- Categories
- Acceptance Testing
- Agile Business Analysis
- Best Practices
- Business Analysis and Systems Analysis
- Business Analysis Planning and Monitoring
- Business Process Modeling (BPM)
- Business Rules
- Conducting Meetings
- Data Modeling, Data Analysis, Data Mining
- Enterprise Analysis
- Facilitation
- IIBA, BABOK, and CBAP certification
- JAD
- Making Teams and Virtual Teams Work
- Problem Analysis, Problem Solving
- Process Analysis
- Prototyping
- Request for Proposal (RFP)
- Requirements Analysis
- Requirements Documentation
- Requirements Elicitation
- Requirements Engineering
- Requirements Management
- Requirements Specifications
- Requirements Traceability
- Requirements Validation
- Software Testing and Test Cases
- System Development Life Cycles
- Test Data Engineering
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- Testing Tools
- Testing Web Applications and Web Services
- Unified Modeling Language (UML)
- Usability
- Use Cases and User Stories
- User Interfaces
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Business Analysis for Information Technology
Books and Selected Products
Data Mining: Introductory and Advanced Topics
Prentice Hall
September 2002
Paperback, 315 pages
ISBN: 0130888923
On-Site and On-Line Training Courses for Business Analysts How to Build Business Data Models
How to Model, Analyze, and Improve Business Data
Description
For courses in data mining.
Thorough in its coverage from basic to advanced topics, this text presents the algorithms and techniques used in data mining. It introduces readers to various data mining concepts and algorithms.
Features
Features
- A database perspective is used throughout.
Provides students with a focused discussion of algorithms, data structures, data types, and complexity of algorithms and space.
- Clearly written algorithms.
Enables students to better understand techniques.
- An emphasis on the use of data mining concepts in real–world applications with large database components.
- Appendix providing overview of available data mining products.
- Strategic text organization of four major sections: Introduction, Core Topics, Advanced Topics, and Products.
Enables instructors to choose portions of the book to cover in a limited period of time.
From the back cover:
Backcover Copy
Margaret Dunham offers the experienced data base professional or graduate level Computer Science student an introduction to the full spectrum of Data Mining concepts and algorithms. Using a database perspective throughout, Professor Dunham examines algorithms, data structures, data types, and complexity of algorithms and space. This text emphasizes the use of data mining concepts in real–world applications with large database components.
KEY FEATURES:- Covers advanced topics such as Web Mining and Spatial/Temporal mining
- Includes succinct coverage of Data Warehousing, OLAP, Multidimensional Data, and Preprocessing
- Provides case studies
- Offers clearly written algorithms to better understand techniques
- Includes a reference on how to use Prototypes and DM products
About the Author:
Author Bios
Margaret H. Dunham received the B.A. and the M.S. in mathematics from Miami University in Oxford, Ohio. She earned the Ph.D. degree in computer science from Southern Methodist University. Professor Dunham‘s research interests encompass main memory databases, data mining, temporal databases, and mobile computing. She is currently an Associate Editor for IEEE Transactions on Knowledge and Data Engineering. She has published numerous technical papers in such research areas as database concurrency control and recovery, database machines, main memory databases, and mobile computing.
Business Analysis for Information Technology deals
Business Analysis for Information Technology products
Hammermill Laser Print Copy/Laser Paper, 98 Brightness, 24lb, Letter Size (8.5 x 11), White, 500 Sheets (10460–4)
Office Impressions Copy Paper 8 1/2" x 11" case, White 5,000 sheets
