Data Analysis
The Data Warehouse Lifecycle Toolkit: Expert Methods for Designing, Developing, and Deploying Data Warehouses
In his bestselling book, "The Data Warehouse Toolkit", Ralph Kimball showed you how to use dimensional modeling to design effective and usable data warehouses. Now, he carries these techniques to the larger issues of delivering complete data marts and data warehouses.
Data Warehouse Design Solutions
The authors of Data Warehouse Design Solutions share their expertise in designing successful data warehouses and concentrate on understanding business processes within a variety of industries.
The Data Warehouse Toolkit: Practical Techniques for Building Dimensional Data Warehouses
Employing many real-life case studies of data warehouses, Ralph Kimball provides clear-cut guidelines on how to model data and design data warehouses to support advanced multidimensional decision support systems.
Market Models: A Guide to Financial Data Analysis
Market Models provides an authoritative and up-to-date treatment of the use of market data to develop models for financial analysis. Written by a leading figure in the field of financial data analysis, this book is the first of its kind to address the vital techniques required for model selection and development. Model developers are faced with many decisions, about the pricing, the data, the statistical methodology and the calibration and testing of the model prior to implementation. It is important to make the right choices and Carol Alexander's clear exposition provides valuable insights at every stage.
SPSS 11.0 Guide to Data Analysis
The goal of this book is to provide an unintimidating introduction to data analysis and to SPSS. This edition has been substantially revised to incorporate new data files that focus on topics that interest today's students—in particular, the role of the Internet in society. The book can be used either as a supplementary text or as a primary text in an introductory course in data analysis. It is designed for use with SPSS 11.0, including the Student Version Data Files.
Intelligent Data Analysis
Provides a detailed introduction of the key classes of intelligent data analysis methods and a valuable source of reference for professionals concerned with modern data analysis.
Guerilla Data Analysis Using Microsoft Excel
Bill Jelen uses his combined experience and analytical ingenuity to de-mystify the arduous task of dealing with downloaded data. He uses real-life examples of real-life management requests, and then walks you through the maze of Excel tools and formulas that not only cuts valuable time out of the process, but teaches you in plain English how to overcome the most common analytical obstacles.
Bayesian Data Analysis, Second Edition
Bayesian Data Analysis describes how to conceptualize, perform, and critique statistical analyses from a Bayesian perspective. Using examples largely from the authors' own experiences, the book focuses on modern computational tools and obtains inferences using computer simulations. Its unique features include thorough discussions of the methods for checking Bayesian models and the role of the design of data collection in influencing Bayesian statistical analysis.Bayesian Data Analysis offers the practicing statistician singular guidance on all aspects of the subject.
Mastering the SAP Business Information Warehouse
Written by the leading experts in the field, this comprehensive guide shows you how to implement the SAP Business Information Warehouse (BW) and create useful applications for business analysis of company-wide data. You’ll quickly learn how to design, build, analyze, and administer the data and information in the SAP BW component. The authors present the material in a way that reflects the process an organization goes through during a software implementation. They begin with an introduction to the fundamentals of data warehousing and business intelligence, helping you determine if SAP BW is right for your organization. The book then focuses on the business content and options available when trying to deliver value from the data stored in the SAP BW. And it includes a methodology for implementing the BW, such as data modeling and techniques for capturing and transforming data.
The Elements of Statistical Learning: Data Mining, Inference, and Prediction
Describes important statistical ideas in machine learning, data mining, and bioinformatics. Covers a broad range, from supervised learning (prediction), to unsupervised learning, including classification trees, neural networks, and support vector machines. DLC: Supervised learning (Machine learning).
Exploratory Data Analysis in Empirical Research
Facing rapidly growing challenges in empirical research, this volume presents a selection of new methods and approaches in the field of Exploratory Data Analysis. The interested reader will find numerous ideas and examples for cross disciplinary applications of classification and data analysis methods in fields such as data and web mining, medicine and biological sciences as well as marketing, finance and management sciences.
SAS System for Forecasting Time Series
Written in an easy-to-read style, this comprehensive book shows how the SAS System performs multivariate time series analysis, covering the advanced SAS procedures STATSPACE, ARIMA, and SPECTRA. The authors demonstrate the interrelationship of SAS/ETS procedures and then explain how the choice of a procedure depends on the data to be analyzed and the results desired. Emphasis is placed on the correct interpretation of output in order to draw meaningful conclusions.
Security Planning and Disaster Recovery
Proactively implement a successful security and disaster recovery plan--before a security breach occurs. Including hands- on security checklists, design maps, and sample plans, this expert resource is crucial for keeping your network safe from any outside intrusions.
Sharpening Your SAS Skills
Sharpening Your SAS Skills is an intermediate text on SAS programming and data management intended for those with some knowledge of the SAS language. It covers the most common tools used by SAS programmers and data analysts in their daily work. Designed as a quick-reference and practitioner's guide, this book will be particularly useful for those preparing for the SAS Base Programming exam. The book includes question and answers at the end of each section to reinforce the reader's knowledge of the topic and tables in each chapter that summarize the syntax and expected data. A companion Web site contains examples, extra exercises, the list and log SAS files, and the pdf/html output files.
Making Sense of Data
The author provides clear explanations that guide the reader to make timely and accurate decisions from data in almost every field of study. A step-by-step approach aids professionals in carefully analyzing data and implementing results, leading to the development of smarter business decisions. With a comprehensive collection of methods from both data analysis and data mining disciplines, this book successfully describes the issues that need to be considered, the steps that need to be taken, and appropriately treats technical topics to accomplish effective decision making from data.
