Before you actually jump on to your data to start cleaning, analysing, visualising, there’s something you do first.
If you don’t know what you have to analyse then what are you gonna analyse? It sounds obvious but it does happen a lot. Starting without knowing what you’re looking for. You might get data that needs analysing or a collection of data that needs attention. Sometimes it’s just a question whether. you can see if you can find something interesting in the data. Before you continue to do so, what’s the reason they ask you to analyse this data? What are they looking for? Main ‘problem’ most of the time is that the manager or the person that asks you to analyse something, often doesn’t know exactly what they want. Because they are not the specialist, you are. Therefore they hope for a surprising result that just pops out of your analysis. Unfortunately that’s quite a challenge, almost impossible to make that happen. That bit in between what you can and what someone expects you to is the gap that needs to close before you start working on the data. Make sure you are the person to close that gap, by asking questions.
Don’t expect someone to come up with a strong and perfectly formulated hypothesis. If they know what they are looking for, it quite often comes in the form of a general question, or wonder about disappointing results from whatever you can think of (depending of the company you’re working for). You are the specialist. You need to ask questions to get as much information as possible, but at the same time you need to use your own knowledge to transform their information in the right strategy or approach that you will use to answer their questions in the right way.
Don’t underestimate the importance of asking understandable questions. If you’ll start talking in all sorts of data science related language, they won’t understand you, might give you the wrong answer and you end up doing the wrong thing. Make sure you get at least a broad overview of what they want, what they expect of you and make sure to communicate properly.
It might sound all very straight forward but don’t forget that after a while, every thing you know about data analysis / data science becomes common knowledge for you. For an employer, a manager or anyone involved in your data, it simply is not. They don’t have that knowledge, because they’re not the specialist. So make sure you ask easy, understandable questions without too much technical language in it.
An exception could be if you’re talking to a head of data science for example. For now I’m only making you aware of it because not only analytical skills are important, also communication skills are very important part of the process.