Amazon Dossier

Total Page:16

File Type:pdf, Size:1020Kb

Amazon Dossier Fluch und Segen für Markenhersteller Markus Fost Inhalt des Dossiers amazon – Fluch und Segen für Markenhersteller 1 Facts & Figures von Amazon 2 Das Amazon Geschäftsmodell – ein komplexes Ökosystem 3 Technische Infrastruktur von Amazon 4 Relevanz von Amazon im Herstellerumfeld 5 Das Amazon Ranking – Entscheidend für die Sichtbarkeit von Markenhersteller 6 Ausblick und Thesen Seite . 2 Dossier | amazon – Fluch und Segen für Markenhersteller | © FOSTEC Commerce Consultants Vorstellung Leistungsspektrum FOSTEC Commerce Consultants ANALYSE . Pragmatische Analyse von Strategie, USP, Geschäftsmodell und Prozessen mit dem Fokus auf die digitale Welt mittels einer Umfeld- und Customer Journey Analyse . Ergebnis: Status quo, Handlungsoptionen und Optimierungsansätze ZIELDEFINITION . Auf Basis Ihrer Ziele mit unserem Know-How gemeinsames Entwickeln eines Best-in-Class Digitalstrategie . Ergebnis: Blueprint Ihrer Digitalstrategie inklusive (E-Commerce) Distributionsstrategie, Quick-wins, Systemevaluation UMSETZUNG . Mit Projekterfahrung und Methodenkompetenz unterstützen wir Ihre Umsetzung zur digitalen Transformation . Ergebnis: Nachhaltig erfolgreiches Geschäftsmodell Seite . 3 Dossier | amazon – Fluch und Segen für Markenhersteller | © FOSTEC Commerce Consultants Vorstellung Warum FOSTEC der richtige Diskussionspartner ist . Erfahrene Experten beraten Sie individuell und auf Augenhöhe . Persönliche Betreuung durch ein inhabergeführtes Beratungsunternehmen . Wir wählen effiziente Methoden, um Sie schnellstmöglich an das Ziel zu bringen . Hohe Umsetzungsorientierung und operative Exzellenz in allen Beratungsschritten . Wir beherrschen nicht nur die Theorie, sondern beweisen uns tagtäglich in der Umsetzung . Wir beteiligen uns an Unternehmen mittels FOSTEC Ventures Seite . 4 Dossier | amazon – Fluch und Segen für Markenhersteller | © FOSTEC Commerce Consultants Inhalt des Dossiers amazon – Fluch und Segen für Markenhersteller Facts & Figures von Amazon 2 Das Amazon Geschäftsmodell – ein komplexes Ökosystem 3 Technische Infrastruktur von Amazon 4 Relevanz von Amazon im Herstellerumfeld 5 Das Amazon Ranking – Entscheidend für die Sichtbarkeit von Markenhersteller 6 Ausblick und Thesen Seite . 5 Dossier | amazon – Fluch und Segen für Markenhersteller | © FOSTEC Commerce Consultants Amazon.com wurde 1994 in einer Garage gegründet und sollte eigentlich „relentless“ heißen 1994 Jeff Bezos In einer Garage Die Gründung Als Online-Buchhandel In Washington Seite . 6 Dossier | amazon – Fluch und Segen für Markenhersteller | © FOSTEC Commerce Consultants Amazon – Eine Umsatzmaschine mit überproportionalem Wachstum im E-Commerce ca. 10 Mio. Amazon-Prime-Kunden mit einem durchschnittlichen Bestellwert von EUR 1.224 / Jahr. 30 % der Verbraucher beginnen ihre Produktsuche auf Amazon. (13% der Verbraucher auf Google) Quelle: WHITE PAPER VON CHANNELADVISOR, Weshalb Amazon nicht der Feind des Onlinehandels ist; InternetHandel (2014) Seite . 7 Dossier | amazon – Fluch und Segen für Markenhersteller | © FOSTEC Commerce Consultants Die Champions-League im globalen E-Commerce besteht aus nur 3 Spielern! . Umsatzvolumen 2013 74,45 Mrd. EUR 16,05 Umsatz Mrd. EUR 7,95 Umsatz Mrd. EUR Umsatz 2 1 3 Zum Vergleich: Die Deutsche Nr. 1 (nach Amazon) bringt es auf 1,95 Mrd. EUR Quelle: Statista (2014) Seite . 