Verfügbarkeit: Data architecture

Data architecture: a primer for the data scientist ; big data, data warehouse and data vault

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Bibliographische Detailangaben
1. Verfasser:	Inmon, William H. 1945- (VerfasserIn)
Format:	Buch
Sprache:	English
Veröffentlicht:	Amsterdam u.a. Elsevier Morgan Kaufman 2015
Schlagworte:	Data warehousing Big data Big Data Data-Warehouse-Konzept Softwarearchitektur
Online-Zugang:	Inhaltsverzeichnis
Beschreibung:	Includes index Corporate data -- The data infrastructure -- The "great divide" -- Demographics of corporate data -- Corporate data analysis -- The life cycle of data : understanding data over time -- A brief history of data -- A brief history of big data -- What is big data? -- Parallel processing -- Unstructured data -- Contextualizing repetitive unstructured data -- Textual disambiguation -- Taxonomies -- A brief history of data warehouse -- Integrated corporate data -- Historical data -- Data marts -- What a data warehouse is not -- Introduction to data vault -- Introduction to data vault modeling -- Introduction to data vault architecture -- Introduction to data vault methodology -- Introduction to data vault implementation -- The operational environment : a short history -- The standard work unit -- Data modeling for the structured environment -- Metadata -- Data governance of structured data -- A brief history of data architecture -- Big data/existing systems interface -- The data warehouse/operational environment interface -- Data architecture : a high-level perspective -- Repetitive analytics : some basics -- Analyzing repetitive data -- Repetitive analysis -- Nonrepetitive data -- Mapping -- Analytics from nonrepetitive data -- Operational analytics -- Operational analytics -- Personal analytics -- A composite data architecture
Beschreibung:	XXI, 355 S. Ill., graph. Darst.
ISBN:	9780128020449

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Datensatz im Suchindex

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adam_text	Contents VU CONTENTS Preface ........................................................................................................xvii About the Authors ......................................................................................xxi Chapter 1.1 Corporate Data ..................................................................................1 The Totality of Data Across the Corporation ...............................................1 Dividing Unstructured Data ..........................................................................2 Business Relevancy .......................................................................................3 Big Data ..........................................................................................................4 The Great Divide ............................................................................................4 The Continental Divide ..................................................................................6 The Complete Picture ....................................................................................6 Chapter 1.2 The Data Infrastructure ....................................................................9 Two Types of Repetitive Data .......................................................................9 Repetitive Structured Data ............................................................................9 Repetitive Big Data ......................................................................................10 The Two Infrastructures ..............................................................................12 What s being Optimized? ............................................................................12 Comparing the Two Infrastructures ...........................................................12 Chapter 1.3 The Great Divide .........................................................................15 Classifying Corporate Data .........................................................................15 The Great Divide ......................................................................................15 Repetitive Unstructured Data .....................................................................16 Nonrepetitive Unstructured Data ...............................................................17 Different Worlds .......................................................................................... 19 Chapter 1.4 Demographics of Corporate Data ................................................21 Chapter 1.5 Corporate Data Analysis ................................................................27 Chapter 1.6 The Life Cycle of Data - Understanding Data Over Time ........33 VIII Contents Chapter 1.7 A Brief History of Data ....................................................................39 Paper Tape and Punch Cards ......................................................................39 Magnetic Tapes ............................................................................................ 39 Disk Storage ................................................................................................. 40 Database Management System .................................................................40 Coupled Processors .....................................................................................41 Online Transaction Processing ...................................................................41 Data Warehouse ..........................................................................................42 Parallel Data Management ..........................................................................42 Data Vault .....................................................................................................43 Big Data ........................................................................................................43 The Great Divide ..........................................................................................44 Chapter ZI A Brief History of Big Data .............................................................45 An Analogy - Taking the High Ground ......................................................45 Taking the High Ground ..............................................................................45 Standardization with the 360......................................................................46 Online Transaction Processing ...................................................................47 Enter Teradata and Massively Parallel Processing ...................................47 Then Came Hadoop and Big Data ..............................................................48 IBM and Hadoop ..........................................................................................48 Holding the High Ground ............................................................................48 Chapter 12 What is Big Data? ............................................................................49 Another Definition .......................................................................................49 Large Volumes .............................................................................................49 Inexpensive Storage ....................................................................................50 The Roman Census Approach ......................................... 