Data Analytics and Data Science are terms that you can hear on every other guy’s mouth. The buzz Data Analytics seems to be growing exponentially.
But, what comes to your mind when you think of a data analyst or data scientist?
Do you think of someone with an air of confidence, who knows what they are doing, who probably have a solution to all possible challenges that could arise?
But if you think it all comes easily to them, let me stop you right there. Even the ever-so-knowledgable data analytics professionals have to deal with situations where they do not know what to do.
Let’s read further to see what Funny situations these professionals often end up in at their workplaces.
Disclaimer: All the experiences have been written in the first-person narrative, but that doesn’t mean they are mine. These are experiences shared by multiple people. Maybe you could have encountered a similar situation(s) yourself. Let’s find out!!!
Manager: Why don’t you create a predictive model on this data and identify the fraudulent transactions?
Me: But Boss, we don’t have a response variable for all the observations; how should I create a predictive model?
Manager: At least try, I am sure you will be able to do it.
Me: But there is no output on which I can train the data to create the model.
Manager: Try, there must be some other way. I am sure you will be able to figure it out.
Me: Okay, Boss. I will create a model.
…..and, we never talked about that model again.
That’s the funny side of being a data scientist or data analyst when working with people who don’t understand technology. If you tell them this can’t be done, they will push you to find some alternative way to do it, and the sad part is you can’t even explain why this doesn’t work. Your world is alien to them, and you are some advanced species that has come in this world to make their lives easier. At other times, they may feel you are too lethargic (and incompetent) to do your job for which they have hired you.
Let’s look at another incident.
Manager: We will use ‘Hadoop’ to carry out analytics at the client’s place.
Me: Boss, but the data size is quite small. We can get the data in CSV files and analyze that on our systems.
Manager: But we have to use ‘Hadoop’ to present our capabilities to the client.
Me: But we don’t need to do any such thing. It can be done easily on our systems.
Manager: Why do you argue so much? If you can’t do it, just tell me. I will find someone else to do it.
Me: Okay, I will use ‘Hadoop’ for analysis.
Wait, wait, there’s more!
Manager: I need results with a 95% confidence interval.
Me: But, we are doing plain descriptive analytics. We use the confidence interval when we are predicting something.
Manager: I don’t know anything. I need all the results with a 95% confidence interval. That’s it.
Me: Okay, I will do that.
Well, nothing changed in my analysis; all I had to do was tell the manager that results lie in the 95% confidence interval.
Let’s look at another one on data quality.
Manager: What happened to the sales data that I gave you? Did you try something on that?
Me: That data is very messed up, so I couldn’t do much with that.
Manager: This coming from analytics guys is not appropriate.
Me: (Dude,) Data doesn’t differentiate between a Manager and a Data Scientist or a Data analyst. If it’s bad, then it’s bad for everyone. Period. (Of course, this just happened in my thoughts.)
Me (now in reality): If an analytics guy is saying that data is bad, then you better believe him.
Manager (With Poker face): This will be reflected in the next annual discussion (Obviously, he didn’t say it but was evident from his expressions).
Now, what should one do when stuck in such a scenario?
Empathize, yeah?
That’s precisely what I have been doing with my friends and myself (if I happen to encounter a similar scenario).
When you have studied analytics for quite some time, but you end up working with people who are not from the technical background, you often find yourself stuck in usual scenarios. According to non-technical people, everything related to coding, infrastructure, databases, big machines, or the internet is IT, and nowadays, IT has been changed to analytics. If your laptop is not working and the IT team is not around, what would you do? Go to the analytics team!
They don’t seem to see any difference between IT and analytics. Sometimes, it may become very challenging to make people understand what you have done because if that doesn’t happen with a single click, then whatever you have done is useless. I am sure many people think that through ‘Analytics,’ all they have to do is just think, and their task will be done automatically. I wish that could happen; I wouldn’t mind spending a few years in learning analytics.
But, there’s a bright side to this as well. When you work with such people, you learn the importance of explaining complicated things in simple and understandable English. Explaining technical work (esp. as complex as the Random Forest model) could be a nightmare, but you get to understand the other side of the story. Since you have studied technology for quite a few years, it comes very intuitively to you, but the case is not the same for other people who are probably from a finance background or teaching or fashion designing. You should appreciate others’ points of view while explaining them the tricky concepts; this increases your patience many folds.
This is how I plan to rationalize non-technical people’s behavior if I ever encounter such an experience (:P).
Have you ever found yourself stuck in a similar situation? Share it with us in the comments section. Tag your friends/colleagues, too. Don’t worry; we won’t tell anyone. Shhh..!