8 Dossier | amazon – Fluch und Segen für Markenhersteller | © FOSTEC Commerce Consultants Auch in puncto Wachstum spielen Amazon, eBay und Alibaba in ihrer eigenen Liga . Brutto-Außenumsatz Amazon.com & eBay vs. Alibaba / Taobao, 1995 - 2012 $150 Amazon.com eBay Alibaba / Taobao $100 in Mrd. Mrd. USD in $50 Brutto Handelsvolumen Handelsvolumen Brutto $0 1995 1997 1999 2001 2003 2005 2007 2009 2011 Quelle: Kleiner Perkins (2013) Seite . 9 Dossier | amazon – Fluch und Segen für Markenhersteller | © FOSTEC Commerce Consultants eBay und Amazon im Vergleich 85% der Deutschen bevorzugen Amazon Amazon eBay 85,16% 14,44% Gründe: . Einkauf bei eBay ist komplizierter . und benötigt mehr Zeit * Online-Befragung von 10.000 Nutzern Quelle: InternetHandel (2014) Seite . 10 Dossier | amazon – Fluch und Segen für Markenhersteller | © FOSTEC Commerce Consultants Erfolg macht blind: Ein Praxisbeispiel der Otto Group Quelle: dGroup(2014) Seite . 11 Dossier | amazon – Fluch und Segen für Markenhersteller | © FOSTEC Commerce Consultants Getrieben von operativer Exzellenz im Kerngeschäft konnte OTTO seine Marktposition gegenüber den etablierten Wettbewerbern halten Quelle: dGroup(2014) Seite . 12 Dossier | amazon – Fluch und Segen für Markenhersteller | © FOSTEC Commerce Consultants Aber: Andere Player – andere Spielregeln Quelle: dGroup(2014) Seite . 13 Dossier | amazon – Fluch und Segen für Markenhersteller | © FOSTEC Commerce Consultants Die Chance für OTTO den Markt im ursprünglichen Geschäftsmodell weiter zu führen wurde uneinholbar vertan Quelle: dGroup(2014) Seite . 14 Dossier | amazon – Fluch und Segen für Markenhersteller | © FOSTEC Commerce Consultants Alternative Zukunftskonzepte sind die letzte Chance weiter eine dominante Rolle im Markt zu Quelle: dGroup(2014) Seite . 15 Dossier | amazon – Fluch und Segen für Markenhersteller | © FOSTEC Commerce Consultants Im Reichweitenvergleich Die 10 größten Online-Shops in Deutschland Besucherzahlen in Mio. 0 5 10 15 20 25 Amazon 22,51 eBay 21,02 Otto 4,73 Tchibo 3,97 Reichweite in Prozent Zalando 3,82 Lidl 3,3 0 10 20 30 40 Bon Prix 2,79 Amazon 41,11 eBay 38,38 Weltbild 2,47 Otto 8,64 Conrad 2,39 Tchibo 7,24 Ikea 2,24 Zalando 6,97 Lidl 6,03 Bon Prix 5,1 Weltbild 4,51 Conrad 4,37 Ikea 4,09 Quelle: Statista, E-Commerce-Markt-Deutschland 2014 Seite . 16 Dossier | amazon – Fluch und Segen für Markenhersteller | © FOSTEC Commerce Consultants Amazon wächst weiter ohne Rücksicht auf die Profitabilität Handelsvolumen 2013 in Mrd. Dollar 100 76 248 80 Umsatz Gewinn CAGR = 30.21% 70 60 Dollar Umsatz 2013 in Mrd. Dollar - 50 74,45 40 16,05 30 20 7,95 10 CAGR = -7.60% 0 Gewinn 2013 in Mrd. Dollar US in Mrd. Nettoumsatz 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 -10 0,27 2,86 3,56 Quelle: Unternehmensangabe, Forester Research Seite . 17 Dossier | amazon – Fluch und Segen für Markenhersteller | © FOSTEC Commerce Consultants Amazon ist eingeschränkt profitabel, jedoch erfolgen massive Investitionen in die Erweiterung der Wertschöpfungskette . Investitionen und Abschreibungen 2014 Fire Phone 170 Mio. Dollar Abschreibung Set Top Box N/A Gaming-Video-Website Twitch 970 Mio. Dollar Kaufpreis E-Book Flatrate Kindle Unlimited N/A Musik-Streamingdienst / Prime Instant Video N/A >> vgl. Netflix Quelle: Internetworld (2014) Seite . 