Karamagi R. Data Mining and Data Warehouse 2020

Textbook in PDF format

This book shall train you to collect data from different sources, and discover knowledge. The book aims to teach you to group data into a Data Warehouse for analysis and reporting. The book further explains how to discover patters that can be discovered from the data by learning from historical datasets using Machine Learning Algorithms. The book provides you with knowledge of general concepts and technologies of Data Manipulation using algorithms and data processing tools. This book shall train you how to recognize problems that can be solved by using Data Warehouse and Data Mining Techniques.
Expected Outcomes
At the end of this bok, you will acquire knowledge, skills and competencies that will enable you to:
Know and understand general concepts and technologies of Data Mining.
Develop Data Warehouses and run OLAP queries for various applications analysis
Apply Machine Learning Algorithms in datasets for prediction and description of various problems
Recognize problems that can be solved by Data Mining Techniques
Learning Objectives
Knowledge Discovery in Database
Knowledge Discovery in Databases Flow and Data Types (Audio, Video, Blobs, Vectors, Lists) and Distributed Database
Data Cleaning - (Extraction, Translation and Loading – (ETL))
Data Warehouse
Data warehouse schema (Star and Snowflakes) and Data Cubes and Data Mart
Data Warehouse Operations
Data Warehouse Operations/ (Roll up, Dice, Roll down) and (On-line Analytical Processing (OLAP) and On-line Transaction Processing (OLTP)
Data Mining
Data Mining Tools, Platforms and Applications and Statistical Data Mining and Datasets (Linked Datasets, Open Datasets, Dataset Discovery/Sharing)
Machine Learning Algorithms
Machine Learning Algorithms Types, Training, Validation, Comparison
Association – Association Rules
Clustering – K Means, Hierarchical Clustering
Classification – Decision Trees, Random Forest, Boosting
Data Mining Application
Deep Learning – Neural Networks, SVM