1 Introduction

2 Theoretical Foundation and Algorithms of Reinforcement Learning  
2.1 Markov Decision Process  
2.2 Basic Techniques  
2.3 Advanced Techniques  

3 Data System Optimization  
3.1 Data Organization  
3.2 Scheduling  
3.3 Tuning  
3.4 Indexing  
3.5 Query Optimization  
3.6 Cache Management  

4 Data Analytics Applications  
4.1 Data Preparation  
4.2 Healthcare  
4.3 Fintech  
4.4 E-Commerce  
4.5 Other Applications  

5 Open Challenges and Future Directions  
5.1 Open Challenges For System Optimization  
5.2 Open Challenges For Applications  
5.3 Future Research Directions  

6 Conclusions