Saturday 31 October 2015

Addressing the Big Data Skills challenge


Finding the necessary skills to help you on your big data journey can be a challenge.  You need people to help you setup your technological environment and then people to help you use and maintain that environment.  For help with implementing your big data technology you can just turn to the vendor.  They will undoubtedly offer services to install and configure the products because that is one way they make money.  Where you will struggle is finding people to help you use that technology in your organisation, specifically with the interpretation of the data.  These people are commonly referred to as data scientists although they can have other titles (IT industry loves creating titles).  Data scientists are typically masters and phd graduates in statistics or data science and are hard to find in large numbers.  McKinsey estimates that the U.S alone faces a shortage of up to 190 000 people with such skills.  So if you can’t find any of these data scientists to employ what can you do?  Well you can make them.  If you have an analytics department it is possible that you have employees that have the aptitude for data science.  You can send them on a few courses or even an entire degree to learn the necessary skills.  It may be slower that employing someone directly but it will pay off as you are will have someone who already knows the business and will have a good idea how big data can be leveraged.  Another option is to create a team with data science capabilities.  You do not necessarily need to employ one person with all the skills, you can employ a team of people who collectively have the necessary skills such as statistics, business domain knowledge, business analysis and so on.  There are ways around this skills shortage, you just need to get creative.

1 comment:

  1. Perhaps Issue of implementation seems to be bugger than finding data science skills. How many organization's have an analytics department? Are those department contributing promise of analytics? Top management needs to understand the value they can get out of analytics

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