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Prompt: Briefly summarize the what you consider to be the three (3) most important things you learned in this course. Database Design Fundamentals: Learning how to design a database schema. This involved  understanding entity-relationship modeling, normalization techniques, and the significance of maintaining data integrity via appropriate schema design. SQL Proficiency: Gaining proficiency in SQL including writing complex queries to retrieve, manipulate, and manage data stored in relational databases. Understanding SQL's syntax, data manipulation capabilities, and its role in database management. Database Management Concepts: Understanding concepts related to database management systems, such as transaction management, concurrency control, indexing, query optimization, and data security. These concepts are vital for efficient and secure database operation and management.

Prompt for this week's journal entry. Compare MongoDB with MySQL.  What are some similarities?  What are some differences?  When would you choose one over the other?  Similarities: Data Storage: Both MongoDB and MySQL store data persistently on disk. Indexes: Both databases support indexes for improving query performance. Data Manipulation: Both provide capabilities for inserting, updating, deleting, and querying data. Differences: Data Model: MongoDB is a NoSQL database, while MySQL is a relational database. MongoDB stores data in flexible, schema-less documents (JSON-like format), while MySQL stores data in structured tables with predefined schemas. Query Language: MongoDB uses a query language similar to JavaScript called the MongoDB Query Language (MQL), while MySQL uses SQL (Structured Query Language). Schema: MongoDB is schema-less, allowing for dynamic and flexible schemas, while MySQL requires a predefined schema for each table. Scaling: MongoDB is designed t...

 Summarize what you've learned this week: This week I learned to integrate sql, mysql workbench, html, java, spring, and Java Database Connectivity (jdbc) to make a web application. This was a web application that hosted prescriptions for patients.

Prompt: The web site "Use the Index Luke" has a page on "slow indexes".   https://use-the-index-luke.com/sql/anatomy/slow-indexesLinks to an external site.  If indexes are supposed to speed up performance of query,  what does the author mean by a slow index?  Response:  When mentioning "slow indexes" the author refers to indexes reducing the speed of a database. A prime example that's used is long-range indexes. These indexes traverse a table looking for matching indexes. If there are multiple matching indexes, the traversal and retrieval is done for each matching index. This means that the table is accessed each time. In such a case, indexes become slow, thus defeating their purpose.