Tapping into Unstructured Data
Integrating Unstructured Data and Textual Analytics into Business Intelligence
Published on 21. December 2007
Book
Paperback/Softback
264 pages
978-0-13-236029-6 (ISBN)
Description
"The authors, the best minds on the topic, are breaking new ground. They show how every organization can realize the benefits of a system that can search and present complex ideas or data from what has been a mostly untapped source of raw data."
--Randy Chalfant, CTO, Sun Microsystems
The Definitive Guide to Unstructured Data Management and Analysis--From the World's Leading Information Management Expert
A wealth of invaluable information exists in unstructured textual form, but organizations have found it difficult or impossible to access and utilize it. This is changing rapidly: new approaches finally make it possible to glean useful knowledge from virtually any collection of unstructured data.
William H. Inmon--the father of data warehousing--and Anthony Nesavich introduce the next data revolution: unstructured data management. Inmon and Nesavich cover all you need to know to make unstructured data work for your organization. You'll learn how to bring it into your existing structured data environment, leverage existing analytical infrastructure, and implement textual analytic processing technologies to solve new problems and uncover new opportunities. Inmon and Nesavich introduce breakthrough techniques covered in no other book--including the powerful role of textual integration, new ways to integrate textual data into data warehouses, and new SQL techniques for reading and analyzing text. They also present five chapter-length, real-world case studies--demonstrating unstructured data at work in medical research, insurance, chemical manufacturing, contracting, and beyond.
This book will be indispensable to every business and technical professional trying to make sense of a large body of unstructured text: managers, database designers, data modelers, DBAs, researchers, and end users alike.
Coverage includes
What unstructured data is, and how it differs from structured data
First generation technology for handling unstructured data, from search engines to ECM--and its limitations
Integrating text so it can be analyzed with a common, colloquial vocabulary: integration engines, ontologies, glossaries, and taxonomies
Processing semistructured data: uncovering patterns, words, identifiers, and conflicts
Novel processing opportunities that arise when text is freed from context
Architecture and unstructured data: Data Warehousing 2.0
Building unstructured relational databases and linking them to structured data
Visualizations and Self-Organizing Maps (SOMs), including Compudigm and Raptor solutions
Capturing knowledge from spreadsheet data and email
Implementing and managing metadata: data models, data quality, and more
William H. Inmon is founder, president, and CTO of Inmon Data Systems. He is the father of the data warehouse concept, the corporate information factory, and the government information factory. Inmon has written 47 books on data warehouse, database, and information technology management; as well as more than 750 articles for trade journals such as Data Management Review, Byte, Datamation, and ComputerWorld. His b-eye-network.com newsletter currently reaches 55,000 people.
Anthony Nesavich worked at Inmon Data Systems, where he developed multiple reports that successfully query unstructured data.
Preface xvii
1 Unstructured Textual Data in the Organization 1
2 The Environments of Structured Data and Unstructured Data 15
3 First Generation Textual Analytics 33
4 Integrating Unstructured Text into the Structured Environment 47
5 Semistructured Data 73
6 Architecture and Textual Analytics 83
7 The Unstructured Database 95
8 Analyzing a Combination of Unstructured Data and Structured Data 113
9 Analyzing Text Through Visualization 127
10 Spreadsheets and Email 135
11 Metadata in Unstructured Data 147
12 A Methodology for Textual Analytics 163
13 Merging Unstructured Databases into the Data Warehouse 175
14 Using SQL to Analyze Text 185
15 Case Study--Textual Analytics in Medical Research 195
16 Case Study--A Database for Harmful Chemicals 203
17 Case Study--Managing Contracts Through an Unstructured Database 209
18 Case Study--Creating a Corporate Taxonomy (Glossary) 215
19 Case Study--Insurance Claims 219
Glossary 227
Index 233
--Randy Chalfant, CTO, Sun Microsystems
The Definitive Guide to Unstructured Data Management and Analysis--From the World's Leading Information Management Expert
A wealth of invaluable information exists in unstructured textual form, but organizations have found it difficult or impossible to access and utilize it. This is changing rapidly: new approaches finally make it possible to glean useful knowledge from virtually any collection of unstructured data.
William H. Inmon--the father of data warehousing--and Anthony Nesavich introduce the next data revolution: unstructured data management. Inmon and Nesavich cover all you need to know to make unstructured data work for your organization. You'll learn how to bring it into your existing structured data environment, leverage existing analytical infrastructure, and implement textual analytic processing technologies to solve new problems and uncover new opportunities. Inmon and Nesavich introduce breakthrough techniques covered in no other book--including the powerful role of textual integration, new ways to integrate textual data into data warehouses, and new SQL techniques for reading and analyzing text. They also present five chapter-length, real-world case studies--demonstrating unstructured data at work in medical research, insurance, chemical manufacturing, contracting, and beyond.
This book will be indispensable to every business and technical professional trying to make sense of a large body of unstructured text: managers, database designers, data modelers, DBAs, researchers, and end users alike.
