Data architecture: a primer for the data scientist : big data, data warehouse and data vault
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Amsterdam
Morgan Kaufman
[2015]
|
| Schlagworte: | |
| Online-Zugang: | FAW01 FLA01 FUBA1 UER01 Volltext |
| Beschreibung: | Today, the world is trying to create and educate data scientists because of the phenomenon of Big Data. And everyone is looking deeply into this technology. But no one is looking at the larger architectural picture of how Big Data needs to fit within the existing systems (data warehousing systems). Taking a look at the larger picture into which Big Data fits gives the data scientist the necessary context for how pieces of the puzzle should fit together. Most references on Big Data look at only one tiny part of a much larger whole. Until data gathered can be put into an existing framework or architecture it can't be used to its full potential. Data Architecture a Primer for the Data Scientist addresses the larger architectural picture of how Big Data fits with the existing information infrastructure, an essential topic for the data scientist. Drawing upon years of practical experience and using numerous examples and an easy to understand framework. W.H. Inmon, and Daniel Linstedt define the importance of data architecture and how it can be used effectively to harness big data within existing systems. You'll be able to: Turn textual information into a form that can be analyzed by standard tools.Make the connection between analytics and Big DataUnderstand how Big Data fits within an existing systems environment Conduct analytics on repetitive and non-repetitive data |
| Beschreibung: | 1 Online-Ressource (xxi, 355 Seiten) Illustrationen, Diagramme |
| ISBN: | 9780128020913 |
Internformat
MARC
| LEADER | 00000nmm a2200000zc 4500 | ||
|---|---|---|---|
| 001 | BV044388814 | ||
| 003 | DE-604 | ||
| 005 | 20211118 | ||
| 007 | cr|uuu---uuuuu | ||
| 008 | 170630s2015 |||| o||u| ||||||eng d | ||
| 015 | |a GBB4D4671 |2 dnb | ||
| 015 | |a GBB4C9342 |2 dnb | ||
| 020 | |a 9780128020913 |c Online |9 978-0-12-802091-3 | ||
| 024 | 7 | |a 10.1016/C2014-0-01420-7 |2 doi | |
| 035 | |a (ZDB-33-ESD)ocn896901332 | ||
| 035 | |a (OCoLC)896901332 | ||
| 035 | |a (DE-599)BVBBV044388814 | ||
| 040 | |a DE-604 |b ger |e rda | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-1046 |a DE-29 |a DE-188 | ||
| 082 | 0 | |a 005.745 |2 23 | |
| 084 | |a ST 530 |0 (DE-625)143679: |2 rvk | ||
| 100 | 1 | |a Inmon, William H. |d 1945- |e Verfasser |0 (DE-588)113317662 |4 aut | |
| 245 | 1 | 0 | |a Data architecture |b a primer for the data scientist : big data, data warehouse and data vault |c William H. Inmon, Daniel Linstedt |
| 264 | 1 | |a Amsterdam |b Morgan Kaufman |c [2015] | |
| 264 | 4 | |c © 2015 | |
| 300 | |a 1 Online-Ressource (xxi, 355 Seiten) |b Illustrationen, Diagramme | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 500 | |a Today, the world is trying to create and educate data scientists because of the phenomenon of Big Data. And everyone is looking deeply into this technology. But no one is looking at the larger architectural picture of how Big Data needs to fit within the existing systems (data warehousing systems). Taking a look at the larger picture into which Big Data fits gives the data scientist the necessary context for how pieces of the puzzle should fit together. Most references on Big Data look at only one tiny part of a much larger whole. Until data gathered can be put into an existing framework or architecture it can't be used to its full potential. Data Architecture a Primer for the Data Scientist addresses the larger architectural picture of how Big Data fits with the existing information infrastructure, an essential topic for the data scientist. Drawing upon years of practical experience and using numerous examples and an easy to understand framework. W.H. Inmon, and Daniel Linstedt define the importance of data architecture and how it can be used effectively to harness big data within existing systems. You'll be able to: Turn textual information into a form that can be analyzed by standard tools.Make the connection between analytics and Big DataUnderstand how Big Data fits within an existing systems environment Conduct analytics on repetitive and non-repetitive data | ||
| 650 | 7 | |a COMPUTERS / Data Modeling & Design |2 bisacsh | |
