Building the Unstructured Data Warehouse
- Architecture, Analysis & Design
- Indbinding:
- Hardback
- Sideantal:
- 216
- Udgivet:
- 29. januar 2011
- Størrelse:
- 177x252x18 mm.
- Vægt:
- 456 g.
- 8-11 hverdage.
- 16. december 2024
Forlænget returret til d. 31. januar 2025
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Abonnementspris
- Rabat på køb af fysiske bøger
- 1 valgfrit digitalt ugeblad
- 20 timers lytning og læsning
- Adgang til 70.000+ titler
- Ingen binding
Abonnementet koster 75 kr./md.
Ingen binding og kan opsiges når som helst.
- 1 valgfrit digitalt ugeblad
- 20 timers lytning og læsning
- Adgang til 70.000+ titler
- Ingen binding
Abonnementet koster 75 kr./md.
Ingen binding og kan opsiges når som helst.
Beskrivelse af Building the Unstructured Data Warehouse
Learn essential techniques from data warehouse legend Bill Inmon on how to build the reporting environment your business needs now!
Answers for many valuable business questions hide in text. How well can your existing reporting environment extract the necessary text from email, spreadsheets, and documents, and put it in a useful format for analytics and reporting? Transforming the traditional data warehouse into an efficient unstructured data warehouse requires additional skills from the analyst, architect, designer, and developer. This book will prepare you to successfully implement an unstructured data warehouse and, through clear explanations, examples, and case studies, you will learn new techniques and tips to successfully obtain and analyze text.
Master these ten objectives:
Build an unstructured data warehouse using the 11-step approach
Integrate text and describe it in terms of homogeneity, relevance, medium, volume, and structure
Overcome challenges including blather, the Tower of Babel, and lack of natural relationships
Avoid the Data Junkyard and combat the "Spider's Web"
Reuse techniques perfected in the traditional data warehouse and Data Warehouse 2.0,including iterative development
Apply essential techniques for textual Extract, Transform, and Load (ETL) such as phrase recognition, stop word filtering, and synonym replacement
Design the Document Inventory system and link unstructured text to structured data
Leverage indexes for efficient text analysis and taxonomies for useful external categorization
Manage large volumes of data using advanced techniques such as backward pointers
Evaluate technology choices suitable for unstructured data processing, such as data warehouse appliances
Answers for many valuable business questions hide in text. How well can your existing reporting environment extract the necessary text from email, spreadsheets, and documents, and put it in a useful format for analytics and reporting? Transforming the traditional data warehouse into an efficient unstructured data warehouse requires additional skills from the analyst, architect, designer, and developer. This book will prepare you to successfully implement an unstructured data warehouse and, through clear explanations, examples, and case studies, you will learn new techniques and tips to successfully obtain and analyze text.
Master these ten objectives:
Build an unstructured data warehouse using the 11-step approach
Integrate text and describe it in terms of homogeneity, relevance, medium, volume, and structure
Overcome challenges including blather, the Tower of Babel, and lack of natural relationships
Avoid the Data Junkyard and combat the "Spider's Web"
Reuse techniques perfected in the traditional data warehouse and Data Warehouse 2.0,including iterative development
Apply essential techniques for textual Extract, Transform, and Load (ETL) such as phrase recognition, stop word filtering, and synonym replacement
Design the Document Inventory system and link unstructured text to structured data
Leverage indexes for efficient text analysis and taxonomies for useful external categorization
Manage large volumes of data using advanced techniques such as backward pointers
Evaluate technology choices suitable for unstructured data processing, such as data warehouse appliances
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