Physical Database Design
Physical Database Design: the database professional's guide to exploiting indexes, views, storage, and more.
The rapidly increasing volume of information contained in relational databases places a strain on databases, performance, and maintainability, and DBAs are under greater pressure than ever to optimize database structure for system performance and administration.
Physical Database Design discusses the concept of how physical structures of databases affect performance and includes specific examples, guidelines, and best and worst practices for a variety of DBMSs and configurations. Something as simple as improving the table index design has a profound impact on performance. Every form of relational database, such as Online Transaction Processing (OLTP), Enterprise Resource Management (ERP), Data Mining (DM), or Management Resource Planning (MRP), can be improved using these methods.
Data Preparation for Analytics Using SAS
This book was designed with businesses in mind, but the basic ideas apply easily to all sorts of research endeavors in which decision makers must gather and use data that were initially collected for some other purpose. In my opinion, the book has two great strengths. First, the technical material in the book is wrapped in a sense of purpose and an awareness of the importance of context. The second great strength is the book's organization and clarity. . . . The development of ideas and examples is clear and orderly, exactly as it should be in a work of this type. --Michael T. Brannick PhD, Professor Graduate Program Director, Psychology Department, University of South Florida
Smart Enough Systems
Smart Enough Systems: How to Deliver Competitive Advantage by Automating Hidden Decisions
- How current technologies fail to address critical issues in automating operational decision-making
- How companies can use the computer-based systems they have in place rather than purchasing new ones to build smarter systems
- How these systems can help companies thrive through Enterprise Decision Management (EDM) - designing, deploying and managing automated decisions
For more information visit http://www.smartenoughsystems.com/wp/main.
Data Mining VIII: Data, Text and Web Mining and their Business Applications
Bringing together papers presented at the Eighth International Conference on Data, Text and Web Mining and their Business Applications, this book addresses the new developments in the important field of information engineering. The book, edited by A. Zanasi, (TEMIS Text Mining Solutions, Italy, Italy), C. A. Brebbia (Wessex Institute of Technology, Southampton, UK) and N. F. F. Ebecken (COPPE/Federal University of Rio de Janeiro, Brazil) features contributions on categorization methods; data preparation; enterprise information systems; mining environmental and geospatial data; text mining; applications in business, industry and customer relationship management; and national security.
Full contents details on the book can be found at www.witpressusa.com.
Reinventing Project Management
Reinventing Project Management: The Diamond Approach to Successful Growth & Innovation
Projects are the engines that drive innovation from idea to commercialization. In fact, the number of projects in most organizations today is expanding while operations is shrinking.. Yet, since many companies still focus on operational excellence and efficiency, most projects fail—largely because conventional project management concepts cannot adapt to a dynamic business environment. Moreover, top managers neglect their company's project activity, and line managers treat all their projects alike—as part of operations.
Based on an unprecedented study of more than 600 projects in a variety of businesses and organizations across the globe, Reinventing Project Management provides a new and highly adaptive model for planning and managing projects to achieve superior business results.
Implementing Enterprise Data Warehousing
Designing complex analytical data structures is difficult enough, but to do it for an entire enterprise becomes a real challenge. This little primer provides a simple method of preparing your people for the complexity of this endeavor. This is just like opening a new restaurant where certain components have to be designed and thought out before you start to build the kitchen. You do not have to be an "expert" to build a data warehouse. A lot can be outsourced, but you do need to be able to create your own plan according to your culture's specific requirements. Some cultures take more 'informing' and 'training' than others. The pace and aggressiveness with which you unfold your plan is something that you understand best. This primer defines the data warehouse components and helps you decide when they can be done, in what order, and by how many people.
Executing Your Strategy
Why do businesses consistently fail to execute their competitive strategies? Because leaders don't identify and invest in the full range of projects and programs required to align the organization with its strategy. Moreover, even when strategy makers do break their plans down into doable chunks, they seldom work with project leaders to prioritize strategic investments and assure that needed resources are applied in priority order. And they often neglect to revise the strategic portfolio to fit the demands of a dynamic environment, or to stay connected to strategic projects through completion, as new products, services, skills and capabilities are transferred into operations.
Data Quality Assessment
Review
DATA QUALITY ASSESSMENT is an excellent book and a must read for any data quality professional. Arkady packs years of experience in data quality into comprehensive step-by-step instructions for practitioners of all levels.
--R. Michael Levin, Sr. Database Architect, Lockheed Martin
The DAMA Dictionary of Data Management
This glossary contains over 800 terms defining a common data management vocabulary for IT professionals, data stewards and business leaders. It is in pdf format embedded with links for easy navigation between terms, and delivered to you on CD-ROM. An index is included with the dictionary, which organizes the 800 terms by topic.
Oracle PL/SQL: Expert Techniques For Developers and Database Administrators
This book takes you beyond the existing solutions found in other professional and reference texts or in online documentation. Starting from PL/SQL internals that include PL/SQL program structure, internal representation, compilation, and execution, users are taught PL/SQL concepts and techniques that go way beyond SQL, such as data structure management, error management, data management, application management, and transaction management.
Enterprise Master Data Management: An SOA Approach to Managing Core Information
The book is authored by IBM data management innovators who are pioneering MDM, and within its pages they systematically introduce its key concepts and technical themes, explain its business case, and illuminate how it interrelates with and enables SOA.
