try. You may be able to solve more of your Big Data-driven projects than you originally thought. And if you need inspiration, check out many of our customers in CRM, marketing and research that are using indexing every day.
Have you tried the DIY approach to the data scientist profession? What did you learn from the experience?