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	<title>data without limits &#187; Philippe Souidi</title>
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	<link>http://datawithoutlimits.com</link>
	<description>your data partner</description>
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		<title>Data Without Limits &#8211; Blog</title>
		<link>http://datawithoutlimits.com/blog-post/</link>
		<comments>http://datawithoutlimits.com/blog-post/#comments</comments>
		<pubDate>Wed, 23 Apr 2014 13:31:03 +0000</pubDate>
		<dc:creator><![CDATA[philippe]]></dc:creator>
				<category><![CDATA[Big Data Companies]]></category>
		<category><![CDATA[Blog]]></category>
		<category><![CDATA[Big Data]]></category>
		<category><![CDATA[datawl]]></category>
		<category><![CDATA[Philippe Souidi]]></category>

		<guid isPermaLink="false">http://datawithoutlimits.com/?p=3576</guid>
		<description><![CDATA[Data Without Limits We are a Creative Agency specialised on Data Analytics, Predictive Analytics and Data Visualization. Big Data Analytics provides opportunities to discover deeper, more complete business insights through the analysis and visualization of significant volumes of rapidly changing structured and unstructured data. Structured or unstrucred data, we love all kind of data. Our [&#8230;]]]></description>
				<content:encoded><![CDATA[<h1 style="text-align: center;">Data Without Limits</h1>
<div id="attachment_3586" style="width: 190px" class="wp-caption aligncenter"><a href="http://datawithoutlimits.com/wp-content/uploads/2014/04/DataWL-LinkedIn-Logo.png"><img class="size-full wp-image-3586" alt="DataWL is the reliable partner for fortune 500 companies, Government Agencies or Institutions. If you think Data, think Data Without Limits your creative data agency." src="http://datawithoutlimits.com/wp-content/uploads/2014/04/DataWL-LinkedIn-Logo.png" width="180" height="110" /></a><p class="wp-caption-text">DataWL is the reliable partner for fortune 500 companies, Government Agencies or Institutions.<br />If you think Data, think Data Without Limits your creative data agency.</p></div>
<p style="text-align: center;">We are a <strong>Creative Agency</strong> specialised on <strong>Data Analytics</strong>, <strong>Predictive Analytics</strong> and <strong>Data Visualization</strong>.</p>
<p class="size-full wp-image-3580" style="text-align: center;">Big Data Analytics provides opportunities to discover deeper, more complete business insights through the analysis and visualization of significant volumes of rapidly changing structured and unstructured data.</p>
<p style="text-align: center;">Structured or unstrucred data, we love all kind of data. Our domain of experince spans from in car telemetric data, over social media data to realtime monitoring of video data. Each completed project makes us even more hungry, hungry for more data to push the limits of the possible even further. As a result we deliver insights to unleash the hidden power and value in your data sets.</p>
<p style="text-align: center;">Combining the competencies of data analytics, strategic consultancy and marketing. DataWL is able to offer a holistic approach to solve companies&#8217; data challenges.</p>
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		<item>
		<title>Magic Quadrant for Business Intelligence and Analytics Platforms</title>
		<link>http://datawithoutlimits.com/magic-quadrant-for-business-intelligence-and-analytics-platforms/</link>
		<comments>http://datawithoutlimits.com/magic-quadrant-for-business-intelligence-and-analytics-platforms/#comments</comments>
		<pubDate>Fri, 22 Feb 2013 07:15:20 +0000</pubDate>
		<dc:creator><![CDATA[philippe]]></dc:creator>
				<category><![CDATA[Big Data Companies]]></category>
		<category><![CDATA[Big Data Experts]]></category>
		<category><![CDATA[1010data]]></category>
		<category><![CDATA[Actuate; Alteryx]]></category>
		<category><![CDATA[Advizor Solutions]]></category>
		<category><![CDATA[Altosoft]]></category>
		<category><![CDATA[Analytics Platforms]]></category>
		<category><![CDATA[Birst]]></category>
