Data Warehousing and Mining Notes
Subject Overview
Full unit-wise notes for Data Warehousing and Mining (BCA Semester 5) are coming soon. WhatsApp us to request the latest available study material for this subject.
Subject at a glance
TBA
Units
TBA
Topics
TBA
Credits
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Unit-wise Syllabus
1 units — click WhatsApp below to get the full notes for each
Unit 1: Notes coming soon
Detailed unit-wise syllabus and notes for this subject are being added. WhatsApp us for the latest available study material in the meantime.
Why Data Warehousing and Mining Matters
Data warehousing and mining cover how organisations collect data from many sources into a warehouse and then discover patterns in it, using techniques such as association rules, classification and clustering. The subject leads naturally to careers in business intelligence, data analytics and data science. Detailed unit-wise notes are being added; the Data Mining unit of Database Management Systems-II introduces the core ideas.
How to Prepare for Data Warehousing and Mining
- Revise the Apriori algorithm and decision tree material from Database Management Systems-II.
- Learn the difference between OLTP and OLAP systems and between a database and a data warehouse.
- Practise basic mining tasks in a tool such as Weka or Python.
Data Warehousing and Mining: Frequently Asked Questions
What is the difference between a database and a data warehouse?
An operational database supports day-to-day transactions, while a data warehouse stores integrated historical data from many sources for analysis and reporting.
What is data mining?
Data mining is the process of discovering useful patterns, such as associations, classes and clusters, in large data sets.