Unstructured Data Analysis: Entity Resolution and Regular Expressions in SAS

Description

Unstructured data is the most voluminous form of data in the world, and several elements are critical for any advanced analytics practitioner leveraging SAS software to effectively address the challenge of deriving value from that data. This book covers the five critical elements of entity extraction, unstructured data, entity resolution, entity network mapping and analysis, and entity management. By following examples of how to apply processing to unstructured data, readers will derive tremendous long-term value from this book as they enhance the value they realize from SAS products. Contents About This Book Software Used to Develop the Book's Content Example Code and Data SAS University Edition Acknowledgments Chapter 1: Getting Started with Regular Expressions 1.1.1 Defining Regular Expressions 1.1.2 Motivational Examples 1.1.3 RegEx Essentials 1.1.4 RegEx Test Code 1.3.1 Wildcard 1.3.2 Word 1.3.3 Non-word 1.3.4 Tab 1.3.5 Whitespace 1.3.6 Non-whitespace 1.3.7 Digit 1.3.8 Non-digit 1.3.9 Newline 1.3.10 Bell 1.3.11 Control Character 1.3.12 Octal 1.3.13 Hexadecimal 1.4.1 List 1.4.2 Not List 1.4.3 Range 1.5.1 Case Modifiers 1.5.2 Repetition Modifiers 1.6.1 Ignore Case 1.6.2 Single Line 1.6.3 Multiline 1.6.4 Compile Once 1.6.5 Substitution Operator 1.7.1 Start of Line 1.7.2 End of Line 1.7.3 Word Boundary 1.7.4 Non-word Boundary 1.7.5 String Start Chapter 2: Using Regular Expressions in SAS 2.1.1 Capture Buffer 2.2.1 PRXPARSE 2.2.2 PRXMATCH 2.2.3 PRXCHANGE 2.2.4 PRXPOSN 2.2.5 PRXPAREN 2.3.1 CALL PRXCHANGE 2.3.2 CALL PRXPOSN 2.3.3 CALL PRXSUBSTR 2.3.4 CALL PRXNEXT 2.3.5 CALL PRXDEBUG 2.3.6 CALL PRXFREE 2.4.1 Data Cleansing and Standardization 2.4.2 Information Extraction 2.4.3 Search and Replacement Chapter 3: Entity Resolution Analytics 3.3.1 Entity Extraction 3.3.2 Extract, Transform, and Load 3.3.3 Entity Resolution 3.3.4 Entity Network Mapping and Analysis 3.3.5 Entity Management 3.4.1 Establish Clear Goals 3.4.2 Verify Proper Data Inventory 3.4.3 Create SMART Objectives Chapter 4: Entity Extraction 4.3.1 Webpage 4.3.2 File System 4.4.1 Social Security Number 4.4.2 Phone Number 4.4.3 Address 4.4.4 Website 4.4.5 Corporation Name Chapter 5: Extract, Transform, Load 5.2.1 PROC CONTENTS 5.2.2 PROC FREQ 5.2.3 PROC MEANS 5.4.1 Hexadecimal to Decimal 5.4.2 Working with Dates 5.6.1 Quantile Binning 5.6.2 Bucket Binning Chapter 6: Entity Resolution 6.1.1 Exact Matching 6.1.2 Fuzzy Matching 6.1.3 Error Handling 6.2.1 INDEX= 6.3.1 COMPGED and COMPLEV 6.3.2 SOUNDEX 6.3.3 Putting Things Together Chapter 7: Entity Network Mapping and Analysis 7.2.1 Shared Entity Attributes 7.2.2 Entity Interactions 7.3.1 Articulation Points and Biconnected Components 7.3.2 Minimum Spanning Trees 7.3.3 Clique Detection 7.3.4 Minimum Cut 7.3.5 Shortest Paths Chapter 8: Entity Management Appendix A: Additional Resources A.2.1 Non-Printing Characters A.2.2 Printing Characters A.4.1 Random PII Generator A.4.2 Output