How do I find the most impactful use cases and have quick wins? Some guidelines / potential questions to give you the perspective.
I have participated in Kaggle and achieved a good ranking. I have a good understanding of Data Science, Let's build solutions. If all you have is a hammer, everything looks like a nail. Let's see beyond Kaggle what things we need to understand.
Solution - Collaborate work with your business to understand, and get their vision, and priorities. Your use case has to be aligned with business needs / current challenges they are solving. A measurable ROI will always help to prioritize and deploy it to production.
Solution - Apply your domain lens, Data science lens, and take a transparent decision. Don't over-engineer for sake of it. If it makes sense do it.
Data Availability and Readiness #3 - If the first two parts are true, you spot problems, you see the feasibility of data science, evaluate what minimum you can build with the available data
Solution - Work with your Data/BI team, partner to build the required data for your MVP solution. The gap between reality vs expectations, What more data do you need to add more, integrate into the system you will get the clarity in this step.
You need to potentially collaborate with the business, product, and data team effectively to spot a successful opportunity. A lot of collaboration, and teamwork to spot the best use cases. Apply these questions and spot your opportunities.
Kaggle and other learning platforms work on the aspect of Feature Engineering, Model building, Beyond Kaggle this is the reality you need to look to apply Data Science in practice. Data science is #Teamwork. You need multiple lenses and participants to work to build impactful use cases.
Feel free to add other questions/guidelines as well.
Keep Exploring!!
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