| 650 | 7 | |a Big data |2 fast | |
| 650 | 7 | |a Data warehousing |2 fast | |
| 650 | 4 | |a Data warehousing | |
| 650 | 4 | |a Big data | |
| 650 | 0 | 7 | |a Big Data |0 (DE-588)4802620-7 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Softwarearchitektur |0 (DE-588)4121677-5 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Data-Warehouse-Konzept |0 (DE-588)4406462-7 |2 gnd |9 rswk-swf |
| 689 | 0 | 0 | |a Big Data |0 (DE-588)4802620-7 |D s |
| 689 | 0 | 1 | |a Data-Warehouse-Konzept |0 (DE-588)4406462-7 |D s |
| 689 | 0 | 2 | |a Softwarearchitektur |0 (DE-588)4121677-5 |D s |
| 689 | 0 | |5 DE-604 | |
| 700 | 1 | |a Linstedt, Daniel |e Verfasser |0 (DE-588)1068367636 |4 aut | |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |z 978-0-12-802044-9 |
| 856 | 4 | 0 | |u http://www.sciencedirect.com/science/book/9780128020449 |x Verlag |z URL des Erstveröffentlichers |3 Volltext |
| 912 | |a ZDB-33-ESD |a ZDB-33-EBS |a ZDB-32-STB | ||
| 999 | |a oai:aleph.bib-bvb.de:BVB01-029791036 | ||
| 966 | e | |u http://www.sciencedirect.com/science/book/9780128020449 |l FAW01 |p ZDB-33-ESD |q FAW_PDA_ESD_Kauf |x Verlag |3 Volltext | |
| 966 | e | |u http://www.sciencedirect.com/science/book/9780128020449 |l FLA01 |p ZDB-33-ESD |q FLA_PDA_ESD |x Verlag |3 Volltext | |
| 966 | e | |u http://www.sciencedirect.com/science/book/9780128020449 |l FUBA1 |p ZDB-33-ESD |q ZDB-33-ESD 2017 |x Verlag |3 Volltext | |
| 966 | e | |u http://www.sciencedirect.com/science/book/9780128020449 |l UER01 |p ZDB-33-EBS |q UER_PDA_EBS_Kauf |x Verlag |3 Volltext | |
Datensatz im Suchindex
| _version_ | 1804177659379318784 |
|---|---|
| any_adam_object | |
| author | Inmon, William H. 1945- Linstedt, Daniel |
| author_GND | (DE-588)113317662 (DE-588)1068367636 |
| author_facet | Inmon, William H. 1945- Linstedt, Daniel |
| author_role | aut aut |
| author_sort | Inmon, William H. 1945- |
| author_variant | w h i wh whi d l dl |
| building | Verbundindex |
| bvnumber | BV044388814 |
| classification_rvk | ST 530 |
| collection | ZDB-33-ESD ZDB-33-EBS ZDB-32-STB |
| ctrlnum | (ZDB-33-ESD)ocn896901332 (OCoLC)896901332 (DE-599)BVBBV044388814 |
| dewey-full | 005.745 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 005 - Computer programming, programs, data, security |
| dewey-raw | 005.745 |
| dewey-search | 005.745 |
| dewey-sort | 15.745 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>03931nmm a2200589zc 4500</leader><controlfield tag="001">BV044388814</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">20211118 </controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">170630s2015 |||| o||u| ||||||eng d</controlfield><datafield tag="015" ind1=" " ind2=" "><subfield code="a">GBB4D4671</subfield><subfield code="2">dnb</subfield></datafield><datafield tag="015" ind1=" " ind2=" "><subfield code="a">GBB4C9342</subfield><subfield code="2">dnb</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9780128020913</subfield><subfield code="c">Online</subfield><subfield code="9">978-0-12-802091-3</subfield></datafield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/C2014-0-01420-7</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-33-ESD)ocn896901332</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)896901332</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV044388814</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-1046</subfield><subfield code="a">DE-29</subfield><subfield code="a">DE-188</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">005.745</subfield><subfield code="2">23</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">ST 530</subfield><subfield code="0">(DE-625)143679:</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Inmon, William H.</subfield><subfield code="d">1945-</subfield><subfield code="e">Verfasser</subfield><subfield code="0">(DE-588)113317662</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Data architecture</subfield><subfield code="b">a primer for the data scientist : big data, data warehouse and data vault</subfield><subfield code="c">William H. Inmon, Daniel Linstedt</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Amsterdam</subfield><subfield code="b">Morgan Kaufman</subfield><subfield code="c">[2015]</subfield></datafield><datafield tag="264" ind1=" " ind2="4"><subfield code="c">© 2015</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (xxi, 355 Seiten)</subfield><subfield