18 Dossier | amazon – Fluch und Segen für Markenhersteller | © FOSTEC Commerce Consultants Das Beispiel netflix zeigt, welches Investitionsvolumen notwendig ist, um einen Streamingdienst zur Profitabilität zu führen 250 Gewinn nach Steuern (in Mio. USD) 200 150 100 50 0 -50 1998 2014 Quelle: Netflix (2014) Seite . 19 Dossier | amazon – Fluch und Segen für Markenhersteller | © FOSTEC Commerce Consultants Amazon`s operativer Cash-Flow auf Rekordniveau Quelle: hbr.org (2014) Seite . 20 Dossier | amazon – Fluch und Segen für Markenhersteller | © FOSTEC Commerce Consultants Aktueller Wert eines 1000 USD Investments beim IPO ausgewählter Internetunternehmen* Amazon.com eBay Yahoo Google Facebook 1.000$ 1.000$ 1.000$ 1.000$ 1.000$ 15.05.1997 24.09.1998 12.04.1996 19.08.2004 18.05.2012 Aktuell Aktuell Aktuell Aktuell Aktuell 239.045$ 68.638$ 61.052$ 12.072$ 1.269$ * Stand 04.11.2013, Splits und Dividenden berücksichtigt, Werte gerundet Quelle: Statista , Yahoo! Finance Seite . 21 Dossier | amazon – Fluch und Segen für Markenhersteller | © FOSTEC Commerce Consultants Inhalt des Dossiers amazon – Fluch und Segen für Markenhersteller 1 Facts & Figures von Amazon Das Amazon Geschäftsmodell – ein komplexes Ökosystem 3 Technische Infrastruktur von Amazon 4 Relevanz von Amazon im Herstellerumfeld 5 Das Amazon Ranking – Entscheidend für die Sichtbarkeit von Markenhersteller 6 Ausblick und Thesen Seite . 22 Dossier | amazon – Fluch und Segen für Markenhersteller | © FOSTEC Commerce Consultants Amazon Vendor Central (Kunde / Lieferanten Beziehung) Vendor Marketplace Marketplace & FBA Vendor (Lieferant beliefert Amazon) Amazon Supply (US) . I.d.R. Markenherstellern und Großhändlern vorbehalten . Artikel werden an ein Logistik-Zentrum geliefert (Retouren wickelt Amazon ab) Amazon S3 . Artikel werden eventuell kostenlos verschickt (Prime) . Kunden können ihre Artikel kombinieren Amazon Web Services . 83% der Teilnehmer berichten von einer Steigerung ihrer Verkäufe Amazon A9 Quelle: http://services.amazon.de/programme/versand-durch-amazon/so-funktionierts.html Seite . 23 Dossier | amazon – Fluch und Segen für Markenhersteller | © FOSTEC Commerce Consultants Beispiel: Amazon Vendor Central (Kunde Lieferanten Beziehung) Seite . 24 Dossier | amazon – Fluch und Segen für Markenhersteller | © FOSTEC Commerce Consultants Amazon Marketplace(Seller Central) (Marktplatz / Händler Beziehung) Vendor Marketplace Marketplace & FBA Amazon Marketplace Amazon Supply (US) . Für Händler und „No-Name-Brands“ . Artikel werden über Textdatei, XML oder das Seller Central in Amazon eingestellt Amazon S3 . Artikel werden selbst kommissioniert und verschickt . Amazon schreibt dem Händler die Erlöse gut und Amazon Web Services überweist diese im 14 tägigem Rhythmus Wachstumsgrenze Transaktionskosten für Teilnehmer zwischen 15- Amazon A9 für kurzfristig profitables19% je nach Warengruppe Geschäft Quelle: http://services.amazon.de/programme/online-verkaufen/so-funktionierts.html
Recommended publications
  • Timeline 1994 July Company Incorporated 1995 July Amazon
