🛠️ Data Warehousing Tools

📄 Metadata → Describe the structure and some meaning about data
📌 Metadata is “data about data”, describing its source, structure, transformation rules, etc.

📊 OLAP → Supports multidimensional data and enables users to view the same data in different ways using multiple dimensions
📌 OLAP allows users to perform operations like drill-down, roll-up, and slice & dice on multidimensional data.

🧱 Hadoop → Breaks a big data problem down into sub-problems, distributes them among thousands of inexpensive processing nodes, and combines results
📌 Hadoop uses the MapReduce model and is ideal for processing huge datasets across distributed systems.

C. Data mart → III

Data Mart

• A subset of a data warehouse

• Focused on a specific department or group (e.g., sales, HR)

• Allows faster access to relevant data

➡️ Application III: A summarized or highly focused portion of an organization’s database for a specific population of users

D. Data mining → II

Data Mining

• Extracts patterns and knowledge from large datasets

• Often used for predictive analysis (e.g., customer behavior, fraud detection)

➡️ Application II: Finds hidden patterns in large databases and infers rules to predict future behavior