Data and Analytics: First things first

As we embark on a new journey and possibly the final frontier in the information age and more importantly in Data Analytics as a tool or skill set used to give insights into any sphere of live and more importantly to measure business' "health" and drive positive strategies, we come to a realization of the gap that exists between the demand for talented data people and the available pool of this resource is heavily unbalanced. I write the following, very brief article from a data analyst who is moving into the daunting data science realm. I have been working with data for a decade or so now - so I feel I can point out to a common trend I have always been confronted with with which I feel can be changed and needs to be changed. My view is that the "First things first" in data analytics teaching needs to change. The emphasis put on any programming tool and its syntax is put in front or at the start of the training and this for me is totally wrong. Most teaching give a historical background - which sets the tone and is a nice way to introduce one to any topic and there is nothing wrong with this. Than they follow with installation of the tool and executing the simple "Hello world" which to be honest is not a bad start but the next few topics or chapters is where I feel the problem lies. Why do we go into data types recognized by the tool and next operators, loops, functions arrays etc - for heaven sake we all went to high school you know. My view is the first few chapters before all this latter should be about linking or importing data into the tool of analysis. Why, well how are you going to learn all the tricks (syntax) if you cannot reference them back to a data set that exist that you can view, oh and that's the other import part that they miss - we want to be able to view or data set. So first thing should always be around reading different types of files into your tool of analysis then follow that with viewing data in your tool of choice and lastly that other staff that teaches you how to manipulate the data. The quality of the article is not whats important but the message. In future I will write a few data analysis intro books since I have been here for sometime (in the trenches).

Look at it this way when we learn in data it should follow that we need to have our subject(data table) in our control and than try to achieve a particular objective like normalizing a composite field, select a part of a string - converting a date field or summarizing by some other fields or you name it - bottom line is we need a lab rat! One-day I will follow up with a more structured article but for now I need to hurry of and rewrite some of the data analytics books out there.