This Twitter Thread is by Sharyph @thegoldsuite (source: 11-18-2022). Sharyph is a tech writer.
Data Analytics Market will increase from $23 billion to $133 billion between 2019 and 2026.
Here is the Fastest way You can Become a Professional Data Analyst.
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You may have spent too many hours watching YouTube Videos, and Udemy Courses, but it may not help.
In this thread, I remove all the fluff and give you the fastest path to go from zero to FULL-TIME DATA ANALYST
Also, in this thread, I will share the major mistakes almost every data analyst makes.
So, you will not repeat those.
Let's get into it.
- Pick a Tool or Programming language for data analysis
I choose Excel as a tool to begin.
Why Excel?
- It's easy to learn
- Used in almost every company
- It has a wide range of applications for data analysis
Pitfall:
It's not designed specifically for data analysis
Excel is perfect for starting out, but once you've mastered Excel,
it's time to move on to the more serious tools and the most logical tool to learn.
- Learn SQL
It is apparently the second most requested skill in data analyst job
Why SQL?
Because it doesn't have the same limitations as Excel
- you can extract
- transform
- load very large data sets
The best thing is it has its own very easy-to-use programming language
SQL is a great tool to add to your skill set as a data analyst
while also being a great stepping stone to some more serious programming.
- Learn a Visualization Tool
There are dozens.
But the majority of companies are looking for people with experience with:
- Tableau
- Power BI
- QlikView
Here are the pros and cons of those tools, so you decide:
Power BI:
- works smoothly with Excel and SharePoint.
it has a free version and even the big versions are relatively budget-friendly compared to the other B I tools.
Tableau:
- Tableau is a B. I tool with more extensive data visualization capabilities than Power BI
- Bit more in demand in the job market than Power BI
Also, It comes with
- a higher price tag
- It is harder to learn than Power BI
QlikView:
- It uses in-memory technology, therefore, faster execution.
- But it comes with a high price tag
- Less demand than Power BI and Tableau
Before we move on to how to get good at data analysis, you need to
- Learn a Programming Language
To become a Data Analyst, we have to choose between 2 programming languages.
- R
- Python
So, which 1 should you pick...
Here is a small help before you choose 👇
R. is a statistical programming language.
Python, a general-purpose computer language, is great for data analysis.
R is easy to learn,
But if you can learn python, you are not only good at data analysis, but you can also be good a developing software, which is a Bonus.
So, now you may know the path.
Excel ➡️SQL ➡️Power BI ➡️Python ➡️
Before concluding this thread, let me also show you the major mistakes beginners make.
So, that you can avoid those and shorten the learning curve.
Mistakes Beginners Make:
- learn by watching others
- You cannot actually learn without doing it
Without writing code or analyzing data you are giving yourself a false sense of progress.
For real practice I would recommend these Free Websites:
- Python: https://learnpython.org
2. Trying to Solve all the problems yourself.
95% of the time someone has occurred the same error and he/she has solved it.
You just have to copy part of the error message in google and you probably end up in StackOverflow.
It is okay to ask for help and learn from others.
You have come to the end.
Here are the steps:
Pick a Tool or Programming language for data analysis
Learn SQL
Learn a Visualization Tool
Learn a Programming Language
Excel ➡️SQL ➡️Power BI ➡️Python ➡️
With this, I conclude this thread, If you enjoyed this thread, please:
- Follow me @thegoldsuite
for more
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Check the links in My Bio, there are resources (free) you will find helpful.
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