Data Warehousing And Mining
MP4 |
Video: h264, 1920x1080 |
Audio: AAC, 44.1 KHz
Language: English |
Size: 1.02 GB |
Duration: 1h 24m
From data storage to knowledge discovery, ETL, OLTP, Clustering and LZW algorithm
What you'll learn
what is data warehousing and mining and why it is needed
Get in-depth knowledge of its methods and algorithms
learn concepts like ETL, DM schemas, OLTP, Clustering and more
understanding of complex topics with real life examples.
Requirements
just the basic knowledge of IT and rest you'll learn here.
Description
From Data Storage to Knowledge DiscoveryExplore the core concepts behind how data is organised, stored, and analysed. This theory-driven course covers data warehouse architecture, ETL processes, OLAP, and fundamental mining techniques like classification, clustering, and association. Designed for curious CS students and beginners who want to understand how and why data systems work before touching the tools.No coding, just concepts. Learn the principles behind building data warehouses and extracting meaningful patterns from data. We'll break down architectures, data models, mining algorithms, and evaluation methods in plain language. Perfect for CS beginners who want a strong conceptual foundation in data analytics.The Theory Behind Data-Driven DecisionsUnderstand the science behind big data. This course walks you through warehouse design principles, data modelling, multidimensional analysis, and the key algorithms used in data mining. Built for computer science students who are curious about analytics but want to master the theory first.Every company is sitting on a goldmine of data. In this course you'll learn how to build the warehouse to store it, and use mining tools to dig out the patterns that matter. Built for beginners in computer science who are curious about AI, analytics, and how data drives the world.Course focus:Concepts: DW architecture, schemas, ETL, OLAPTechniques: Classification, Clustering, Association, Prediction Thinking: How data turns into knowledge
For curious beginners and students of computer science who want to turn raw data into real insight.
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