CSU Monterey Bay Learning Journal

Five things i've learned so far in the course so far... 1. Relational Schema Design and Normalization How to structure data into tables, define their primary and foreign keys, and apply normalization rules to eliminate redundancy and ensure data integrity. 2. Basic CRUD operations with SQL Writing SELECT , INSERT , UPDATE , and DELETE statements to retrieve and manipulate data, including filtering with WHERE , sorting with ORDER BY , and limiting results with LIMIT 3. Joins and Set Operations Combining data across multiple tables using INNER JOIN , LEFT/RIGHT JOIN , as well as operations like UNION and EXCEPT to merge or compare result sets. 4. Aggregate Functions and Grouping Using COUNT() , SUM() , AVG() , MIN() , MAX() along with GROUP BY and HAVING clauses to summarize statistics and filter groups. 5. Database Design Designing databases by creating ER diagrams using primary and foreign key relationships between entities. Three questions I have regarding databases... 1. Scali...

A view is essentially a saved query that you can treat like a table. Under the hood, the database doesn’t necessarily store the view’s data separately; it re-runs the defining SELECT every time you reference it  The similarities to a table are the Rows and Column, you SELECT from a view similar as to how you would do it from a table. Join and filters also looks the same. The key differences between the two... Aspect Tables View Storage Physically stores data on disk. Usually virtual (query results are generated on the fly). Some DBs support materialized views. Primary Key Defined directly on the table; enforced. No inherent PK—though some systems allow unique indexes on views, most treat them as keyless. Updatability Always updatable (barring triggers/locks). Only if certain rules are met: Comparing SQL with Java there are notable differences a...

 1. The key differences between relational tables and spread sheets is it's structure and schema. On a spreadsheet you can mix data types in a column/cell because there are no enforced schema where as a relational table has declared data types for their columns, so age would have to be an integer value. There's also no built in validation for types or wrong data type in spread sheet whereas a relational table would reject invalid data. The biggest one would be the ability to query. I've done queries on large datasets via excel before and it takes forever and isn't maintainable on a bigger scale versus relational tables where I can query and cross reference specific data from different tables to get the results quick. 2. From what I've learned so far, investing in a database means data integrity and consistency via schemas. From personal experience, I know that database are often compatible with other tools such as tableau, power bi, and excel. All of which are great...