		<category><![CDATA[Bitam]]></category>
		<category><![CDATA[Board International]]></category>
		<category><![CDATA[Business Intelligence]]></category>
		<category><![CDATA[Daniel Yuen]]></category>
		<category><![CDATA[Dimensional Insight]]></category>
		<category><![CDATA[eQ Technologic]]></category>
		<category><![CDATA[GoodData]]></category>
		<category><![CDATA[IBM]]></category>
		<category><![CDATA[InetSoft]]></category>
		<category><![CDATA[Information Builders]]></category>
		<category><![CDATA[JackBe]]></category>
		<category><![CDATA[Jaspersoft]]></category>
		<category><![CDATA[Jedox]]></category>
		<category><![CDATA[Joao Tapadinhas]]></category>
		<category><![CDATA[Kurt Schlegel]]></category>
		<category><![CDATA[LogiXML]]></category>
		<category><![CDATA[Magic Quadrant]]></category>
		<category><![CDATA[Microsoft]]></category>
		<category><![CDATA[MicroStrategy]]></category>
		<category><![CDATA[myDials/Adaptive Planning]]></category>
		<category><![CDATA[Oracle]]></category>
		<category><![CDATA[Panorama Software]]></category>
		<category><![CDATA[Pentaho]]></category>
		<category><![CDATA[Philippe Souidi]]></category>
		<category><![CDATA[Phocas]]></category>
		<category><![CDATA[Prognoz]]></category>
		<category><![CDATA[QlikTech]]></category>
		<category><![CDATA[Rita L. Sallam]]></category>
		<category><![CDATA[Salient Management Company]]></category>
		<category><![CDATA[SAP]]></category>
		<category><![CDATA[SAS]]></category>
		<category><![CDATA[SpagoBI]]></category>
		<category><![CDATA[Strategy Companion]]></category>
		<category><![CDATA[Tableau Software]]></category>
		<category><![CDATA[Targit]]></category>
		<category><![CDATA[Tibco Spotfire]]></category>
		<category><![CDATA[Yellowfin]]></category>

		<guid isPermaLink="false">http://datawithoutlimits.com/?p=3419</guid>
		<description><![CDATA[Gartner released in february its Magic Quadrant for Business Intelligence and Analytics Platforms ID:G00239854 Analysts were: Kurt Schlegel, Rita L. Sallam, Daniel Yuen, Joao Tapadinhas So, what&#8217;s new? The example of Birst and GoodData shows BI&#8217;s future is in the cloud. So far all cloud solution have to live with a hybrid of deployed in [&#8230;]]]></description>
				<content:encoded><![CDATA[<p>Gartner released in february its Magic Quadrant for Business Intelligence and Analytics Platforms ID:G00239854</p>
<p>Analysts were: Kurt Schlegel, Rita L. Sallam, Daniel Yuen, Joao Tapadinhas</p>
<p><a href="http://www.23ideas.de/wp-content/uploads/2013/02/Bildschirmfoto-2013-02-22-um-10.57.03.png"><img class="alignnone size-medium wp-image-393" alt="Bildschirmfoto 2013-02-22 um 10.57.03" src="http://www.23ideas.de/wp-content/uploads/2013/02/Bildschirmfoto-2013-02-22-um-10.57.03-300x296.png" width="300" height="296" /></a></p>
<p><strong>So, what&#8217;s new?</strong></p>
<p>The example of Birst and GoodData shows BI&#8217;s future is in the cloud. So far all cloud solution have to live with a hybrid of deployed in the cloud or in an on-premises appliance. Birst success in winning deals is based on its functional breadth, depth and strength, ease of use and low cost of ownership value proposition. This makes Birst  the &#8220;new darling&#8221; of the Magic Quadrant.</p>
<p>&#8220;Increasingly, Gartner sees more organizations building diagnostic analytics that leverage critical capabilities, such as interactive visualization, to enable users to drill more easily into the data to discover new insights. For example, visual patterns uncovered in the data might expose an inconsistent supply chain process that is the root cause of an organization&#8217;s ability to consistently reach its goal for on-time delivery.&#8221;</p>
<p>&#8220;If there were a single market theme in 2012, it would be that data discovery became a mainstream architecture. For years, data discovery vendors — such as QlikTech, Salient Management Company, Tableau Software and Tibco Spotfire — received more positive feedback than vendors offering OLAP cube and semantic-layer-based architectures.&#8221;</p>
<p><strong>Featured companies:</strong><br />
