Anomaly Detection Framework for Big Data als von - 8 Angebote vergleichen
| Preise | 2017 | 2018 | 2019 |
|---|---|---|---|
| Schnitt | € 55,90 | € 56,15 | € 54,55 |
| Nachfrage |
1
Anomaly Detection Framework for Big Data (2017)
DE PB NW RPISBN: 9783330043039 bzw. 3330043032, in Deutsch, LAP Lambert Academic Publishing Mrz 2017, Taschenbuch, neu, Nachdruck.
Von Händler/Antiquariat, AHA-BUCH GmbH [51283250], Einbeck, Germany.
This item is printed on demand - Print on Demand Neuware - Financial service organizations have a number of strategic goals including the acquisition and retention of new and existing customers through the application of various management methodologies. In view of these goals, the institutions generate large volumes of data on profile data, purchase and browsing history and social media data daily. In recent times, businesses have increased the volume of data they process and analyze and this comes at a high computational cost in its analysis. Due to the high increase in the volume of data, most institutions are moving away from the measure of the data volume by volume and considering other parameters. The additional parameters of interest to support evaluation of systems-enabled strategy include variety and velocity. My motivated to design and employ techniques that will stem from both approaches to designing a more hybrid approach which will perform better and also moderate in terms of computational cost. 136 pp. Englisch.
This item is printed on demand - Print on Demand Neuware - Financial service organizations have a number of strategic goals including the acquisition and retention of new and existing customers through the application of various management methodologies. In view of these goals, the institutions generate large volumes of data on profile data, purchase and browsing history and social media data daily. In recent times, businesses have increased the volume of data they process and analyze and this comes at a high computational cost in its analysis. Due to the high increase in the volume of data, most institutions are moving away from the measure of the data volume by volume and considering other parameters. The additional parameters of interest to support evaluation of systems-enabled strategy include variety and velocity. My motivated to design and employ techniques that will stem from both approaches to designing a more hybrid approach which will perform better and also moderate in terms of computational cost. 136 pp. Englisch.
2
Anomaly Detection Framework for Big Data
DE PB NWISBN: 9783330043039 bzw. 3330043032, in Deutsch, LAP Lambert Academic Publishing, Taschenbuch, neu.
Lieferung aus: Deutschland, Versandkostenfrei.
Anomaly Detection Framework for Big Data: Financial service organizations have a number of strategic goals including the acquisition and retention of new and existing customers through the application of various management methodologies. In view of these goals, the institutions generate large volumes of data on profile data, purchase and browsing history and social media data daily. In recent times, businesses have increased the volume of data they process and analyze and this comes at a high computational cost in its analysis. Due to the high increase in the volume of data, most institutions are moving away from the measure of the data volume by volume and considering other parameters. The additional parameters of interest to support evaluation of systems-enabled strategy include variety and velocity. My motivated to design and employ techniques that will stem from both approaches to designing a more hybrid approach which will perform better and also moderate in terms of computational cost. Englisch, Taschenbuch.
Anomaly Detection Framework for Big Data: Financial service organizations have a number of strategic goals including the acquisition and retention of new and existing customers through the application of various management methodologies. In view of these goals, the institutions generate large volumes of data on profile data, purchase and browsing history and social media data daily. In recent times, businesses have increased the volume of data they process and analyze and this comes at a high computational cost in its analysis. Due to the high increase in the volume of data, most institutions are moving away from the measure of the data volume by volume and considering other parameters. The additional parameters of interest to support evaluation of systems-enabled strategy include variety and velocity. My motivated to design and employ techniques that will stem from both approaches to designing a more hybrid approach which will perform better and also moderate in terms of computational cost. Englisch, Taschenbuch.
3
Anomaly Detection Framework for Big Data
DE NWISBN: 9783330043039 bzw. 3330043032, in Deutsch, neu.
Lieferung aus: Vereinigtes Königreich Großbritannien und Nordirland, Lieferzeit: 11 Tage, zzgl. Versandkosten.
Financial service organizations have a number of strategic goals including the acquisition and retention of new and existing customers through the application of various management methodologies. In view of these goals, the institutions generate large volumes of data on profile data, purchase and browsing history and social media data daily. In recent times, businesses have increased the volume of data they process and analyze and this comes at a high computational cost in its analysis. Due to the high increase in the volume of data, most institutions are moving away from the measure of the data volume by volume and considering other parameters. The additional parameters of interest to support evaluation of systems-enabled strategy include variety and velocity. My motivated to design and employ techniques that will stem from both approaches to designing a more hybrid approach which will perform better and also moderate in terms of computational cost.
Financial service organizations have a number of strategic goals including the acquisition and retention of new and existing customers through the application of various management methodologies. In view of these goals, the institutions generate large volumes of data on profile data, purchase and browsing history and social media data daily. In recent times, businesses have increased the volume of data they process and analyze and this comes at a high computational cost in its analysis. Due to the high increase in the volume of data, most institutions are moving away from the measure of the data volume by volume and considering other parameters. The additional parameters of interest to support evaluation of systems-enabled strategy include variety and velocity. My motivated to design and employ techniques that will stem from both approaches to designing a more hybrid approach which will perform better and also moderate in terms of computational cost.