    Timeline 1994 July Company Incorporated 1995 July Amazon.com Sells First Book, “Fluid Concepts & Creative Analogies: Computer Models of the Fundamental Mechanisms of Thought” 1996 July Launches Amazon.com Associates Program 1997 May Announces IPO, Begins Trading on NASDAQ Under “AMZN” September Introduces 1-ClickTM Shopping November Opens Fulfillment Center in New Castle, Delaware 1998 February Launches Amazon.com Advantage Program April Acquires Internet Movie Database June Opens Music Store October Launches First International Sites, Amazon.co.uk (UK) and Amazon.de (Germany) November Opens DVD/Video Store 1999 January Opens Fulfillment Center in Fernley, Nevada March Launches Amazon.com Auctions April Opens Fulfillment Center in Coffeyville, Kansas May Opens Fulfillment Centers in Campbellsville and Lexington, Kentucky June Acquires Alexa Internet July Opens Consumer Electronics, and Toys & Games Stores September Launches zShops October Opens Customer Service Center in Tacoma, Washington Acquires Tool Crib of the North’s Online and Catalog Sales Division November Opens Home Improvement, Software, Video Games and Gift Ideas Stores December Jeff Bezos Named TIME Magazine “Person Of The Year” 2000 January Opens Customer Service Center in Huntington, West Virginia May Opens Kitchen Store August Announces Toys “R” Us Alliance Launches Amazon.fr (France) October Opens Camera & Photo Store November Launches Amazon.co.jp (Japan) Launches Marketplace Introduces First Free Super Saver Shipping Offer (Orders Over $100) 2001 April Announces Borders Group Alliance August Introduces In-Store Pick Up September Announces Target Stores Alliance October Introduces Look Inside The BookTM 2002 June Launches Amazon.ca (Canada) July Launches Amazon Web Services August Lowers Free Super Saver Shipping Threshold to $25 September Opens Office Products Store November Opens Apparel & Accessories Store 2003 April Announces National Basketball Association Alliance June Launches Amazon Services, Inc.
    [Show full text]
  • Performance at Scale with Amazon Elasticache
    Performance at Scale with Amazon ElastiCache July 2019 Notices Customers are responsible for making their own independent assessment of the information in this document. This document: (a) is for informational purposes only, (b) represents current AWS product offerings and practices, which are subject to change without notice, and (c) does not create any commitments or assurances from AWS and its affiliates, suppliers or licensors. AWS products or services are provided “as is” without warranties, representations, or conditions of any kind, whether express or implied. The responsibilities and liabilities of AWS to its customers are controlled by AWS agreements, and this document is not part of, nor does it modify, any agreement between AWS and its customers. © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved. Contents Introduction .......................................................................................................................... 1 ElastiCache Overview ......................................................................................................... 2 Alternatives to ElastiCache ................................................................................................. 2 Memcached vs. Redis ......................................................................................................... 3 ElastiCache for Memcached ............................................................................................... 5 Architecture with ElastiCache for Memcached ...............................................................
