Can someone help me out with project for Data Management. I need some topics that I could use for my thesis/hypothesis (with a lot of information)

I had death rates as my topic but my teacher said he does not approve of it because the statistics for it is too easy because you can just look at official sites and gather from there. I don't know what other topics there are...

Thank you!

Divorce rates, high school graduation rates, welfare rates are just a few you could consider.

Of course, I'd be happy to help you find some alternative topics for your thesis/hypothesis in the field of data management. Here are a few ideas that might be more suitable:

1. Customer churn prediction: Analyzing customer behaviors and data to predict and prevent customer churn in a particular industry.
- Explanation: You can explore data from a company's customer base and use predictive analytics techniques to identify factors that indicate a higher likelihood of customer churn.

2. Sentiment analysis on social media data: Analyzing social media posts to understand public sentiment towards a specific product, brand, or event.
- Explanation: You can collect and analyze data from social media platforms, such as Twitter or Facebook, using natural language processing techniques to detect sentiment and understand people's opinions.

3. Fraud detection in financial transactions: Developing a model that detects anomalous patterns in financial transactions to identify fraudulent activities.
- Explanation: You can analyze transactional data from financial institutions, apply machine learning algorithms, and construct models to identify potentially fraudulent activities and patterns.

4. Recommendation system for personalized content: Building a recommendation engine that suggests personalized content (e.g., movies, books, articles) to users based on their preferences and behaviors.
- Explanation: You can collect and analyze user data, such as browsing history or past interactions, to create personalized recommendations using machine learning techniques like collaborative filtering or content-based filtering.

5. Predictive maintenance in manufacturing: Using sensor data and machine learning algorithms to predict equipment failures and recommend maintenance actions to minimize downtime.
- Explanation: You can collect and analyze sensor data from manufacturing equipment, apply predictive modeling to identify patterns of failure, and develop a maintenance strategy to reduce unplanned downtime.

Remember, data management is a broad field, so feel free to explore other areas that interest you. To gather information for your chosen topic, you can utilize various data sources such as public datasets, surveys, interviews, or focus groups. Additionally, consider using relevant academic databases to find scholarly articles that discuss similar topics for a comprehensive understanding of the subject matter.