On path as a Data Analyst

On path as a Data Analyst

my Junior role has been busy af but exciting!

So I shared two months ago that I was starting my new role as a Junior Data Analyst and here's an update : I'm loving it!

Busy af but good.

As in life not everything is wonderland, there are some catches, and I believe that the way you embrace challenges is what makes the difference between that being a nightmare or a thrilling experience.

For anyone considering starting a similar role, how good or bad that could be for you depends of course on your unique levels of perception and from where you are coming from. Bear in mind this requires a high sense of critique, very low or null ego levels and a big capacity of adaptation and learning new stuff.

Focusing more on the technical side of the journey itself, my days have been focused on 3 main things:

  • not letting my team down
  • keeping up with the specialised knowledge for the role
  • evolving with my python and excel skills

As a result, even if not asked to, I ended up working a lot more than what I should, especially in the first 3 weeks. After a long 8 hour shift, I invested a few more hours in continuous learning everyday to keep up with what I considered to be the minimal requirements for myself.

What I considered to be the minimal requirements to be 'on track' was coding, learning more tips and tricks about python for Data Analysts and learning more about the required specialized knowledge, let's say around trading.

I didn't expect tbh, as a junior data analyst to have to gingle with more than 4 dataframes, extracted in 'patches' from dirty csv files that are then cleaned and merged and whatnot. But I'm glad it did end up like this because the baggage I'm building and carrying on me is very valuable, in my own pov.

Now, this results in a big dataset, almost 1 million rows and around 20 columns so I had to really dive into big dataset management and find my own solutions to make it right.

What if you receive a csv file that is not tidy at all? Well, I came to learn first of all that this is unfortunately a comum reality among data analysts. Would I be a better programmer than those who freaking create those csv's I wonder? Or have I high standards ? Com'on it's freaking simple ! Standardisation of things and rules are there for a reason! That's why we have standard csv, xml, jason and so on! Ahr well you know, if I can't change that, I can at least protect myself against that.

So I'm still building a powerful app that reads the csv file line by line, checks the number of separators, then create a mapping type table from the 'good lines' so I can finally fix the 'bad lines'.

I'm kind'of doing machine learning and software development instead of being just a data analyst but that's the trade I'm willing to bet on: myself.

Because, as a data analyst, you MUST know and be able to:

  • get the data
  • clean the data
  • manipulate the data
  • use the most effective tool to complete the job in the time you have available

Yes, I had to dive deep into Excel because although I know I can make it in Python, I don't have the time right now so I had to make that decision and jump to Excel (🤮) to finish my job.

Because only then you can sit on it and really do the 'analyst' thing, no matter what tool you use.

Yes, getting the data at this level might be more a job for a Data Scientist or Architect, not exactly sure but in a small team like mine, I'm gald I'm used to be a man of many hats.

Reiterating this, if you have a table of a dozen rows and columbs, it's easy to fix it manually in excel right? But if you're handling a one million lines per 20 columns table, you really have to bring all of your creativity and abstract approach to build a series of functions that will guarantee that you end up with a tidy and trusted set of dataframes.

If not, any conclusions you take from the data set are worthless.

Not to consider the amount of time and energies invested.

Let's quickly talk about the excitement that comes with it.

I love being challenged and as I refered on a previous post, I'm the type of person that likes to take 'thinking' to extreme levels. On the other hand, I learned in life to see the big picture and to learn about perception and behaviour. That along with some technical knowledge in tech stuff, makes me feel accomplished and fulfilled.

I work now from home, paycheck is better than what I had previously but I know these skills and acquired experience will come with a compensation sooner or later.

I believe that money has to be a bi product of your goals and not the primary goal.

Building happiness for money to come or building money for happiness to come, that's really up to you. I reckon the first one is the right choice.

Stay frosty Analysts!