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		<title>AWS Summit Series 2015 &#124; Tel Aviv: Amazon Redshift</title>
		<link>http://amazonblogstore.com/aws-summit-series-2015-tel-aviv-amazon-redshift/</link>
		<comments>http://amazonblogstore.com/aws-summit-series-2015-tel-aviv-amazon-redshift/#comments</comments>
		<pubDate>Wed, 23 Sep 2015 08:13:37 +0000</pubDate>
		<dc:creator><![CDATA[admin]]></dc:creator>
				<category><![CDATA[Amazon Customer Service Videos]]></category>
		<category><![CDATA[2015 Summit Series AWS]]></category>
		<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[amazon web services]]></category>
		<category><![CDATA[aws]]></category>
		<category><![CDATA[AWS Cloud]]></category>
		<category><![CDATA[AWS SUmmit Tel Aviv]]></category>
		<category><![CDATA[AWS SUmmits 2015]]></category>
		<category><![CDATA[cloud]]></category>
		<category><![CDATA[cloud computing]]></category>
		<category><![CDATA[redshift]]></category>
		<category><![CDATA[Tel Av...]]></category>

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		<description><![CDATA[Watch the Deep-Dive Session of Amazon Redshift at the AWS Summit Tel Aviv 2015. Learn more: https://aws.amazon.com/redshift]]></description>
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		<title>UMUC Builds New Analytics Platform Using Amazon Redshift</title>
		<link>http://amazonblogstore.com/umuc-builds-new-analytics-platform-using-amazon-redshift/</link>
		<comments>http://amazonblogstore.com/umuc-builds-new-analytics-platform-using-amazon-redshift/#comments</comments>
		<pubDate>Wed, 23 Sep 2015 08:12:29 +0000</pubDate>
		<dc:creator><![CDATA[admin]]></dc:creator>
				<category><![CDATA[Amazon Customer Service Videos]]></category>
		<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[amazon web services]]></category>
		<category><![CDATA[aws]]></category>
		<category><![CDATA[AWS Cloud]]></category>
		<category><![CDATA[cloud]]></category>
		<category><![CDATA[cloud computing]]></category>
		<category><![CDATA[data]]></category>
		<category><![CDATA[Software (Industry)]]></category>
		<category><![CDATA[technology]]></category>

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		<description><![CDATA[Learn how UMUC improved its extract, transform, and load (ETL) performance by twentyfold building its new analytics platform on AWS using Amazon Redshift.]]></description>
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<p><span itemprop='description'>Learn how UMUC improved its extract, transform, and load (ETL) performance by twentyfold building its new analytics platform on AWS using Amazon Redshift.</span></p>
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		<title>Overview  The AWS Big Data Platform</title>
		<link>http://amazonblogstore.com/overview-the-aws-big-data-platform/</link>
		<comments>http://amazonblogstore.com/overview-the-aws-big-data-platform/#comments</comments>
		<pubDate>Wed, 23 Sep 2015 08:11:08 +0000</pubDate>
		<dc:creator><![CDATA[admin]]></dc:creator>
				<category><![CDATA[Amazon Customer Service Videos]]></category>
		<category><![CDATA[Amazon Machine Learning]]></category>
		<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[big data]]></category>
		<category><![CDATA[DynamoDB]]></category>
		<category><![CDATA[elastic mapreduce]]></category>
		<category><![CDATA[lambda]]></category>

