“The One Mistake You’re Making in Starting a Data Science Project (And How to Avoid It)”

Building an Analytics portfolio project can be a daunting task, especially for those who are new to data analytics. In a survey we conducted at Analytica Data Science Solutions, we found that most people struggled with knowing where to begin. Often, people will find a data set that they find interesting and try to build a project around it from scratch. This can lead to wasted time and to the possibility of abandoning the project..

So, where do you start when it comes to a data analytics project? As a data scientist with experience in numerous projects, I’ve learned that the key is to start with the problem, not the solution. Just like a business venture, you don’t start with a solution and try to sell it. Instead, you start with the core problem and develop a solution for it. The days of “Build it and they will come” are long gone!

For example, the founders of YouTube identified a problem in the early 2000s: there was no platform to share video clips. So they built YouTube to solve this problem. Similarly, during the onset of the COVID-19 pandemic, there was a need to understand how the virus was spreading geographically. A PhD student at Johns Hopkins University developed a famous dashboard to solve this problem, which is now being used by governments and agencies around the world.

How can I find my ideas from ?

To find inspiration for data analytics projects, it’s important to look at what problems others are trying to solve. This can be through reading blog posts or research papers, or checking out platforms like Tableau Public or GitHub. Without investing time in understanding the problems that can be solved with data analytics, you may never reach your full potential in actually solving those problems.

Once you have identified a problem to solve, the next step is to define your project’s scope and objectives. This will help you stay focused and on track as you move forward with your project. From there, you can start to gather and clean your data, and then move on to the analysis and visualization stages..

Remember, starting a data analytics project is not about the data set, it’s about the problem you are trying to solve. By beginning with the problem and following a structured approach, you can successfully complete your portfolio project and showcase your skills to potential employers or clients.

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