Steps to follow if you want to start a career in Data Analytics today!
Data is the hottest job market of the 21st century, but with the hefty paychecks comes the downside of huge competition. So now, how to get into data as a fresher? How to start as a beginner? By standing out. And how do you stand out?
Let’s decode how.
Learn the right skills.
Internet is filled with an overwhelming amount of resources, courses, and blogs. The human mind easily gets tricked with the shiny object syndrome and goes after new, better resources rather than building a skill only to end up in tutorial hell. It’s time to prioritize the skills you want to learn and the material needed for it before starting and sticking to it.
Remember, you don’t need to learn everything in the job description. Most JDs are poorly crafted google search mess and there are only a handful of skills you really need.
The top skills you’ll need to be a Data Analyst are :
- SQL
- Data visualization tool ( Tableau/Power BI)
- Excel
- Python
Let’s focus on each one separately :
1. SQL
SQL is the meat and potatoes of every Data Analyst. It can be used to extract and transform data from relational databases and is extremely scalable. It is the №1 skill you need to get if you are someone just getting into data.
You can use resources like Mode and SQLBolt for hands-on interactive learning in your browser itself.
I have a series of blogs explaining its important concepts too :
2. Data visualization tool ( Tableau/Power BI)
Quoting Alex the Analyst from Youtube :
Data visualization tools along with SQL are an unstoppable force. You can apply to most jobs knowing just these two.
Being a data analyst you spend a lot of time generating reports to communicate your findings to other teams through visualization. Tableau and Power BI are what most companies use these days. And adding ANY one of them to your toolbelt would be a great plus.
The best resource for this to my knowledge is Youtube, tons of tutorials. But always remember to get your hands dirty. It’s only when we try things out that we learn.
3. Excel
Excel is used by almost everyone and is not even mentioned separately as a skill in the job description since it is assumed you have it. It is a MUST-HAVE skill in 2022 not just for the data community but for everyone. Here’s a beginner-friendly video walking you through it :
4. Python
Python is a programming language and extremely useful to wrangle, clean, visualize and model data all in one place however it can be daunting for an absolute beginner. So it is recommended to take this is as the last step while not getting overwhelmed with all it can do. You don’t need to know it all, you can learn while on the job. Here’s a great free course on Udemy for Python for Data Analysis :
https://www.udemy.com/course/master-data-analysis-with-python-intro-to-pandas/
Building Proof of Work
After gaining the necessary skills, it is essential to put them to use as most recruiters and hiring managers are looking for more than certificates and degrees, they want practical proof which builds a sense of trust because you showcase your skills in practical scenarios.
The best way to do this is by :
- making projects
- doing work for nonprofits
- doing contract freelance jobs
I have shared a few projects ideas on Twitter and I will be sharing their how-to on my Medium. Stay tuned ✨
You can also follow the portfolio series by Alex the Analyst on Youtube
Putting yourself out there
After your toolbelt is ready and you have tested your skills in practical use cases. It is time to put yourself out there. Out where? in the hiring world.
1. Create a LinkedIn profile
If you are not already familiar, Linkedin is where the hiring managers hang out. And it is an excellent way to showcase all your learnings, certifications, projects in one place easily navigable.
2. Create a resume
It’s 2022 and yes we still need to make this. But nonetheless put your best efforts on this because it’s the first round of every job screening and make sure to run it through an ATS first based on your job description because most times if you don’t find that sweet spot between keywords and truth it is possible your resume might not even come before a human 👻
3. Reach out
Cold emails, cold DMs give it all you got. Reach out to employees of the company you applied to or want to get into and have conversations about openings and referrals. After coming at this stage make sure to contact atleast 10 people a day.
That’s it from my side. Hope it helped. All the best on your Data journey 🎊
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