Enhance Your Data Analysis Skills During Your Lunch Break!

by Aaron Finch

Data analysis is a fundamental skill for every data scientist to have. After knowing business analyst salary, even i have grown interest. It’s also one of the most popular skills on LinkedIn, and it’s been growing quickly. So, how can you make sure that you’re getting the most out of your data analysis skills? If you want to keep up with these trends and add a few new tricks to your bag of tricks, then this blog post will offer some good ideas.

One way to grow your data analysis skills is through lunch breaks when you can take short breaks from work or study during an afternoon break. You don’t have to feel guilty about taking a small break during your lunch since you’re not missing anything. You’re not even doing a big job such as building a time series model for smoking habits. There’s no real reason to rush back to work or study immediately after lunch. So, do yourself a favor and make the most of your lunch break.

1.) Start with some basic data analysis techniques before moving on to other techniques

Recently, there have been a lot of big data resources and data science courses created on YouTube and elsewhere. But, some people might feel overwhelmed by the number of resources. Instead, it’s better to start with some basic techniques and move on from there.

For example, start with a few data manipulation techniques and then move on to the more advanced techniques. You might be surprised at how useful these simple techniques can be when you start using them in your daily work or even just for fun everyday life.

2) Always try your best to make the best data analysis techniques better

For example, it’s not just about learning from other sources. It’s also about improving your understanding of the techniques you’re using. This will allow you to make the most out of data analysis techniques during your daily work and help you identify clear areas for improvement.

3) It can be beneficial to use available resources more than trying to reinvent the wheel

Instead of reinventing some wheels, find a place where you can get further details on a particular technique and where there are already some good examples. This will truly help you improve your skills on these data analysis techniques which is much more worthwhile than trying to figure out how something works “from scratch”.

4) You can always build something from scratch if you want to

Sometimes, you’ll have to do some research and develop your own skill set. But make sure that you don’t forget about the resources available for you. Even if there are already good examples on a technique, it’s best to look at these examples and understand those techniques before trying to build something from scratch. You never know what might happen when you try new challenges on your own. Besides, there is always the possibility that you might find something better than what’s already out there!

5) Try learning data analysis techniques with someone else if possible

If possible, it’s great if you can learn data analysis techniques with other people such as a friend or a classmate. This can be a good way to practice the techniques and also to build friendships along the way.

6) You never know where you’ll learn it from or who will teach it to you

You might be surprised by where you’ll learn data analysis techniques. For example, some of the best resources for data analysis are not necessarily on your local university’s course curriculum. You might also find these resources in unexpected places such as through your work, a friend, or even a website with videos online. Never underestimate any place that can offer you insights in your data analysis skills.

7) You should always try to apply data analysis techniques in a real-world problem

When it comes to applying data analysis tools and techniques, it’s best if you can apply them in some real-world settings. Try doing this by trying out new solutions on your own rather than waiting for others to do that for you. You may also find a way to apply the techniques on your own. If you already have a data analysis system for one problem, try to take advantage of it and use it for other problems too.

It’s always good to see how effective the tools and techniques that you learn work in your day-to-day work or even on real data sets. 


In this blog post, I’ve shown you some ways to improve your data analysis skills by using lunch breaks during your work or study time. Start with some easy techniques and then explore them further at a later time. You never know what might happen!

What are your thoughts about these data analysis techniques? Let me know in the comments below.

Note: There are more than 40 million people on LinkedIn, so don’t worry if you don’t see yourself in these statistics.

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