Imagine the distance from your house to the shop is 2 km. If I were to tell you how much time it would take to cover this two-kilometer distance, you might inquire about crossing the road or the mode of transportation—whether by car or by foot. Opting for a car would result in less time spent, while walking would require more. If you’re familiar with the route, you’ll likely already know whether to walk or drive.
You might find the subject somewhat intriguing. The reason for giving this example is to help you understand how much time is needed to learn data analysis for a job. Given the world’s heavy reliance on current technology, with all activities being tech-driven, data holds immense importance.
Hey, the methods you will adopt to learn data analysis are also a key issue. Like if I tell my story, it took me three months to learn data analysis. And I personally developed some projects, and easily I got the job. So today, I will share with you my personal experiences and how you too can easily go through this journey and get a job after learning data analysis.
What do data analysts do?
Let me give you an example of the place where I am currently working. I work for a local business that sells products online. The sales of some of their products decreased last month. Now my boss came to me and told me to analyze why the sales of our product decreased. I have analyzed that some of our competitors have been created in the market. Some customers have left us for this.
So we started a campaign on that product, and we started showing ads to people in that area and gave a 10% discount, and then we solved this problem. This total process was made possible by the fact that we had data and could analyze that data. And I have done this analytics work using only two software: Excel and Power BI. If I explain to you why I use Excel: because when I analyzed this data, I did it with Excel because there was not much data, I had a total of 3000 data. That’s why I use Excel, and after doing this whole analysis, I created a dashboard and visualized all the things. There, I used Power BI for that.
What do you need to know to get a data analyst job?
First of all, different companies have different requirements. People who work with big data will tell you about doing data analysis in programming languages. After all, the work of all the tools is the same; you can do analysis with all of them. But what matters is what tools you have to work with at what time.
For example, when I work in science, I do data analysis with Python. But Excel will help you very well to do basic data analysis. To get a job, you need to know the working of almost all the tools, but to get a country-level job, you need to know Excel and Power BI.
What to start learning?
Before I learned data analysis, I could work fairly well in Excel. For example, I used to create different types of accidents and used different types of calculations in Excel. I used to do such tasks with Excel. And when I started learning data analysis, I started data analysis with Excel, and I also request you to start data analysis with Excel. Then your learning journey will be much easier. Suppose you are given a data set and asked to clean it. You will have an idea of the data when you can clean it with Excel.
Undoubtedly, Excel is a simple tool. When you understand all the concepts about data using Excel, it will be much easier for you to learn the rest of the tools.
Learn Power BI
When you do analysis, you need to convert that data into a dashboard. Because that dashboard, you will visualize the data; you will present the data in the form of various charts and graphs. That’s why you need to learn with power. Currently, Excel is very popular and is a tool to manage everything easily. Currently, I build 70% of my work data dashboards with this Power BI.
Learn Python
When you use any programming language in the real world, you must assume that the task is done several times easier. When you work with large data sets, you can’t easily read without programming. Suppose you have 10 lakhs of data, the easiest way to analyze that data would be Python programming.
To give you a small example, in a recent project, I used Python programming; I created a visualization with just two lines of code. But on the other hand, if I were to do this in Excel, it would probably take me over 30 minutes.
If you can learn these three tools well, then you will be job-ready. And you can easily get a job. I learned these three tools to get my first job, and I got the job I wanted.
Prepare yourself to get a job
There isn’t one single secret to data analysis, but rather a combination of best practices and approaches that lead to successful insights. Here are a few key aspects to consider:
- Understanding the Data: Before diving into analysis, it’s crucial to grasp the data’s origin, format, and any potential inconsistencies. This helps in cleaning and manipulating the data effectively.
- Asking the Right Questions: Data analysis is driven by clear questions. What are you trying to learn or achieve? Formulating the right questions guides the analysis process and the choice of techniques.
- Data Wrangling: Most data isn’t perfect and often requires cleaning and organization. This might involve handling missing values, outliers, and ensuring consistency in formatting.
- Visualization: Charts and graphs can reveal patterns and trends that might be missed in raw data tables. Choosing the right visualizations effectively communicates insights.
- Beware of Biases: Our own perspectives can subconsciously influence how we interpret data. Being aware of potential biases helps in maintaining objectivity during analysis.
- Focus on Context: Data doesn’t exist in a vacuum. Consider the context in which it was collected to ensure the inferences you draw are meaningful.
After all, learning data analysis, you will work on some projects. Because when you can show these projects as your portfolio, getting a job will be much easier. And if you are a technology lover and can sit in front of computer for four to five hours every day then you will become a good data analyst within 6 months.