code="b">Illustrationen, Diagramme</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">Today, the world is trying to create and educate data scientists because of the phenomenon of Big Data. And everyone is looking deeply into this technology. But no one is looking at the larger architectural picture of how Big Data needs to fit within the existing systems (data warehousing systems). Taking a look at the larger picture into which Big Data fits gives the data scientist the necessary context for how pieces of the puzzle should fit together. Most references on Big Data look at only one tiny part of a much larger whole. Until data gathered can be put into an existing framework or architecture it can't be used to its full potential. Data Architecture a Primer for the Data Scientist addresses the larger architectural picture of how Big Data fits with the existing information infrastructure, an essential topic for the data scientist. Drawing upon years of practical experience and using numerous examples and an easy to understand framework. W.H. Inmon, and Daniel Linstedt define the importance of data architecture and how it can be used effectively to harness big data within existing systems. You'll be able to: Turn textual information into a form that can be analyzed by standard tools.Make the connection between analytics and Big DataUnderstand how Big Data fits within an existing systems environment Conduct analytics on repetitive and non-repetitive data</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">COMPUTERS / Data Modeling & Design</subfield><subfield code="2">bisacsh</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Big data</subfield><subfield code="2">fast</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Data warehousing</subfield><subfield code="2">fast</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Data warehousing</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Big data</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Big Data</subfield><subfield code="0">(DE-588)4802620-7</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Softwarearchitektur</subfield><subfield code="0">(DE-588)4121677-5</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Data-Warehouse-Konzept</subfield><subfield code="0">(DE-588)4406462-7</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="689" ind1="0" ind2="0"><subfield code="a">Big Data</subfield><subfield code="0">(DE-588)4802620-7</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="1"><subfield code="a">Data-Warehouse-Konzept</subfield><subfield code="0">(DE-588)4406462-7</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="2"><subfield code="a">Softwarearchitektur</subfield><subfield code="0">(DE-588)4121677-5</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2=" "><subfield code="5">DE-604</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Linstedt, Daniel</subfield><subfield code="e">Verfasser</subfield><subfield code="0">(DE-588)1068367636</subfield><subfield code="4">aut</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe</subfield><subfield code="z">978-0-12-802044-9</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">http://www.sciencedirect.com/science/book/9780128020449</subfield><subfield code="x">Verlag</subfield><subfield code="z">URL des Erstveröffentlichers</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-33-ESD</subfield><subfield code="a">ZDB-33-EBS</subfield><subfield code="a">ZDB-32-STB</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-029791036</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">http://www.sciencedirect.com/science/book/9780128020449</subfield><subfield code="l">FAW01</subfield><subfield code="p">ZDB-33-ESD</subfield><subfield code="q">FAW_PDA_ESD_Kauf</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">http://www.sciencedirect.com/science/book/9780128020449</subfield><subfield code="l">FLA01</subfield><subfield code="p">ZDB-33-ESD</subfield><subfield code="q">FLA_PDA_ESD</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">http://www.sciencedirect.com/science/book/9780128020449</subfield><subfield code="l">FUBA1</subfield><subfield code="p">ZDB-33-ESD</subfield><subfield code="q">ZDB-33-ESD 2017</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">http://www.sciencedirect.com/science/book/9780128020449</subfield><subfield code="l">UER01</subfield><subfield code="p">ZDB-33-EBS</subfield><subfield code="q">UER_PDA_EBS_Kauf</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield></record></collection> |
