Khan, Arshad

Business Intelligence and Data Analysis in the Age of AI

Campesato, Oswald

Beginning Python 3 with Claude 3

Fortino, Andres

Case Studies in Excel, R, and ChatGPT

Data Analysis for Business Decisions

Zherlitsyn, Dmytro

Financial Data Analysis Using Python

A Prompt-based Exploration of LLMs

Large Language Models for Developers

Beginning Python 3 with Grok 2

Herman, Erik

Using Analytics and Case Studies

Data Science for Decision Makers

Goralski, Walter

Understanding AI, IoT, 6G and The Infrastructure Revolution

Erik, Herman L.

Theory, Applications and Ethics

AI Revealed

CAMPESATO, OSWALD

CSS3 and SVG with Meta AI

500 Questions, Answers, & Tips

Business Intelligence & Data Warehousing Simplified

Chapter 21 Tool Selection and Data Mining

Frontmatter

Contents

Preface

Chapter 1 Introduction

Chapter 2 Business Intelligence Application and Future

Chapter 3 Data Warehousing Evolution and Fundamentals

Chapter 4 Data Warehouse Types and Design Objectives

Chapter 5 Growth Contributors

Chapter 6 Data Warehouse Characteristics

Chapter 7 Star Schema

Chapter 8 Data Warehouse Process

Chapter 9 Architecture

Chapter 10 Metadata

Chapter 11 Source Data

Chapter 12 Data Conversion and Migration

Chapter 13 Data Quality

Chapter 14 ETL Process

Chapter 15 ETL Issues, Tools, and ELT

Chapter 16 Data Storage

Chapter 17 Data Modeling

Chapter 18 Data Warehouse Engine and Operating System

Chapter 19 Hardware

Chapter 20 Data Access

Chapter 22 Features of Front- End Tools

Chapter 23 Data Marts

Chapter 24 Implementation Approaches

Chapter 25 Inmon versus Kimball

Chapter 26 Multidimensionality

Chapter 27 Facts and Dimensions

Chapter 28 OLAP

Chapter 29 OLAP models

Chapter 30 Multidimensional Database

Chapter 31 OLAP: Comparisons, Tools, and Vendors

Chapter 32 Planning for the Data Warehouse Initiative

Chapter 33 Implementation Prerequisites and Approach

Chapter 34 Common Mistakes and Risks

Chapter 35 Project Resources

Chapter 36 Project Definition and Initiation

Chapter 37 Project Planning

Chapter 38 Analysis

Chapter 39 Analysis: Additional Topics

Chapter 40 Design

Chapter 41 Design: Data Modeling and OLAP Design

Chapter 42 Design: Additional Topics

Chapter 43 Documentation

Chapter 44 Development

Chapter 45 Testing and Training

Chapter 46 Deployment and Operation

Chapter 47 Trends

Index

This book targets business and IT professionals who need an introduction to business intelligence and data warehousing through a simple question/answer format. Organized into 30 odd chapters, each on a different topic, the book contains approximately 500 questions with answers and tips. Topics include evolution and fundamentals, characteristics and process, architecture and objects, metadata, data conversion, ETL, data storage, infrastructure, data access, data marts, implementation approaches, planning, design, Inmon vs.

This book targets business and IT professionals who need an introduction to business intelligence and data warehousing through a simple question/answer format....

Chapter 21 Tool Selection and Data Mining - Chapter 21 Tool...

Chapter 21 Tool Selection and Data Mining

Format

Chapter 21 Tool Selection and Data Mining

Arshad Khan

Arshad Khan

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