Actuate; Alteryx, Birst, Bitam, Board International, GoodData, IBM, Information Builders, Jaspersoft, LogiXML, Microsoft, MicroStrategy, Oracle, Panorama Software, Pentaho, Prognoz, QlikTech, Salient Management Company, SAP, SAS, Tableau Software, Targit, Tibco Spotfire</p>
<p><strong>Other Vendors to Consider:</strong><br />
1010data, Advizor Solutions, Altosoft, Dimensional Insight, eQ Technologic, InetSoft, JackBe, Jedox, myDials/Adaptive Planning, Phocas, SpagoBI, Strategy Companion, Yellowfin</p>
<p>&nbsp;</p>
<p>Read the Gartner&#8217;s Summary hier: <a href="http://www.gartner.com/technology/reprints.do?id=1-1DZLPF2&amp;ct=130207&amp;st=sb">Magic Quadrant for Business Intelligence and Analytics Platforms</a></p>
<p>&nbsp;</p>
<p>&nbsp;</p>
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		<title>Ben Horowitz Co-Founder of  Andreessen Horowitz about his Investment Strategies</title>
		<link>http://datawithoutlimits.com/ben-horowitz-co-founder-of-andreessen-horowitz-about-his-investment-strategies/</link>
		<comments>http://datawithoutlimits.com/ben-horowitz-co-founder-of-andreessen-horowitz-about-his-investment-strategies/#comments</comments>
		<pubDate>Wed, 20 Feb 2013 15:20:04 +0000</pubDate>
		<dc:creator><![CDATA[philippe]]></dc:creator>
				<category><![CDATA[Digital Innovation]]></category>
		<category><![CDATA[Entrepreneur]]></category>
		<category><![CDATA[Investments]]></category>
		<category><![CDATA[23business]]></category>
		<category><![CDATA[Ben Horowitz]]></category>
		<category><![CDATA[Entrepreneurship]]></category>
		<category><![CDATA[Innovation]]></category>
		<category><![CDATA[Investment]]></category>
		<category><![CDATA[Investor]]></category>
		<category><![CDATA[Philippe Souidi]]></category>
		<category><![CDATA[Strategie]]></category>
		<category><![CDATA[UC Berkeley]]></category>

		<guid isPermaLink="false">http://datawithoutlimits.com/?p=3421</guid>
		<description><![CDATA[Ben Horowitz revails some of his investment strategies during his lecture at UC Berkeleys College of Engineering&#8217;s Center for Entrepreneurship. What Ben Horowitz is looking at investments: The size of the opportunity &#8211; you need to get 30% to 40% of the market to meaningfull and to make money in technology. The quality of the [&#8230;]]]></description>
				<content:encoded><![CDATA[<p>Ben Horowitz revails some of his investment strategies during his lecture at UC Berkeleys College of Engineering&#8217;s Center for Entrepreneurship.</p>
<p>What Ben Horowitz is looking at investments:</p>
<ol>
<li>The size of the opportunity &#8211; you need to get 30% to 40% of the market to meaningfull and to make money in technology.</li>
<li>The quality of the team &#8211; is the team good enough to build a great product that is ten-times better and take the market.</li>
<li>A bad market always beat a good team.</li>
</ol>
<p>What Ben Horowitz likes to have in his investments:</p>
<ul>
<li>Megalomaniacs</li>
<li>Outliers</li>
<li>Shifts in technology or markets</li>
<li>Market sectors that are dead &#8211; big market, a winner, bad product; this is a opportunity</li>
<li>Entrepreneurs that tilt towards big markets and not a niche</li>
<li>Hard core technical team</li>
<li>Products then teams rather than vice versa</li>
</ul>
<p>What Ben Horowitz believes to be the biggest challenges for entrepreneurs:</p>
<ul>
<li>Being both entrepreneur and inventor</li>
<li>Finding product/market fit</li>
<li>Managing their own psychology</li>
</ul>
<p><iframe src="http://www.youtube.com/embed/G-LBSqm3xh4" height="315" width="420" allowfullscreen="" frameborder="0"></iframe></p>
<p>Learn how business works directly from groundbreaking entrepreneurs and business leaders. This episode features Ben Horowitz, co-founder of Andreessen Horowitz, a $300 million venture fund aimed at investing in new entrepreneurs, products, and companies in the technology industry. Presented by UC Berkeleys College of Engineering&#8217;s Center for Entrepreneurship. Series: Distinguished Innovator Lectures [4/2010] [Business] [Show ID: 17365]</p>
