Data warehousing in the age of big data:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Amsterdam
Morgan Kaufmann is an imprint of Elsevier
2013
|
| Schlagworte: | |
| Online-Zugang: | FAW01 FLA01 FUBA1 URL des Erstveröffentlichers |
| Beschreibung: | "In conclusion as you come to the end of this book, the concept of a Data Warehouse and its primary goal of serving the enterprise version of truth, and being the single platform for all the source of information will continue to remain intact and valid for many years to come. As we have discussed across many chapters and in many case studies, the limitations that existed with the infrastructures to create, manage and deploy Data Warehouses have been largely eliminated with the availability of Big Data technologies and infrastructure platforms, making the goal of the single version of truth a feasible reality. Integrating and extending Big Data into the Data Warehouse, and creating a larger decision support platform will benefit businesses for years to come. This book has touched upon governance and information lifecycle management aspects of Big Data in the larger program, however you can reuse all the current program management techniques that you follow for the Data Warehouse for this program and even implement agile approaches to integrating and managing data in the Data Warehouse. Technologies will continue to evolve in this spectrum and there will be more additions of solutions, which can be integrated if you follow the modular integration approaches to building and managing the Data Warehouse. The Appendix sections contain many more case studies and a special section on Healthcare Information Factory based on Big Data approaches. These are more guiding posts to help you align your thoughts and goals to building and integrating Big Data in your Data Warehouse"-- Includes bibliographical references and index |
| Beschreibung: | 1 Online-Ressource (346 pages) Illustrationen, Grafiken |
| ISBN: | 0124059201 9780124059207 1299591914 9781299591912 |
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| 500 | |a "In conclusion as you come to the end of this book, the concept of a Data Warehouse and its primary goal of serving the enterprise version of truth, and being the single platform for all the source of information will continue to remain intact and valid for many years to come. As we have discussed across many chapters and in many case studies, the limitations that existed with the infrastructures to create, manage and deploy Data Warehouses have been largely eliminated with the availability of Big Data technologies and infrastructure platforms, making the goal of the single version of truth a feasible reality. Integrating and extending Big Data into the Data Warehouse, and creating a larger decision support platform will benefit businesses for years to come. This book has touched upon governance and information lifecycle management aspects of Big Data in the larger program, however you can reuse all the current program management techniques that you follow for the Data Warehouse for this program and even implement agile approaches to integrating and managing data in the Data Warehouse. Technologies will continue to evolve in this spectrum and there will be more additions of solutions, which can be integrated if you follow the modular integration approaches to building and managing the Data Warehouse. The Appendix sections contain many more case studies and a special section on Healthcare Information Factory based on Big Data approaches. These are more guiding posts to help you align your thoughts and goals to building and integrating Big Data in your Data Warehouse"-- | ||
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Datensatz im Suchindex
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| any_adam_object | |
| author | Krishnan, Krish |
| author_GND | (DE-588)1042305153 |
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| dewey-full | 005.74/5 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 005 - Computer programming, programs, data, security |
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| discipline | Informatik |
| format | Electronic eBook |
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| id | DE-604.BV042314322 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T01:18:10Z |
| institution | BVB |
| isbn | 0124059201 9780124059207 1299591914 9781299591912 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-027751313 |
| oclc_num | 843860813 1073654100 |
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| physical | 1 Online-Ressource (346 pages) Illustrationen, Grafiken |
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| spelling | Krishnan, Krish Verfasser (DE-588)1042305153 aut Data warehousing in the age of big data Krish Krishnan Amsterdam Morgan Kaufmann is an imprint of Elsevier 2013 1 Online-Ressource (346 pages) Illustrationen, Grafiken txt rdacontent c rdamedia cr rdacarrier "In conclusion as you come to the end of this book, the concept of a Data Warehouse and its primary goal of serving the enterprise version of truth, and being the single platform for all the source of information will continue to remain intact and valid for many years to come. As we have discussed across many chapters and in many case studies, the limitations that existed with the infrastructures to create, manage and deploy Data Warehouses have been largely eliminated with the availability of Big Data technologies and infrastructure platforms, making the goal of the single version of truth a feasible reality. Integrating and extending Big Data into the Data Warehouse, and creating a larger decision support platform will benefit businesses for years to come. This book has touched upon governance and information lifecycle management aspects of Big Data in the larger program, however you can reuse all the current program management techniques that you follow for the Data Warehouse for this program and even implement agile approaches to integrating and managing data in the Data Warehouse. Technologies will continue to evolve in this spectrum and there will be more additions of solutions, which can be integrated if you follow the modular integration approaches to building and managing the Data Warehouse. The Appendix sections contain many more case studies and a special section on Healthcare Information Factory based on Big Data approaches. These are more guiding posts to help you align your thoughts and goals to building and integrating Big Data in your Data Warehouse"-- Includes bibliographical references and index COMPUTERS / Database Management / Data Warehousing bisacsh Big data fast Data warehousing fast Data warehousing Big data Big Data (DE-588)4802620-7 gnd rswk-swf Data-Warehouse-Konzept (DE-588)4406462-7 gnd rswk-swf Data-Warehouse-Konzept (DE-588)4406462-7 s Big Data (DE-588)4802620-7 s 1\p DE-604 Erscheint auch als Druck-Ausgabe, Paperback 978-0-12-405891-0 Erscheint auch als Druck-Ausgabe, Paperback 0-12-405891-4 http://www.sciencedirect.com/science/book/9780124058910 Verlag URL des Erstveröffentlichers Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Krishnan, Krish Data warehousing in the age of big data COMPUTERS / Database Management / Data Warehousing bisacsh Big data fast Data warehousing fast Data warehousing Big data Big Data (DE-588)4802620-7 gnd Data-Warehouse-Konzept (DE-588)4406462-7 gnd |
| subject_GND | (DE-588)4802620-7 (DE-588)4406462-7 |
| title | Data warehousing in the age of big data |
| title_auth | Data warehousing in the age of big data |
| title_exact_search | Data warehousing in the age of big data |
| title_full | Data warehousing in the age of big data Krish Krishnan |
| title_fullStr | Data warehousing in the age of big data Krish Krishnan |
| title_full_unstemmed | Data warehousing in the age of big data Krish Krishnan |
| title_short | Data warehousing in the age of big data |
| title_sort | data warehousing in the age of big data |
| topic | COMPUTERS / Database Management / Data Warehousing bisacsh Big data fast Data warehousing fast Data warehousing Big data Big Data (DE-588)4802620-7 gnd Data-Warehouse-Konzept (DE-588)4406462-7 gnd |
| topic_facet | COMPUTERS / Database Management / Data Warehousing Big data Data warehousing Big Data Data-Warehouse-Konzept |
| url | http://www.sciencedirect.com/science/book/9780124058910 |
| work_keys_str_mv | AT krishnankrish datawarehousingintheageofbigdata |