Data Warehousing, Data Mining, & OLAP, written by Alex Berson and Stephen J. Smith (Computing McGraw-Hill 1997), focuses on data delivery as a top priority in business computing today. The authors use the forward to specify the three areas of data warehousing to be covered in the book as 1) bringing data necessary for enhancing traditional information presentation technologies into a single source, 2) supporting online analytical processing (OLAP), and 3) the newest data delivery engine, Data Mining.
The second section, Data Warehousing, begins by detailing data warehousing components and the processes of building a data warehouse. This section of the book details mapping the warehouse to the parallel processing architectures, selecting database schemas for decision support, the process of extracting, cleaning, and transforming data, and describes meta data as a key component of supporting the knowledge workers. The chapters go into tremendous details, discussing tool requirements and offering a look at tool-by-tool vendor-based solutions.
data warehousing data mining and olap alex berson ebook free 15
The Business Analysis section of this book begins by breaking reporting and query tools into categories including reporting tools, managed query tools, executive information system (EIS) tools, OLAP tools, and data mining tools. The authors talk about the need for developing reporting applications and then discuss many of the most recognized reporting and querying tools on the market today. The chapters in this section also detail OLAP (what it is and and why it is necessary), introduces patterns and models for business analysis, explains different types of statistical analysis, and delves briefly into the technologies of expert systems and artificial intelligence.
The fourth section, Data Mining, introduces the topic by discussing its motivation, measuring its effectiveness, and by defining the difference between discovery and prediction. The first chapter in this section talks about the state of the data mining industry and compares the present technologies to that of days in the recent past. The rest of the chapters in this section discuss decision trees, neural networks, genetic algorithms and rule induction. The section wraps up by helping the reader to select and use the right tools.
I was sometimes asked by people who wanted to learn data warehousing to recommend a book for them. Some of them are database administrators/data architects (on various platforms) and some are developers (application developers and database developers). They know how to write SQL. They know how to create tables. They know how to query data. They are looking for a basic data warehousing book, which is practical and aimed for beginners. A book that can be used by new starters to build their first data warehouse, and the BI on top of it. A book that contains all the essential topics such as methodology, architecture, data modelling, ETL, data quality, reports, cubes and BI. A book that contains examples and illustrations from real projects which are easy to understand. For this reason I wrote a data warehousing book: Building a Data Warehouse: with Examples on SQL Server (#12).
This definitive, up-to-the-minute reference provides strategic, theoretical and practical insight into three of the most promising information management technologies--data warehousing, on line analytical processing (OLAP), and data mining--showing how these technologies can work together to create a new class of information delivery system: the Information Factory. It comprehensively covers data warehouse design (using various approaches, models and indexing techniques), relational data base mining, data warehousing on the Web, and data replication. Several chapters discuss application development with popular OLAP tools.
\r \tThis definitive, up-to-the-minute reference provides strategic, theoretical and practical insight into three of the most promising information management technologies--data warehousing, on line analytical processing (OLAP), and data mining--showing how these technologies can work together to create a new class of information delivery system: the Information Factory. It comprehensively covers data warehouse design (using various approaches, models and indexing techniques), relational data base mining, data warehousing on the Web, and data replication. Several chapters discuss application development with popular OLAP tools. 2ff7e9595c
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