50 Unstructured Data .......................................................... 51 Data in Big Data ....................................................] ..............................52 Context in Repetitive Data ...................................... ZZZZZ. ....................53 Nonrepetitive Data .......................................... ZZZZZ. ............................53 Context in Nonrepetitive Data ....................... ZZZZZZZ. ......................54 Chapter Z3 Parallel Processing .........................................................................57 Contents IX Chapter 2.4 Unstructured Data ............................................................................63 Textual Information Everywhere ................................................................63 Decisions Based on Structured Data ..........................................................63 The Business Value Proposition .................................................................64 Repetitive and Nonrepetitive Unstructured Information ..........................65 Ease of Analysis ...........................................................................................66 Contextualization .........................................................................................67 Some Approaches to Contextualization ....................................................68 MapReduce ..................................................................................................69 Manual Analysis ..........................................................................................70 Chapter 2.5 Contextualizing Repetitive Unstructured Data ...........................71 Parsing Repetitive Unstructured Data ........................................................71 Recasting the Output Data ..........................................................................71 Chapter 2.6 Textual Disambiguation .................................................................73 From Narrative into an Analytical Database .............................................73 Input into Textual Disambiguation .............................................................74 Mapping .......................................................................................................75 Input/Output .................................................................................................76 Document Fracturing/Named Value Processing .......................................77 Preprocessing a Document .........................................................................77 Emails - A Special Case ..............................................................................78 Spreadsheets ...............................................................................................79 Report Decompilation .................................................................................79 Chapter 2.7 Taxonomies .......................................................................................83 Data Models and Taxonomies ....................................................................83 Applicability of Taxonomies .......................................................................85 What is a Taxonomy? ..................................................................................85 Taxonomies in Multiple Languages ...........................................................86 Dynamics of Taxonomies and Textual Disambiguation ..........................87 Taxonomies and Textual Disambiguation - Separate Technologies ......88 Different Types of Taxonomies ..................................................................89 Taxonomies - Maintenance Over Time .....................................................89 X Contents Chapter 3.1 A Brief History of Data Warehouse ..............................................91 Early Applications ........................................................................................ 91 Online Applications ..................................................................................... 91 Extract Programs ......................................................................................... 92 4GL Technology ........................................................................................... 92 Personalcomputers.................................................................................... 94 Spreadsheets ............................................................................................... 94 Integrity of Data ........................................................................................... 95 Spider-WebSystems ...................................................................................95 The Maintenance Backlog ...........................................................................96 The Data Warehouse ...................................................................................97 To an Architected Environment ..................................................................98 To the CIF .....................................................................................................98 DW2.0 ........................................................................................................100 Chapter 32 Integrated Corporate Data ............................................................101 Many Applications .....................................................................................101 Looking Across the Corporation ...............................................................101 More Than One Analyst ............................................................................104 ETL Technology .........................................................................................104 The Challenges of Integration ..................................................................105 The Benefits of a Data Warehouse ...........................................................107 The Granular Perspective ..........................................................................108 Chapter 3.3 Historical Data ............................................................................... Ill Chapter 3.4 Data Marts .......................................................................................115 Granular Data ............................................................................................. 115 Relational Database Design ...................................................................... 115 The Data Mart ......................................................... ľZZZ!!!ZZZľZi16 Key Performance Indicators ...................................................... ZZZZ.117 The Dimensional Model ........................................ ..............u 117 Combining the Data Warehouse and Data Marts .............................. Z. 118 Chapter IS The Operational Data Store .........................................................121 Online Transaction Processing on Integrated Data ....... Z...... ..................121 The Operational Data Store .............................. ................ ^ ODS and the Data Warehouse ....... .ZZ ..................................................123 Contents XI ODS Classes ...............................................................................................124 External Updates into the ODS .................................................................125 The ODS/Data Warehouse Interface ........................................................126 Chapter 3.6 What a Data Warehouse is Not ...................................................127 A Simple Data Warehouse Architecture ..................................................127 Online High-Performance Transaction Processing in the Data Warehouse ........................................................................................127 Integrity of Data .........................................................................................128 The Data Warehouse Workload ................................................................129 Statistical Processing from the Data Warehouse ....................................130 The Frequency of Statistical Processing ..................................................130 The Exploration Warehouse .....................................................................131 Chapter 4.1 Introduction to Data Vault ............................................................133 Data Vault 2.0 Modeling ............................................................................134 Data Vault 2.0 Methodology Defined .......................................................135 Data Vault 2.0 Architecture .......................................................................135 Data Vault 2.0 Implementation .................................................................135 Business Benefits of Data Vault 2.0..........................................................135 Data Vault 1.0.............................................................................................137 Chapter 4.2 Introduction to Data Vault Modeling ..........................................139 A Data Vault Model Concept .....................................................................139 Data Vault Model Defined .........................................................................139 Components of a Data Vault Model .........................................................140 Data Vault and Data Warehousing ...........................................................141 Translating to Data Vault Modeling .........................................................142 Data Restructure ........................................................................................144 Basic Rules of Data Vault Modeling .........................................................144 Why We Need Many-to-Many Link Structures ........................................144 Hash keys Instead of Sequence Numbers ...............................................145 Chapter 4.3 Introduction to Data Vault Architecture ....................................149 Data Vault 2.0 Architecture .......................................................................149 How NoSQL Fits into the Architecture .....................................................149 Data Vault 2.0 Architecture Objectives ....................................................151 XU Contents Data Vault 2.0 Modeling Objective ........................................................... Hard and Soft Business Rules .................................................................. Managed SSBI and the Architecture ........................................................ 153 Chapter 4.4 Introduction to Data Vault Methodology ...................................155 Data Vault 2.0 Methodology Overview ....................................................155 CMMI and Data Vault 2.0 Methodology ...................................................155 CMMI Versus Agility .................................................................................. Ί58 Project Management Practices and SDLC Versus CMMI and Agile ......159 Six Sigma and Data Vault 2.0 Methodology ...........................................160 Total Quality Management .......................................................................161 Chapter 4.5 Introduction to Data Vault Implementation ...............................163 Implementation Overview ........................................................................163 The Importance of Patterns ......................................................................163 Reengineering and Big Data .....................................................................164 Virtualize Our Data Marts ..........................................................................166 Managed Self-Service Bl ...........................................................................167 Chapter 5.1 The Operational Environment - A Short History ......................169 Commercial Uses of the Computer ..........................................................169 The First Applications ................................................................................170 Ed Yourdon and the Structured Revolution ............................................170 System Development Ufe Cycle ...............................................................171 Disk Technology ........................................................................................171 Enter the Database Management System ...............................................172 Response Time and Availability ...............................................................173 Corporate Computing Today ....................................................................175 Chapter 52 The Standard Work Unit ...............................................................177 Elements of Response Time .....................................................................177 An Hourglass Analogy ..............................................................................178 The Racetrack Analogy ..............................................................................179 Your Vehicle Runs as Fast as the Vehicle in Front of It ..........................179 The Standard Work Unit ...........................................................................180 The Service Level Agreement ...................................................................180 Contents XIII Chapter 5.3 Data Modeling for the Structured Environment .......................181 The Purpose of the Road Map ..................................................................181 Granular Data Only ....................................................................................181 The Entity Relationship Diagram ..............................................................182 The