| id | DE-604.BV044388814 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T07:51:35Z |
| institution | BVB |
| isbn | 9780128020913 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-029791036 |
| oclc_num | 896901332 |
| open_access_boolean | |
| owner | DE-1046 DE-29 DE-188 |
| owner_facet | DE-1046 DE-29 DE-188 |
| physical | 1 Online-Ressource (xxi, 355 Seiten) Illustrationen, Diagramme |
| psigel | ZDB-33-ESD ZDB-33-EBS ZDB-32-STB ZDB-33-ESD FAW_PDA_ESD_Kauf ZDB-33-ESD FLA_PDA_ESD ZDB-33-ESD ZDB-33-ESD 2017 ZDB-33-EBS UER_PDA_EBS_Kauf |
| publishDate | 2015 |
| publishDateSearch | 2015 |
| publishDateSort | 2015 |
| publisher | Morgan Kaufman |
| record_format | marc |
| 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 William H. Inmon, Daniel Linstedt Amsterdam Morgan Kaufman [2015] © 2015 1 Online-Ressource (xxi, 355 Seiten) Illustrationen, Diagramme txt rdacontent c rdamedia cr rdacarrier Today, the world is trying to create and educate data scientists because of the phenomenon of Big Data. And everyone is looking deeply into this technology. But no one is looking at the larger architectural picture of how Big Data needs to fit within the existing systems (data warehousing systems). Taking a look at the larger picture into which Big Data fits gives the data scientist the necessary context for how pieces of the puzzle should fit together. Most references on Big Data look at only one tiny part of a much larger whole. Until data gathered can be put into an existing framework or architecture it can't be used to its full potential. Data Architecture a Primer for the Data Scientist addresses the larger architectural picture of how Big Data fits with the existing information infrastructure, an essential topic for the data scientist. Drawing upon years of practical experience and using numerous examples and an easy to understand framework. W.H. Inmon, and Daniel Linstedt define the importance of data architecture and how it can be used effectively to harness big data within existing systems. You'll be able to: Turn textual information into a form that can be analyzed by standard tools.Make the connection between analytics and Big DataUnderstand how Big Data fits within an existing systems environment Conduct analytics on repetitive and non-repetitive data COMPUTERS / Data Modeling & Design bisacsh Big data fast Data warehousing fast Data warehousing Big data Big Data (DE-588)4802620-7 gnd rswk-swf Softwarearchitektur (DE-588)4121677-5 gnd rswk-swf Data-Warehouse-Konzept (DE-588)4406462-7 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 Verfasser (DE-588)1068367636 aut Erscheint auch als Druck-Ausgabe 978-0-12-802044-9 http://www.sciencedirect.com/science/book/9780128020449 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Inmon, William H. 1945- Linstedt, Daniel Data architecture a primer for the data scientist : big data, data warehouse and data vault COMPUTERS / Data Modeling & Design bisacsh Big data fast Data warehousing fast Data warehousing Big data Big Data (DE-588)4802620-7 gnd Softwarearchitektur (DE-588)4121677-5 gnd Data-Warehouse-Konzept (DE-588)4406462-7 gnd |
| subject_GND | (DE-588)4802620-7 (DE-588)4121677-5 (DE-588)4406462-7 |
| 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 William H. Inmon, Daniel Linstedt |
| title_fullStr | Data architecture a primer for the data scientist : big data, data warehouse and data vault William H. Inmon, Daniel Linstedt |
| title_full_unstemmed | Data architecture a primer for the data scientist : big data, data warehouse and data vault William 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 | COMPUTERS / Data Modeling & Design bisacsh Big data fast Data warehousing fast Data warehousing Big data Big Data (DE-588)4802620-7 gnd Softwarearchitektur (DE-588)4121677-5 gnd Data-Warehouse-Konzept (DE-588)4406462-7 gnd |
| topic_facet | COMPUTERS / Data Modeling & Design Big data Data warehousing Big Data Softwarearchitektur Data-Warehouse-Konzept |
| url | http://www.sciencedirect.com/science/book/9780128020449 |
| work_keys_str_mv | AT inmonwilliamh dataarchitectureaprimerforthedatascientistbigdatadatawarehouseanddatavault AT linstedtdaniel dataarchitectureaprimerforthedatascientistbigdatadatawarehouseanddatavault |