Hey, I totally get it. You’re in your final year of university, and you’re interested in data analytics. You’ve even finished the Google Data Analytics course, covering the basics in Excel, SQL, R, and Tableau. You’re eager to dive deeper into SQL and eventually pick up Python for data analysis. But now, you want to build a beginner-friendly analytics project using just Excel and SQL to showcase in interviews and upcoming campus placements. The problem is, you feel lost.
I’m here to tell you that it’s okay to feel that way. Building a project from scratch can be overwhelming, especially when you’re new to data analytics. But don’t worry, I’ve got some advice to help you get started.
First, let’s talk about the type of project you can build without Python. The good news is that you can still create a meaningful project using Excel and SQL. For example, you can analyze books-related datasets like reading trends, genres, ratings, and more. You can use Excel to clean and visualize the data, and SQL to query and extract insights from the data.
Now, you might be wondering how detailed or insightful a project can be with just Excel and SQL. The answer is, it can be quite detailed and insightful! With Excel, you can create interactive dashboards, pivot tables, and charts to visualize the data. With SQL, you can write queries to extract specific data points, perform aggregations, and create data models.
So, how do you add SQL code to a portfolio in a useful way? One way is to create a report that showcases your SQL skills. You can include screenshots of your SQL queries, along with explanations of what each query does and why. You can also include visualizations of the data using Excel charts and graphs.
As for whether people will think you’re lazy or basic for not using Python yet, don’t worry about it. The fact that you’re taking the initiative to build a project from scratch shows that you’re proactive and willing to learn. And who knows, your Excel and SQL skills might just impress them!
Lastly, don’t be discouraged by the Python-heavy projects on Kaggle. Remember, everyone starts somewhere, and building a project from scratch is a great way to learn and improve your skills. So, take your time, stay focused, and keep practicing. You got this!