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		<title>SmartCamp Winner Spotlight: Streetlight Data</title>
		<link>http://datawithoutlimits.com/smartcamp-winner-spotlight-streetlight-data/</link>
		<comments>http://datawithoutlimits.com/smartcamp-winner-spotlight-streetlight-data/#comments</comments>
		<pubDate>Tue, 05 Feb 2013 15:22:15 +0000</pubDate>
		<dc:creator><![CDATA[philippe]]></dc:creator>
				<category><![CDATA[Big Data Companies]]></category>
		<category><![CDATA[Big Data Experts]]></category>
		<category><![CDATA[BI]]></category>
		<category><![CDATA[Big Data]]></category>
		<category><![CDATA[Conference]]></category>
		<category><![CDATA[Expert]]></category>
		<category><![CDATA[IBM]]></category>
		<category><![CDATA[Philippe Souidi]]></category>
		<category><![CDATA[Smart Camp]]></category>
		<category><![CDATA[Smart Data]]></category>
		<category><![CDATA[Speaker]]></category>

		<guid isPermaLink="false">http://datawithoutlimits.com/?p=3423</guid>
		<description><![CDATA[StreetLight Data describes how people use their city. What web analytics does for e-commerce, we do for in-store commerce. We provide metrics like: for this corner on a typical Tuesday afternoon, what percent of people coming by are over 40? Make less than $60k/year? How many are going shopping? For the retail ecosystem this means [&#8230;]]]></description>
				<content:encoded><![CDATA[<p>StreetLight Data describes how people use their city. What web analytics does for e-commerce, we do for in-store commerce. We provide metrics like: for this corner on a typical Tuesday afternoon, what percent of people coming by are over 40? Make less than $60k/year? How many are going shopping? For the retail ecosystem this means answering questions that have never before been answered: Who is coming by my store and NOT coming in? We also open up insights that can radically improve transportation and urban planning. Our solutions depend on our Route Science(TM) engine, which puts messy transportation data in context, leveraging archival data exhaust from the location-based services industry.<br />
<a href="http://tecpunk.files.wordpress.com/2012/11/streetlightsolution.jpg"><img title="streetlightsolution" alt="" src="http://tecpunk.files.wordpress.com/2012/11/streetlightsolution.jpg?w=300" height="225" width="300" /></a><br />
&nbsp;</p>
<p>Read more on: &lt;a title=&#8221;IBM Smart Camp Streetlight&#8221; href=&#8221;http://ibmsmartcamp.com/2012/09/20/smartcamp-winner-spotlight-streetlight-data/&#8221;&gt;IBM Smart Camp&lt;/a&gt;</p>
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		<title>BellaDati &#8211; makes big data directly accessible to business leaders</title>
		<link>http://datawithoutlimits.com/belladati-makes-big-data-directly-accessible-to-business-leaders/</link>
		<comments>http://datawithoutlimits.com/belladati-makes-big-data-directly-accessible-to-business-leaders/#comments</comments>
		<pubDate>Thu, 17 Jan 2013 15:23:58 +0000</pubDate>
		<dc:creator><![CDATA[philippe]]></dc:creator>
				<category><![CDATA[Big Data Companies]]></category>
		<category><![CDATA[Big Data Experts]]></category>
		<category><![CDATA[Entrepreneur]]></category>
		<category><![CDATA[Maps]]></category>
		<category><![CDATA[BellaDati]]></category>
		<category><![CDATA[Big Data]]></category>
		<category><![CDATA[Data Visualization]]></category>
		<category><![CDATA[Martin Trgina]]></category>
		<category><![CDATA[Philippe Souidi]]></category>

		<guid isPermaLink="false">http://datawithoutlimits.com/?p=3425</guid>
		<description><![CDATA[Currently, big data is a melting pot of distributed data architectures and tools like Hadoop, NoSQL, Hive and R. But, there are new companies emerging offering a toolset to make big data accessible to business leaders. BellaDati is a fit-to-purpose products that abstract away as much of the technical complexity as possible, so that the [&#8230;]]]></description>
				<content:encoded><![CDATA[<p>Currently, big data is a melting pot of distributed data architectures and tools like Hadoop, NoSQL, Hive and R. But, there are new companies emerging offering a toolset to make big data accessible to business leaders.</p>
