If we look online or on social media, everyone claims to be a good analyst. But few can actually do actual work or analyze data well. One can bring out an insight. Or can make a decision from any data. Such people are rarely found. For example, last month, I was working as a data analyst job recruiter for a company. To be honest, when we created the job applications and released them to the market, we received about 400+ applications. The first time, we cut 300 people based only on skill and knowledge.
You can find the explanation of why I left it at the end of this article. As a recruiter, I can see that there are many data analysts in the market. Many claim to be good data analysts. But the number of actual good quality data analysts is very low. Finally, when we called for interviews, we called 12 people for interviews. And finally, when we selected three people, even after selection, we can see that there are many gaps in their education.
Many people think that they will become good data analysts by learning the tools of analysis. But not really. To be a good data analyst, you need some soft skills. That will help you make decisions from data.
What do data analysts actually do?
If I try to explain it to you very simply, a data analyst acts as a bridge between a business and making business decisions. Today, the entire world depends on data. A business, therefore, generates a lot of data. And when a business starts making decisions from this data, what it did in the past and what it has to do in the future, when it starts making such decisions, it will grow the business very well.
And for this, a data analyst has to adopt some methods:
- Data Collection: Data analysts gather information from various sources, which can involve conducting surveys, scraping data from websites, or purchasing datasets from external vendors.
- Data Cleaning and Wrangling: Raw data is often messy and inconsistent. Data analysts clean and organize the data to ensure its accuracy before analysis.
- Data Analysis: Once the data is clean, analysts use statistical techniques and data visualization tools to identify patterns, trends, and anomalies.
- Communication and Storytelling: Data analysis is all about turning numbers into insights. Analysts create reports, dashboards, and presentations to communicate their findings to both technical and non-technical audiences.
When a good data analyst adopts these methods, he can easily make good business decisions. For example, in the company where I am working as a data analyst, 60% of the company’s decisions are made by my data analysis.
Why Project Is Important for Data Analytics
From my personal experience, I can say that a project or portfolio is more important than a certificate for a data analyst job. When you go for a job interview, if you can show three to four projects, the job recruiter will get a positive impression of you. A good data analyst looks at at least three projects.
Generally, a data analyst has three projects like:
- Web scraping.
- Data cleaning.
- Data Visualization.
If one can make projects on these three things in the beginner stage, then he can easily claim himself as a good data analyst.
Web Scraping
Web scraping can be a valuable tool for data analysts, allowing them to collect large datasets from websites for analysis. Identify the data points you want to extract. Browse the website and familiarize yourself with the structure. By doing such things, you can use web scraping in your project.
Data Cleaning
Data cleaning is the essential process of preparing data for analysis by identifying and correcting errors, inconsistencies, and missing information within a dataset. It ensures the data you’re working with is accurate and reliable, leading to trustworthy analysis and conclusions.
Data Visualization
Data visualization is the art of transforming raw data into visually appealing and informative graphics that clearly communicate trends, patterns, and relationships within the data. It’s a powerful tool for data analysts and anyone who wants to make sense of information.
Data Analyst Soft Skills
Learning the tools alone will not make you very good in the tech world. You must focus on soft skills just as you need to have skills in data analysis. Data analysts need a strong combination of technical skills and soft skills to be successful. I think soft skills help you to be a good data analyst.
- Communication: Being able to clearly and concisely explain complex data findings to both technical and non-technical audiences is crucial. Communication is fundamental for data analysts. Understand your audience’s technical background. Use clear, concise language for non-technical audiences.
- Collaboration: Data analysts rarely work in isolation. They collaborate with colleagues from various departments, such as marketing, sales, and engineering. When you work as a team, you can share your valuable opinions on anything. This allows you to go deeper into the data.
- Problem-Solving: Data analysis is all about solving problems. Above all, a data analyst finds business problems and solves them. For this, it is very important to have problem-solving skills as a soft skill.
By mastering these soft skills, you can transform data from raw numbers into a powerful tool for driving informed decisions and achieving positive outcomes.
If you want to hire a data analyst, then follow these methods. And if you want to make yourself a data analyst, then follow all these things above and make yourself a good one. It is not a very difficult task. All you have to do is sort it out.