DIS .......................................................................................................183 Physical Database Design .........................................................................185 Relating the Different Levels of the Data Model .....................................185 An Example of the Linkage .......................................................................186 Generic Data Models .................................................................................188 Operational Data Models and Data Warehouse Data Models ...............188 Chapter^ Metadata .........................................................................................189 Typical Metadata .......................................................................................189 The Repository ...........................................................................................189 Using Metadata ..........................................................................................191 Analytical Uses of Metadata .....................................................................192 Looking at Multiple Systems ....................................................................193 The Lineage of Data ...................................................................................193 Comparing Existing Systemsto Proposed Systems ..............................193 Chapter 5.5 Data Governance of Structured Data .........................................195 A Corporate Activity ..................................................................................195 Motivations for Data Governance ............................................................195 Repairing Data ...........................................................................................195 Granular, Detailed Data .............................................................................197 Documentation ..........................................................................................197 Data Stewardship ......................................................................................197 Chapter 6.1 A Brief History of Data Architecture ..........................................199 Chapter 6.2 Big Data/Existing Systems Interface .........................................211 The Big Data/Existing Systems Interface .................................................211 The Repetitive Raw Big Data/Existing Systems Interface ......................211 Exception-Based Data ...............................................................................213 The Nonrepetitive Raw Big Data/Existing Systems Interface ................214 Into the Existing Systems Environment ..................................................215 The Context-Enriched Big Data Environment .....................................216 Analyzing Structured Data/Unstructured Data Together .......................218 xhf Contents Chapter 6.3 The Data Warehouse/Operational Environment Interface ......219 The Operational/Data Warehouse Interface ............................................219 The Classical ETL Interface ....................................................................... 219 The Operational Data Store/ETL Interface ...............................................220 The Staging Area ....................................................................................... 221 Changed Data Capture .............................................................................. 222 Inline Transformation ................................................................................222 ELT Processing ...........................................................................................223 Chapter 6.4 Data Architecture - A High-Level Perspective ........................225 A High-Level perspective ..........................................................................225 Redundancy ...............................................................................................225 The System of Record ...............................................................................226 Different Communities ..............................................................................229 Chapter 7.1 Repetitive Analytics - Some Basics ..........................................231 Different Kinds of Analysis .......................................................................231 Looking for Patterns ..................................................................................232 Heuristic Processing ..................................................................................234 The Sandbox ..............................................................................................237 The Normal Profile ................................................................................238 Distillation, Filtering ..................................................................................238 Subsetting Data .........................................................................................240 Filtering Data ..............................................................................................242 Repetitive Data and Context .....................................................................243 Linking Repetitive Records .......................................................................244 Log Tape Records ......................................................................................245 Analyzing Points of Data ...........................................................................246 Data Over Time ..........................................................................................247 Chapter 12 Analyzing Repetitive Data ............................................................249 Log Data ..................................................................................... ZZ.......250 Active/Passive Indexing of Data ...............................................................252 Summary/Detailed Data ............................................................!, !... ..! 253 Metadata in Big Data .........................................................!!!!!! ! !!!!!. !!!!!! 255 Linking Data .......................................................................... ,..