The study data analysis, I was overly concerned about the tools and glamor that could make the title of a data commentator.
My internship started, and I had one goal in mind: Develop my technological skills. I mean, everybody wants to make their Linked Deficiency Profile decorated with skills and certificates.
Unexpectedly, however, that my most important lesson will not appear with a tool or tutorial. It came from something more than someone: cooperation.
At first, I tried to deal with everything on my own, viewing each work as a personal challenge. I didn't know, my product was somehow because I spent many hours trying to find solutions each time I found myself.
Not so I would start looking for the answer and involve experienced professionals that things begin to fall into the area.
This is where I see that in the data anchor, working with others is not an option; It is a necessity.
As improved, I intend to share experiences in part with cooperation and how it warned as a person who interpreting the desired data. Also, why do I believe it is one of the most important skills (and trustworthy) the whole commentator focus on.
The first days of my work training
As a teenager who enters the sector, I just wanted my hands to real data. Until then, most of my habit had sample datamfits.
Now, I have my training. I had the opportunity to work with the most important data in the organization.
I was given a project to create a basic report using the data in work activities. The details were not very dirty, but it was not clean or. Consisted of certain inconsistencies, double lines, and a few non-entries.
I resolved using Excel and Power question, and then I would clean what I could, and I built the dashboard I thought was looking good. I honestly, I was proud of it.
Forward, the period of presentation.
Before I move forward, here is something: no one told me about the introduction factor for the data analysis.
It is funny as that can be heard, true. Earlier I thought I would work with the data, have meaning on it, and pass it on to the bones in managing or something like that.
Snap returns to the fact, I introduced dashboard, and my boss did not seem impressive. Not because the visual was bad, in fact, he said that it looked good.
The debate was that the dashboard did not speak what the group actually necessary to see.
True, I did not talk to anyone about what you discernment were helpful for them, any information that would help work well in decision-making.
These are basic basic basics in data analysis, and I lacked in that feature. I made up based on what I thought is important, not what they needed.
I didn't ask questions such as:
- “WHO Will you use this dashboard? “
- “What are you Will decisions do this to help them do? “
- “Why Does this information care about? “
That is the ability to work together, ask questions before the project begins and searches for the answer to eliminating.
Which partnership taught me
In time, I began to see that, despite my views clean and my numbers were accurate, sometimes people didn't understand my reports.
I can spend many hours I solve the banned problem with a two-minute discussion. Take it or stop it, I believe the data requires testing together and is transferred in a way that brings others by walking.
Data analysis is not just information, it's about people.
When I work very well with people, when I see that critical partnership throughout the data analyzing process. Looking back, those working hours and others was when I was growing too much.
One of the first times I sat down with unemployed workers, surprised by the way they looked at the details.
I had spent many hours creating a chart to show monthly jobs, but when I explained it, they said:
“Ok … But how do I know that we do better or worse than the last quarter?”
I have a change in mind.
Instead of constructing well-looking charts, I began to think from the idea of a non-technical activity. It is like having more eyes to trouble; It can help you see things differently.
Response
Before my internship, I was to build something, give a few checks, and skip another new to get my analysis.
On the other hand, in the team planning, the answer is usually part of the work of work.
Sometimes that was saying to review the chart because it was not clear, or noticed the KPI I thought that it was not working on the report.
Each reply cycle helped me sheep both the visual and the story that reported. It has taught me that even in data analysis, intelligence and reviews are compatible.
And here is something, the answer doesn't always be correcting mistakes. Sometimes it is about getting more likely to see yourself.
For many, seeking an answer cannot be free and can pull. Don't worry, you're not alone. The key in this argument is the opinion of this study that is sudden spike at heart levels while you receive feedback.
A key lesson in this study shows that the answer is not critical, but rather is a concerted work.
Some people borrow their views so your work is crazy. And trust me, if you hurry to invite you, your skills are quick to grow.
I've learned to stop waiting until my work is “perfect” before you share it. Instead, I replaced early, collecting input, and improved.
The partnership creates more than skills – creates your network
In my behalf, network communication in the data industry is highly attacked and are not spoken enough. If there was one thing that I did not see before my internship, how much cooperation is to form relationships.
When working together with people, perhaps by asking questions, you are talking about technical solutions about lunch, or repair the project together, not only for jobs; You create a connection.
I first saw how important this is when an engineer joined him in the data pipe story that sent the course of the SQL skills. It's on YouTube, and I advise you to check it out.
From the technological point of view, cooperation increases the “tool box” in ways you read how to read in ways will not make the right diligence. Each time I worked with someone, I took something new (even if it was found).
Now here is the best part: This relationship is simply not expiring when an internship does. The same people today partner can be your teachers, your future referees, or your partners and in another organization.
Collaboration is a bridge between your current skills and future opportunities for the future.
The end and the Knowledge
Looking back, my internship did not teach data skills; Teach me how to work with people. I understood that my real value is repeated when I work with others, not just aside them.
The fact is, no matter how good itself is with Python, Tebou, or SQL, you will continue to move forward to the fanatic package when you tap the information and the displeasures of the people.
When you start the data analysis, remember that your tools will expire, your Tech stack will appear, but your ability to work well with people will not lose its value.