    [Show full text]
  • Amazon Elasticache Deep Dive Powering Modern Applications with Low Latency and High Throughput
    Amazon ElastiCache Deep Dive Powering modern applications with low latency and high throughput Michael Labib Sr. Manager, Non-Relational Databases © 2020, Amazon Web Services, Inc. or its Affiliates. Agenda • Introduction to Amazon ElastiCache • Redis Topologies & Features • ElastiCache Use Cases • Monitoring, Sizing & Best Practices © 2020, Amazon Web Services, Inc. or its Affiliates. Introduction to Amazon ElastiCache © 2020, Amazon Web Services, Inc. or its Affiliates. Purpose-built databases © 2020, Amazon Web Services, Inc. or its Affiliates. Purpose-built databases © 2020, Amazon Web Services, Inc. or its Affiliates. Modern real-time applications require Performance, Scale & Availability Users 1M+ Data volume Terabytes—petabytes Locality Global Performance Microsecond latency Request rate Millions per second Access Mobile, IoT, devices Scale Up-out-in E-Commerce Media Social Online Shared economy Economics Pay-as-you-go streaming media gaming Developer access Open API © 2020, Amazon Web Services, Inc. or its Affiliates. Amazon ElastiCache – Fully Managed Service Redis & Extreme Secure Easily scales to Memcached compatible performance and reliable massive workloads Fully compatible with In-memory data store Network isolation, encryption Scale writes and open source Redis and cache for microsecond at rest/transit, HIPAA, PCI, reads with sharding and Memcached response times FedRAMP, multi AZ, and and replicas automatic failover © 2020, Amazon Web Services, Inc. or its Affiliates. What is Redis? Initially released in 2009, Redis provides: • Complex data structures: Strings, Lists, Sets, Sorted Sets, Hash Maps, HyperLogLog, Geospatial, and Streams • High-availability through replication • Scalability through online sharding • Persistence via snapshot / restore • Multi-key atomic operations A high-speed, in-memory, non-Relational data store. • LUA scripting Customers love that Redis is easy to use.
    [Show full text]
  • Amazon Mechanical Turk Developer Guide API Version 2017-01-17 Amazon Mechanical Turk Developer Guide
    Amazon Mechanical Turk Developer Guide API Version 2017-01-17 Amazon Mechanical Turk Developer Guide Amazon Mechanical Turk: Developer Guide Copyright © Amazon Web Services, Inc. and/or its affiliates. All rights reserved. Amazon's trademarks and trade dress may not be used in connection with any product or service that is not Amazon's, in any manner that is likely to cause confusion among customers, or in any manner that disparages or discredits Amazon. All other trademarks not owned by Amazon are the property of their respective owners, who may or may not be affiliated with, connected to, or sponsored by Amazon. Amazon Mechanical Turk Developer Guide Table of Contents What is Amazon Mechanical Turk? ........................................................................................................ 1 Mechanical Turk marketplace ....................................................................................................... 1 Marketplace rules ............................................................................................................... 2 The sandbox marketplace .................................................................................................... 2 Tasks that work well on Mechanical Turk ...................................................................................... 3 Tasks can be completed within a web browser ....................................................................... 3 Work can be broken into distinct, bite-sized tasks .................................................................
    [Show full text]
  • Integration with Amazon S3
    Integration with Amazon S3 YourDataConnect has developed a solution to ingest metadata from the AWS S3 file system into YourDataConnect. Amazon S3 can store multiple object types which enables storage for Internet applications, backup and recovery, disaster recovery, data archives, data lakes for analytics, and hybrid cloud storage. Figure 1 shows an AWS S3 bucket and folders. Figure 1: AWS S3 bucket and folders. Figure 2 shows a preview of the csv file in AWS S3. Figure 2: Preview of data in AWS Copyright © 2020, YourDataConnect. All rights reserved. Integration of Amazon S3 with YourDataConnect has developed a solution to import the file system, S3 bucket, directory, filegroup, file, and field metadata from Amazon S3 intoYourDataConnect while maintaining the hierarchy between S3 objects (see Figure 3). Figure 3: End-to-end traceability of Amazon S3 objects in YourDataConnect To learn more about this solution, please request a demo by contacting [email protected] or visit our website at yourdataconnect.com. Copyright © 2020, YourDataConnect. All rights reserved. This document is provided for information purposes only, and the contents hereof are subject to change without notice. This document is not warranted to be error-free, nor is it subject to any other warranties or conditions, whether expressed orally or implied in law, including implied warranties and conditions of merchantability or fitness for a particular purpose. We specifically disclaim any liability with respect to this document, and no contrac tual obligations are formed either directly or indirectly by this document. This document may not be reproduced or transmitted in any form or by any means, electronic or mechanical, for any purpose, without our prior written permission..