*Iľ ľ 256 Contents XV Chapter 7.3 Repetitive Analysis ........................................................................259 Internal, External Data ...............................................................................259 Universal Identifiers ..................................................................................259 Security .......................................................................................................261 Filtering, Distillation ..................................................................................263 Archiving Results .......................................................................................264 Metrics ........................................................................................................266 Chapter 8.1 Nonrepetitive Data ........................................................................267 Inline Contextualization .............................................................................270 Taxonomy/Ontology Processing ..............................................................271 Custom Variables .......................................................................................272 Homographie Resolution ..........................................................................273 Acronym Resolution ..................................................................................275 Negation Analysis ......................................................................................275 Numeric Tagging .......................................................................................276 Date Tagging ..............................................................................................277 Date Standardization .................................................................................277 List Processing ...........................................................................................278 Associative Word Processing ...................................................................279 Stop Word Processing ...............................................................................280 Word Stemming ........................................................................................280 Document Metadata ..................................................................................281 Document Classification ...........................................................................282 Proximity Analysis .....................................................................................282 Functional Sequencing within Textual ETL .............................................283 Internal Referential Integrity .....................................................................283 Preprocessing, Postprocessing ................................................................285 Chapter 8.2 Mapping ...........................................................................................287 Chapter 8.3 Analytics from Nonrepetitive Data .............................................291 Call Center Information .............................................................................291 Medical Records ........................................................................................300 XVI Contents Chapter 9.1 Operational Analytics ...................................................................305 Transaction Response Time .....................................................................307 Chapter 10.1 Operational Analytics .................................................................313 Chapter 11.1 Personal Analytics ......................................................................323 Chapter 12.1 A Composite Data Architecture ................................................329 Glossary ..................................................................................................................335 Index .......................................................................................................................345
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spelling	Inmon, William H. 1945- Verfasser (DE-588)113317662 aut Data architecture a primer for the data scientist ; big data, data warehouse and data vault W.H. Inmon ; Daniel Linstedt Amsterdam u.a. Elsevier Morgan Kaufman 2015 XXI, 355 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Includes index Corporate data -- The data infrastructure -- The "great divide" -- Demographics of corporate data -- Corporate data analysis -- The life cycle of data : understanding data over time -- A brief history of data -- A brief history of big data -- What is big data? -- Parallel processing -- Unstructured data -- Contextualizing repetitive unstructured data -- Textual disambiguation -- Taxonomies -- A brief history of data warehouse -- Integrated corporate data -- Historical data -- Data marts -- What a data warehouse is not -- Introduction to data vault -- Introduction to data vault modeling -- Introduction to data vault architecture -- Introduction to data vault methodology -- Introduction to data vault implementation -- The operational environment : a short history -- The standard work unit -- Data modeling for the structured environment -- Metadata -- Data governance of structured data -- A brief history of data architecture -- Big data/existing systems interface -- The data warehouse/operational environment interface -- Data architecture : a high-level perspective -- Repetitive analytics : some basics -- Analyzing repetitive data -- Repetitive analysis -- Nonrepetitive data -- Mapping -- Analytics from nonrepetitive data -- Operational analytics -- Operational analytics -- Personal analytics -- A composite data architecture Data warehousing Big data Big Data (DE-588)4802620-7 gnd rswk-swf Data-Warehouse-Konzept (DE-588)4406462-7 gnd rswk-swf Softwarearchitektur (DE-588)4121677-5 gnd rswk-swf Big Data (DE-588)4802620-7 s Data-Warehouse-Konzept (DE-588)4406462-7 s Softwarearchitektur (DE-588)4121677-5 s DE-604 Linstedt, Daniel Sonstige (DE-588)1068367636 oth Digitalisierung UB Bamberg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027799548&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis
spellingShingle	Inmon, William H. 1945- Data architecture a primer for the data scientist ; big data, data warehouse and data vault Data warehousing Big data Big Data (DE-588)4802620-7 gnd Data-Warehouse-Konzept (DE-588)4406462-7 gnd Softwarearchitektur (DE-588)4121677-5 gnd
subject_GND	(DE-588)4802620-7 (DE-588)4406462-7 (DE-588)4121677-5
title	Data architecture a primer for the data scientist ; big data, data warehouse and data vault
title_auth	Data architecture a primer for the data scientist ; big data, data warehouse and data vault
title_exact_search	Data architecture a primer for the data scientist ; big data, data warehouse and data vault
title_full	Data architecture a primer for the data scientist ; big data, data warehouse and data vault W.H. Inmon ; Daniel Linstedt
title_fullStr	Data architecture a primer for the data scientist ; big data, data warehouse and data vault W.H. Inmon ; Daniel Linstedt
title_full_unstemmed	Data architecture a primer for the data scientist ; big data, data warehouse and data vault W.H. Inmon ; Daniel Linstedt
title_short	Data architecture
title_sort	data architecture a primer for the data scientist big data data warehouse and data vault
title_sub	a primer for the data scientist ; big data, data warehouse and data vault
topic	Data warehousing Big data Big Data (DE-588)4802620-7 gnd Data-Warehouse-Konzept (DE-588)4406462-7 gnd Softwarearchitektur (DE-588)4121677-5 gnd
topic_facet	Data warehousing Big data Big Data Data-Warehouse-Konzept Softwarearchitektur
url	http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027799548&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
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