Foundations of Relational Databases
Querying Across Tables
The Course Covers the following topics
1. Foundations of Relational Databases
2. Retrieving Data
3. Querying Across Tables
4. Creating, Updating, and Deleting
5. The Schema Evolves
6. Wrapping Up SQL Fundamentals
5 Reasons Why You Should Learn SQL
Structured Query Language, or what’s more commonly known as SQL, is a special-purpose programming language that’s used to interact with databases. It works by analyzing and understanding databases consisting of fields of data within tables.
SQL has roots dating back to the early 1970s, during which IBM engineers Donald Chamberlin and Raymond Boyce designed the initial version to the manipulate and retrieve data stored in the company’s database system. The two pioneers of SQL called their new language SEQUEL, although they were later forced to change it due to trademark issues. SQL has since become an official standard for the American National Standards Institute (ANSI) and the International Organization for Standardization (ISO).
#1) Data Mining
Learning SQL will allow you to mine data with greater efficiency. Using basic queries you can identify specific data at time intervals, view update events, monitor table activity, and much more. This alone should be reason enough to take the initiative and learn SQL.
#2) SQL Programmers in High Demand
#3) Data Manipulation
SQL is particularly effective at data manipulation. Because it allows you to see the exact data and how it works, you’ll have an easier time testing and manipulating the data. Furthermore, data stored in SQL is dynamic, meaning it can me modified and manipulated at any time using some basic queries.
#4) Combine Data from Multiple Sources
Combining data from two or more sources can be time-consuming and downright daunting task. However, SQL makes the process a breeze by supporting simple “merges” in which the specified fields or entire databases are combined.
#5) Manage Large Pools of Data
Still searching for a practical way to manage large datasets? Traditional spreadsheets can be used to manage small-to-medium-sized pools of data, but you’ll need a different solution when handling excessively large records. Thankfully, this is an area in which SQL shines: whether it’s 1,000 records or 100 million, SQL is fully equipped to manage datapools of virtually all sizes.