    [Show full text]
  • Labeling Parts of Speech Using Untrained Annotators on Mechanical Turk THESIS Presented in Partial Fulfillment of the Requiremen
    Labeling Parts of Speech Using Untrained Annotators on Mechanical Turk THESIS Presented in Partial Fulfillment of the Requirements for the Degree Master of Science in the Graduate School of The Ohio State University By Jacob Emil Mainzer Graduate Program in Computer Science and Engineering The Ohio State University 2011 Master's Examination Committee: Professor Eric Fosler-Lussier, Advisor Professor Mikhail Belkin Copyright by Jacob Emil Mainzer 2011 Abstract Supervised learning algorithms often require large amounts of labeled data. Creating this data can be time consuming and expensive. Recent work has used untrained annotators on Mechanical Turk to quickly and cheaply create data for NLP tasks, such as word sense disambiguation, word similarity, machine translation, and PP attachment. In this experiment, we test whether untrained annotators can accurately perform the task of POS tagging. We design a Java Applet, called the Interactive Tagging Guide (ITG) to assist untrained annotators in accurately and quickly POS tagging words using the Penn Treebank tagset. We test this Applet on a small corpus using Mechanical Turk, an online marketplace where users earn small payments for the completion of short tasks. Our results demonstrate that, given the proper assistance, untrained annotators are able to tag parts of speech with approximately 90% accuracy. Furthermore, we analyze the performance of expert annotators using the ITG and discover nearly identical levels of performance as compared to the untrained annotators. ii Vita 2009................................................................B.S. Physics, University of Rochester September 2009 – August 2010 .....................Distinguished University Fellowship, The Ohio State University September 2010 – June 2011 .........................Graduate Teaching Assistant, The Ohio State University Fields of Study Major Field: Computer Science and Engineering iii Table of Contents Abstract ..............................................................................................................................
    [Show full text]
  • Analytics Lens AWS Well-Architected Framework Analytics Lens AWS Well-Architected Framework
    Analytics Lens AWS Well-Architected Framework Analytics Lens AWS Well-Architected Framework Analytics Lens: AWS Well-Architected Framework Copyright © Amazon Web Services, Inc. and/or its affiliates. All rights reserved. Amazon's trademarks and trade dress may not be used in connection with any product or service that is not Amazon's, in any manner that is likely to cause confusion among customers, or in any manner that disparages or discredits Amazon. All other trademarks not owned by Amazon are the property of their respective owners, who may or may not be affiliated with, connected to, or sponsored by Amazon. Analytics Lens AWS Well-Architected Framework Table of Contents Abstract ............................................................................................................................................ 1 Abstract .................................................................................................................................... 1 Introduction ...................................................................................................................................... 2 Definitions ................................................................................................................................. 2 Data Ingestion Layer ........................................................................................................... 2 Data Access and Security Layer ............................................................................................ 3 Catalog and Search Layer ...................................................................................................