4
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Anomaly Detection Framework for Big Data
DE PB NWISBN: 9783330043039 bzw. 3330043032, in Deutsch, Taschenbuch, neu.
Von Händler/Antiquariat, European-Media-Service Mannheim [1048135], Mannheim, Germany.
Publisher/Verlag: LAP Lambert Academic Publishing | Financial service organizations have a number of strategic goals including the acquisition and retention of new and existing customers through the application of various management methodologies. In view of these goals, the institutions generate large volumes of data on profile data, purchase and browsing history and social media data daily. In recent times, businesses have increased the volume of data they process and analyze and this comes at a high computational cost in its analysis. Due to the high increase in the volume of data, most institutions are moving away from the measure of the data volume by volume and considering other parameters. The additional parameters of interest to support evaluation of systems-enabled strategy include variety and velocity. My motivated to design and employ techniques that will stem from both approaches to designing a more hybrid approach which will perform better and also moderate in terms of computational cost. | Format: Paperback | Language/Sprache: english | 222 gr | 220x150x8 mm | 136 pp.
Publisher/Verlag: LAP Lambert Academic Publishing | Financial service organizations have a number of strategic goals including the acquisition and retention of new and existing customers through the application of various management methodologies. In view of these goals, the institutions generate large volumes of data on profile data, purchase and browsing history and social media data daily. In recent times, businesses have increased the volume of data they process and analyze and this comes at a high computational cost in its analysis. Due to the high increase in the volume of data, most institutions are moving away from the measure of the data volume by volume and considering other parameters. The additional parameters of interest to support evaluation of systems-enabled strategy include variety and velocity. My motivated to design and employ techniques that will stem from both approaches to designing a more hybrid approach which will perform better and also moderate in terms of computational cost. | Format: Paperback | Language/Sprache: english | 222 gr | 220x150x8 mm | 136 pp.
5
Anomaly Detection Framework for Big Data (2017)
EN PB NWISBN: 9783330043039 bzw. 3330043032, in Englisch, 136 Seiten, LAP LAMBERT Academic Publishing, Taschenbuch, neu.
Neu ab: $58.97 (5 Angebote)
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Lieferung aus: Vereinigte Staaten von Amerika, Usually ships in 24 hours.
Von Händler/Antiquariat, Amazon.com.
Financial service organizations have a number of strategic goals including the acquisition and retention of new and existing customers through the application of various management methodologies. In view of these goals, the institutions generate large volumes of data on profile data, purchase and browsing history and social media data daily. In recent times, businesses have increased the volume of data they process and analyze and this comes at a high computational cost in its analysis. Due to the high increase in the volume of data, most institutions are moving away from the measure of the data volume by volume and considering other parameters. The additional parameters of interest to support evaluation of systems-enabled strategy include variety and velocity. My motivated to design and employ techniques that will stem from both approaches to designing a more hybrid approach which will perform better and also moderate in terms of computational cost. Paperback, Label: LAP LAMBERT Academic Publishing, LAP LAMBERT Academic Publishing, Produktgruppe: Book, Publiziert: 2017-02-06, Freigegeben: 2017-02-06, Studio: LAP LAMBERT Academic Publishing, Verkaufsrang: 8806553.
Von Händler/Antiquariat, Amazon.com.
Financial service organizations have a number of strategic goals including the acquisition and retention of new and existing customers through the application of various management methodologies. In view of these goals, the institutions generate large volumes of data on profile data, purchase and browsing history and social media data daily. In recent times, businesses have increased the volume of data they process and analyze and this comes at a high computational cost in its analysis. Due to the high increase in the volume of data, most institutions are moving away from the measure of the data volume by volume and considering other parameters. The additional parameters of interest to support evaluation of systems-enabled strategy include variety and velocity. My motivated to design and employ techniques that will stem from both approaches to designing a more hybrid approach which will perform better and also moderate in terms of computational cost. Paperback, Label: LAP LAMBERT Academic Publishing, LAP LAMBERT Academic Publishing, Produktgruppe: Book, Publiziert: 2017-02-06, Freigegeben: 2017-02-06, Studio: LAP LAMBERT Academic Publishing, Verkaufsrang: 8806553.
6
Anomaly Detection Framework for (2017)
DE PB NWISBN: 9783330043039 bzw. 3330043032, in Deutsch, Taschenbuch, neu.
Lieferung aus: Deutschland, Next Day, Versandkostenfrei.
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Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
8
9783330043039 Anomaly Detection Framework for Big Data - Nana Kwame Gyamfi,Ferdi
DE NWISBN: 9783330043039 bzw. 3330043032, in Deutsch, neu.
Lieferung aus: Italien, Lieferart: Flat, Lieferung: Weltweit, Artikelstandort: Italy.
Von Händler/Antiquariat, cinemamovie.store - CINEMA MOVIE STORE.
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Von Händler/Antiquariat, cinemamovie.store - CINEMA MOVIE STORE.
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