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		<description><![CDATA[This webinar will discuss big data challenges and provide an overview of the AWS Big Data Platform, and include a discussion of popular use cases and reference architectures. Learning Objectives: • How to leverage the AWS platform to manage massive volumes of data from a variety of sources while containing costs. • Reference architectures for ...]]></description>
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<p><span itemprop='description'>This webinar will discuss big data challenges and provide an overview of the AWS Big Data Platform, and include a discussion of popular use cases and reference architectures. </p>
<p>Learning Objectives:<br />
• How to leverage the AWS platform to manage massive volumes of data from a variety of sources while containing costs.<br />
• Reference architectures for popular use cases, including: connected devices (IoT), log streaming, real-time intelligence, and analytics.<br />
• Overview of the AWS big data portfolio of services, including Amazon S3, Kinesis, DynamoDB, AWS Lambda, Elastic MapReduce (EMR), Redshift and Amazon Machine Learning.</span></p>
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		<title>株式会社ベルシステム24ホールディングスにおける AWS クラウド活用</title>
		<link>http://amazonblogstore.com/%e6%a0%aa%e5%bc%8f%e4%bc%9a%e7%a4%be%e3%83%99%e3%83%ab%e3%82%b7%e3%82%b9%e3%83%86%e3%83%a024%e3%83%9b%e3%83%bc%e3%83%ab%e3%83%87%e3%82%a3%e3%83%b3%e3%82%b0%e3%82%b9%e3%81%ab%e3%81%8a%e3%81%91%e3%82%8b/</link>
		<comments>http://amazonblogstore.com/%e6%a0%aa%e5%bc%8f%e4%bc%9a%e7%a4%be%e3%83%99%e3%83%ab%e3%82%b7%e3%82%b9%e3%83%86%e3%83%a024%e3%83%9b%e3%83%bc%e3%83%ab%e3%83%87%e3%82%a3%e3%83%b3%e3%82%b0%e3%82%b9%e3%81%ab%e3%81%8a%e3%81%91%e3%82%8b/#comments</comments>
		<pubDate>Wed, 23 Sep 2015 08:05:43 +0000</pubDate>
		<dc:creator><![CDATA[admin]]></dc:creator>
				<category><![CDATA[Amazon Customer Service Videos]]></category>
		<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[AWS クラウド]]></category>
		<category><![CDATA[EC2]]></category>
		<category><![CDATA[redshift]]></category>
		<category><![CDATA[s3]]></category>
		<category><![CDATA[アマゾン ウェブ サービス]]></category>
		<category><![CDATA[アマゾン クラウド]]></category>
		<category><![CDATA[データ分析]]></category>
		<category><![CDATA[ビッグデータ]]></category>
		<category><![CDATA[ビッグデータ クラウド]]></category>

		<guid isPermaLink="false">http://amazonblogstore.com/%e6%a0%aa%e5%bc%8f%e4%bc%9a%e7%a4%be%e3%83%99%e3%83%ab%e3%82%b7%e3%82%b9%e3%83%86%e3%83%a024%e3%83%9b%e3%83%bc%e3%83%ab%e3%83%87%e3%82%a3%e3%83%b3%e3%82%b0%e3%82%b9%e3%81%ab%e3%81%8a%e3%81%91%e3%82%8b/</guid>
		<description><![CDATA[ベルシステム24ホールディングスはコンタクトセンターが提供するカスタマーエクスペリエンス向上のために大量のデータを瞬時に分析する必要性から、AWS クラウドを採用。Amazon Redshift をコンタクトセンターのデータと連携することにより、ビッグデータ分析環境を迅速かつ低コストで実現し、アプリケーション企画やサービス構築といった上流工程にリソースを集中することに成功しています。 AWS におけるビッグデータ活用については、http://aws.amazon.com/jp/big-data/ をご覧ください。]]></description>
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<p><span itemprop='description'>ベルシステム24ホールディングスはコンタクトセンターが提供するカスタマーエクスペリエンス向上のために大量のデータを瞬時に分析する必要性から、AWS クラウドを採用。Amazon Redshift をコンタクトセンターのデータと連携することにより、ビッグデータ分析環境を迅速かつ低コストで実現し、アプリケーション企画やサービス構築といった上流工程にリソースを集中することに成功しています。<br />
AWS におけるビッグデータ活用については、http://aws.amazon.com/jp/big-data/ をご覧ください。</span></p>
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