Probably the hardest part of any Data Science project is coming up with an original but feasible idea. An expert looking for such an idea can easily fall into the "dataset trap". They spend many hours looking through existing datasets and trying to come up with interesting new ideas. But this approach has one problem. The fact is that someone who only looks at existing datasets (with Kaggle, Google Datasets, FiveThirtyEight) limits their creativity by seeing only a small set of tasks that the datasets they study are focused on.
Sometimes we examine the datasets of interest. If we build a successful model for data from Kaggle, for which countless models have already been created, there will be no practical value. On the other hand, it allows us to learn something new. But data scientists are people who strive to create something new, unique, something that can bring real benefit to the world.
How do you generate new ideas? In order to find the answer to this question, we combined our own experience and the results of creativity research. This led to the fact that we were able to form 5 questions, the answers to which help to find new ideas. As you search for answers to the questions presented here, you will walk the path of generating new ideas and will be able to use your creative potential to its fullest. As a result, you will have new unique ideas that you can implement in your Data Science projects.
When you think about starting a new project, you have an intention or purpose in mind. First, you need to find the answer to the question of why you want to create another project in the field of data science. Having a rough outline of what kind of goal you are aiming for will help you focus on finding an idea. So think about what you are going to create a project for. Here are some options:
There are three main reasons to think about this question:
The main source of inspiration is reading. As you search for an idea, you can find interesting topics by reading various materials:
If we talk about other sources of inspiration, then inspiration can be found in everyday life. Whenever you are interested in a question, think about whether you can answer that question using data manipulation techniques. If something interests you, take a moment and study the relevant data.
How do you generate project ideas based on the above sources of inspiration? Neuroscientists have identified three distinct psychological processes associated with generating ideas:
Once you have decided on the general direction of research, you will need to search for data that will allow you to understand how to implement your idea in the form of a Data Science project. This is extremely important in determining whether an idea will succeed. In answering the question in the title of this section, it is worth considering the possibility of having what you need in existing data stores. You may have to collect the necessary data yourself, which complicates the task. So here's an overview of data sources:
If you are unable to find data that can help you implement your project idea, reformulate the idea. Try to get an idea from the original idea that can be implemented using the data you have. In the meantime, ask yourself a question about why you are not able to find the data you need. What is wrong with the area you are interested in? What can you do about it? Answers to these questions alone can lead to the emergence of a new Data Science project.
So you have a fantastic idea! But can it be implemented? Go through the steps in the idea generation process again. Think about what you want to achieve (question # 1), whether you are interested in the chosen area (question # 2), if you have experience in it(question # 3), do you have the data you need to implement the idea (question # 4). Now you need to determine the following: do you have the skills necessary to implement the idea and to achieve the goal?
It is important to take into account such a factor as the time you plan to spend on this project. You are probably not going to write a doctoral dissertation on your chosen topic. Therefore, the project that you will do within the framework of the found idea, perhaps, will affect only a certain part of it. Maybe it will consist only of learning something new that you will need to implement the idea in the future.
After you go through the 5 steps above for generating an idea, you should have a question that you can and want to answer, spending as much time on it as you are willing to spend on achieving your goal.
We believe that this material will inspire you to create cool new data science projects. Good luck with your development!
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