    [Show full text]
  • Amazon Mechanical Turk Requester UI Guide Amazon Mechanical Turk Requester UI Guide
    Amazon Mechanical Turk Requester UI Guide Amazon Mechanical Turk Requester UI Guide Amazon Mechanical Turk: Requester UI Guide Copyright © 2014 Amazon Web Services, Inc. and/or its affiliates. All rights reserved. The following are trademarks of Amazon Web Services, Inc.: Amazon, Amazon Web Services Design, AWS, Amazon CloudFront, Cloudfront, Amazon DevPay, DynamoDB, ElastiCache, Amazon EC2, Amazon Elastic Compute Cloud, Amazon Glacier, Kindle, Kindle Fire, AWS Marketplace Design, Mechanical Turk, Amazon Redshift, Amazon Route 53, Amazon S3, Amazon VPC. In addition, Amazon.com graphics, logos, page headers, button icons, scripts, and service names are trademarks, or trade dress of Amazon in the U.S. and/or other countries. Amazon©s trademarks and trade dress may not be used in connection with any product or service that is not Amazon©s, in any manner that is likely to cause confusion among customers, or in any manner that disparages or discredits Amazon. All other trademarks not owned by Amazon are the property of their respective owners, who may or may not be affiliated with, connected to, or sponsored by Amazon. Amazon Mechanical Turk Requester UI Guide Table of Contents Welcome ..................................................................................................................................... 1 How Do I...? ......................................................................................................................... 1 Introduction to Mechanical Turk .......................................................................................................
    [Show full text]
  • AWS SDK for .NET Developer Guide Version V2.0.0 AWS SDK for .NET Developer Guide
    AWS SDK for .NET Developer Guide Version v2.0.0 AWS SDK for .NET Developer Guide AWS SDK for .NET: Developer Guide Copyright © 2014 Amazon Web Services, Inc. and/or its affiliates. All rights reserved. The following are trademarks of Amazon Web Services, Inc.: Amazon, Amazon Web Services Design, AWS, Amazon CloudFront, Cloudfront, CloudTrail, Amazon DevPay, DynamoDB, ElastiCache, Amazon EC2, Amazon Elastic Compute Cloud, Amazon Glacier, Kinesis, Kindle, Kindle Fire, AWS Marketplace Design, Mechanical Turk, Amazon Redshift, Amazon Route 53, Amazon S3, Amazon VPC. In addition, Amazon.com graphics, logos, page headers, button icons, scripts, and service names are trademarks, or trade dress of Amazon in the U.S. and/or other countries. Amazon©s trademarks and trade dress may not be used in connection with any product or service that is not Amazon©s, in any manner that is likely to cause confusion among customers, or in any manner that disparages or discredits Amazon. All other trademarks not owned by Amazon are the property of their respective owners, who may or may not be affiliated with, connected to, or sponsored by Amazon. AWS SDK for .NET Developer Guide Table of Contents AWS SDK for .NET Developer Guide ................................................................................................ 1 How to Use This Guide ........................................................................................................... 1 Supported Services and Revision History .................................................................................
    [Show full text]
  • What Is Amazon Elasticache?
    Amazon ElastiCache User Guide API Version 2015-02-02 Amazon ElastiCache User Guide Amazon ElastiCache: User Guide Copyright © 2015 Amazon Web Services, Inc. and/or its affiliates. All rights reserved. AWS services or capabilities described in AWS Documentation may vary by region/location. Click Getting Started with Amazon AWS to see specific differences applicable to the China (Beijing) Region. The following are trademarks of Amazon Web Services, Inc.: Amazon, Amazon Web Services Design, AWS, Amazon CloudFront, AWS CloudTrail, AWS CodeDeploy, Amazon Cognito, Amazon DevPay, DynamoDB, ElastiCache, Amazon EC2, Amazon Elastic Compute Cloud, Amazon Glacier, Amazon Kinesis, Kindle, Kindle Fire, AWS Marketplace Design, Mechanical Turk, Amazon Redshift, Amazon Route 53, Amazon S3, Amazon VPC, and Amazon WorkDocs. In addition, Amazon.com graphics, logos, page headers, button icons, scripts, and service names are trademarks, or trade dress of Amazon in the U.S. and/or other countries. Amazon©s trademarks and trade dress may not be used in connection with any product or service that is not Amazon©s, in any manner that is likely to cause confusion among customers, or in any manner that disparages or discredits Amazon. All other trademarks not owned by Amazon are the property of their respective owners, who may or may not be affiliated with, connected to, or sponsored by Amazon. AWS services or capabilities described in AWS Documentation may vary by region/location. Click Getting Started with Amazon AWS to see specific differences applicable to the China (Beijing) Region. Amazon ElastiCache User Guide Table of Contents What Is Amazon ElastiCache? ......................................................................................................... 1 Amazon ElastiCache Videos .................................................................................................... 2 Introductory Videos .......................................................................................................