Coverage includes
What unstructured data is, and how it differs from structured data
First generation technology for handling unstructured data, from search engines to ECM--and its limitations
Integrating text so it can be analyzed with a common, colloquial vocabulary: integration engines, ontologies, glossaries, and taxonomies
Processing semistructured data: uncovering patterns, words, identifiers, and conflicts
Novel processing opportunities that arise when text is freed from context
Architecture and unstructured data: Data Warehousing 2.0
Building unstructured relational databases and linking them to structured data
Visualizations and Self-Organizing Maps (SOMs), including Compudigm and Raptor solutions
Capturing knowledge from spreadsheet data and email
Implementing and managing metadata: data models, data quality, and more
William H. Inmon is founder, president, and CTO of Inmon Data Systems. He is the father of the data warehouse concept, the corporate information factory, and the government information factory. Inmon has written 47 books on data warehouse, database, and information technology management; as well as more than 750 articles for trade journals such as Data Management Review, Byte, Datamation, and ComputerWorld. His b-eye-network.com newsletter currently reaches 55,000 people.
Anthony Nesavich worked at Inmon Data Systems, where he developed multiple reports that successfully query unstructured data.
Preface xvii
1 Unstructured Textual Data in the Organization 1
2 The Environments of Structured Data and Unstructured Data 15
3 First Generation Textual Analytics 33
4 Integrating Unstructured Text into the Structured Environment 47
5 Semistructured Data 73
6 Architecture and Textual Analytics 83
7 The Unstructured Database 95
8 Analyzing a Combination of Unstructured Data and Structured Data 113
9 Analyzing Text Through Visualization 127
10 Spreadsheets and Email 135
11 Metadata in Unstructured Data 147
12 A Methodology for Textual Analytics 163
13 Merging Unstructured Databases into the Data Warehouse 175
14 Using SQL to Analyze Text 185
15 Case Study--Textual Analytics in Medical Research 195
16 Case Study--A Database for Harmful Chemicals 203
17 Case Study--Managing Contracts Through an Unstructured Database 209
18 Case Study--Creating a Corporate Taxonomy (Glossary) 215
19 Case Study--Insurance Claims 219
Glossary 227
Index 233
More details
Language
English
Place of publication
Upper Saddle River
United States
Publishing group
Pearson Education (US)
Target group
College/higher education
Dimensions
Height: 228 mm
Width: 184 mm
Thickness: 20 mm
Weight
510 gr
ISBN-13
978-0-13-236029-6 (9780132360296)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
Bill Inmon--the "father of data warehousing"--has written 50 books and published in nine languages on subjects such as data warehousing, database design, and architecture.
For current events, seminars, conference speaking schedules, and a lot of other information related to data warehousing, unstructured data, and textual ETL, take a look at Bill Inmon's Web site at www.inmoncif.com.
Anthony aka "Tony" Nesavich received his master's degree in computer information technology from Regis University in Denver, Colorado. He worked with Bill Inmon at Inmon Data Systems (IDS) where he was instrumental in the development of the IDS Foundation software. Much of Tony's contributions to IDS are discussed in this book. Tony lives in Denver, Colorado, with his wife Melissa and his faithful dog, Lola.
For current events, seminars, conference speaking schedules, and a lot of other information related to data warehousing, unstructured data, and textual ETL, take a look at Bill Inmon's Web site at www.inmoncif.com.
Anthony aka "Tony" Nesavich received his master's degree in computer information technology from Regis University in Denver, Colorado. He worked with Bill Inmon at Inmon Data Systems (IDS) where he was instrumental in the development of the IDS Foundation software. Much of Tony's contributions to IDS are discussed in this book. Tony lives in Denver, Colorado, with his wife Melissa and his faithful dog, Lola.
Content
Preface xvii
1 Unstructured Textual Data in the Organization 1
2 The Environments of Structured Data and Unstructured Data 15
3 First Generation Textual Analytics 33
4 Integrating Unstructured Text into the Structured Environment 47
5 Semistructured Data 73
6 Architecture and Textual Analytics 83
7 The Unstructured Database 95
8 Analyzing a Combination of Unstructured Data and Structured Data 113
9 Analyzing Text Through Visualization 127
10 Spreadsheets and Email 135
11 Metadata in Unstructured Data 147
12 A Methodology for Textual Analytics 163
13 Merging Unstructured Databases into the Data Warehouse 175
14 Using SQL to Analyze Text 185
15 Case Study--Textual Analytics in Medical Research 195
16 Case Study--A Database for Harmful Chemicals 203
17 Case Study--Managing Contracts Through an Unstructured Database 209
18 Case Study--Creating a Corporate Taxonomy (Glossary) 215
19 Case Study--Insurance Claims 219
Glossary 227
Index 233
1 Unstructured Textual Data in the Organization 1
2 The Environments of Structured Data and Unstructured Data 15
3 First Generation Textual Analytics 33
4 Integrating Unstructured Text into the Structured Environment 47
5 Semistructured Data 73
6 Architecture and Textual Analytics 83
7 The Unstructured Database 95
8 Analyzing a Combination of Unstructured Data and Structured Data 113
9 Analyzing Text Through Visualization 127
10 Spreadsheets and Email 135
11 Metadata in Unstructured Data 147
12 A Methodology for Textual Analytics 163
13 Merging Unstructured Databases into the Data Warehouse 175
14 Using SQL to Analyze Text 185
15 Case Study--Textual Analytics in Medical Research 195
16 Case Study--A Database for Harmful Chemicals 203
17 Case Study--Managing Contracts Through an Unstructured Database 209
18 Case Study--Creating a Corporate Taxonomy (Glossary) 215
19 Case Study--Insurance Claims 219
Glossary 227
Index 233