14. What Is SQL?
SQL (Structured Query Language) is the standard language used to communicate with databases. It allows analysts to retrieve, manipulate, and analyze data efficiently. In healthcare analytics, SQL is essential for extracting claims, encounters, and member data from large databases.
15. What Is a Database?
A database is an organized collection of data stored electronically. In healthcare, common databases include claims databases, electronic health records (EHR), and data warehouses.
16. What Is a Data Warehouse?
A data warehouse is a centralized repository that stores large amounts of historical data from multiple sources. It is optimized for analysis and reporting rather than daily transactions. Healthcare data warehouses often combine claims, clinical, and member data for analytics.
17. What Is NoSQL?
NoSQL refers to non-relational databases designed to handle large volumes of unstructured or semi-structured data. They are often used when data does not fit neatly into traditional table structures (e.g., clinical notes, images, or real-time data).
18. What Is an Aggregate Function?
Aggregate functions in SQL perform calculations on a set of values and return a single value. Common examples include:
- COUNT() – counts rows
- SUM() – adds values
- AVG() – calculates average
- MAX() / MIN() – finds highest/lowest values
These are heavily used in healthcare reporting (e.g., average cost per member, number of chronic conditions).
19. INNER JOIN vs OUTER JOIN
- INNER JOIN: Returns only records that have matching values in both tables.
- OUTER JOIN: Returns records from one or both tables even if there is no match.
- LEFT OUTER JOIN: Returns all records from the left table
- RIGHT OUTER JOIN: Returns all records from the right table
- FULL OUTER JOIN: Returns all records from both tables
Mastering JOINs is critical for combining member, claims, and diagnosis data.
20. Nested vs Correlated Subquery
- Nested Subquery: A subquery inside another query that runs independently.
- Correlated Subquery: A subquery that references columns from the outer query and runs repeatedly for each row.
Understanding these helps write efficient, complex healthcare analytics queries.