    [Show full text]
  • How Can Startups Make Use of Cloud Services
    California State University, San Bernardino CSUSB ScholarWorks Electronic Theses, Projects, and Dissertations Office of aduateGr Studies 4-2021 How can startups make use of cloud services Gauri Nade Gauri Nade California State University - San Bernardino Follow this and additional works at: https://scholarworks.lib.csusb.edu/etd Part of the Educational Technology Commons Recommended Citation Nade, Gauri and Nade, Gauri, "How can startups make use of cloud services" (2021). Electronic Theses, Projects, and Dissertations. 1262. https://scholarworks.lib.csusb.edu/etd/1262 This Thesis is brought to you for free and open access by the Office of aduateGr Studies at CSUSB ScholarWorks. It has been accepted for inclusion in Electronic Theses, Projects, and Dissertations by an authorized administrator of CSUSB ScholarWorks. For more information, please contact [email protected]. HOW CAN START UPS MAKE USE OF CLOUD SERVICES A Project Presented to the Faculty of California State University, San Bernardino In Partial Fulfillment of the Requirements for the Degree Master of Science in Information Systems and Technology by Gauri Rajendra Nade May 2021 HOW CAN START UPS MAKE USE OF CLOUD SERVICES A Project Presented to the Faculty of California State University, San Bernardino by Gauri Rajendra Nade May 2021 Approved by: Benjamin Becerra, PhD, Committee Chair Conrad Shayo, PhD, Reader Jay Varzandeh, PhD, Dept. Chair, Information & Decision Sciences © 2021 Gauri Rajendra Nade ABSTRACT The purpose of this project is to discuss the technical obstacles that small and medium-sized enterprises (SMEs) face, as well as how cloud computing can help to solve these issues. Cloud computing has the ability to radically change competitive environments by offering a new forum for generating and delivering business value and market development.
    [Show full text]
  • An Improved Prepost Algorithm for Frequent Pattern Mining with Hadoop on Cloud
    Available online at www.sciencedirect.com ScienceDirect Procedia Computer Science 79 ( 2016 ) 207 – 214 7th International Conference on Communication, Computing and Virtualization 2016 An Improved PrePost Algorithm for Frequent Pattern Mining with Hadoop on Cloud Sanket Thakarea, Sheetal Rathib, R.R.Sedamkarc aME Scholar, Thakur College of Engineering and Technology, Mumbai- 400101, India bAssistant Professor, Thakur College of Engineering and Technology, Mumbai- 400101, India cProfessor, Thakur College of Engineering and Technology, Mumbai-400101, India Abstract Due to the advancement in internet technologies the volume of data is tremendously increasing day by day. The research is gaining importance in extracting valuable information from such huge amount of data. Many research works are done and various algorithms are proposed. The PrePost algorithm is one of well-known algorithms of frequent pattern mining. It is based on N-list data structure to mine frequent item-sets. But the performance of PrePost algorithm degrades when it comes to processing of large amount of data. Hadoop is very well known technique for processing such large amount of data. This paper proposes the Improved PrePost algorithm which combines the features of Hadoop in order to process large data efficiently. Efficiency of PrePost algorithm is enhanced by implementing compact PPC tree with the general tree method and finding frequent itemsets without generating candidate itemsets. An architecture of the Improved PrePost algorithm with public cloud is proposed. The results show that as dataset size is increased, the Improved PrePost algorithm gives 60% better performance. Keywords: Big Data, Data Mining, PPC Tree, Data Node, Name Node, Cloud Computing, S3 Storage 1.
    [Show full text]