<p><img class="alignleft" alt="" src="http://www.belladati.com/en/post.rendercontent:viewfile/523?t:ac=202" width="590" height="277" /></p>
<p><a href="http://www.belladati.com/en/">BellaDati</a> is a fit-to-purpose products that abstract away as much of the technical complexity as possible, so that the power of big data can be put into the hands of business users.<br />
[youtube http://www.youtube.com/watch?v=Kwm0SP_hJQQ]</p>
<p>BellaDati&#8217;s idea is to provide the world with a tool to reinvent the way business users interact with their data.</p>
<p>BellaDati is offering solutions for several industies so far:</p>
<ul>
<li><a href="http://www.belladati.com/en/banking-analytics">Banking Analytics</a></li>
<li><a href="http://www.belladati.com/en/retail-e-commerce-analytics"> Retail and eCommerce Analytics</a></li>
<li><a href="http://www.belladati.com/en/social-media-analytics"> Social Media Analytics</a></li>
<li><a href="http://www.belladati.com/en/marketing-analytics"> Marketing Analytics</a></li>
<li><a href="http://www.belladati.com/en/smartcity"> Smart City Analytics</a></li>
<li><a href="http://www.belladati.com/en/salesforce-visual-analytics"> Salesforce Visual Analytics </a></li>
<li><a href="http://www.belladati.com/en/business-intelligence-platform">BellaDati Business Intelligence Platform</a></li>
</ul>
<p>This trend of simplifying the access to data knowledge will change the BI landscape as we know it. <a href="cz.linkedin.com/in/martintrgina">Martin Trgina</a> the CEO and founder of BellaDati has this vision and manifested it by the mission statement of BellaDati:</p>
<p>&#8220;We believe everybody should have an answer to data questions without waiting and in a nice design. We believe that everyone can love the BI. So — we made BellaDati.&#8221;</p>
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		<title>Big Data Analytics at Telefonica Czech</title>
		<link>http://datawithoutlimits.com/big-data-analytics-at-telefonica-czech/</link>
		<comments>http://datawithoutlimits.com/big-data-analytics-at-telefonica-czech/#comments</comments>
		<pubDate>Thu, 03 Jan 2013 10:25:20 +0000</pubDate>
		<dc:creator><![CDATA[philippe]]></dc:creator>
				<category><![CDATA[Big Data Companies]]></category>
		<category><![CDATA[Big Data Experts]]></category>
		<category><![CDATA[Big Data]]></category>
		<category><![CDATA[Czech]]></category>
		<category><![CDATA[Philippe Souidi]]></category>
		<category><![CDATA[Telefonica]]></category>

		<guid isPermaLink="false">http://datawithoutlimits.com/?p=3427</guid>
		<description><![CDATA[Telefonica Czech is using so far 20% of their available data. Nevertheless close rates increase up to 200% through Microtargeting Watch the video on http://www.teradata.com/]]></description>
				<content:encoded><![CDATA[<p>Telefonica Czech is using so far 20% of their available data. Nevertheless close rates increase up to 200% through Microtargeting</p>
<p><a href="http://www.teradata.com/videos/Telefonica-Czech-Microtargeting-and-Monetizing-equals-Innovation/" target="_blank">Watch the video on http://www.teradata.com/</a></p>
]]></content:encoded>
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		<title>Algorithms Are Taking Over The World : Christopher Steiner at TEDxOrangeCoast</title>
		<link>http://datawithoutlimits.com/algorithms-are-taking-over-the-world-christopher-steiner-at-tedxorangecoast/</link>
		<comments>http://datawithoutlimits.com/algorithms-are-taking-over-the-world-christopher-steiner-at-tedxorangecoast/#comments</comments>
		<pubDate>Mon, 31 Dec 2012 15:26:42 +0000</pubDate>
		<dc:creator><![CDATA[philippe]]></dc:creator>
				<category><![CDATA[Big Data Experts]]></category>
		<category><![CDATA[Christopher Steiner]]></category>
		<category><![CDATA[Philippe Souidi]]></category>
		<category><![CDATA[Ted]]></category>

		<guid isPermaLink="false">http://datawithoutlimits.com/?p=3429</guid>
		<description><![CDATA[Christopher Steiner is the author of Automate This (2012) and $20 Per Gallon, a New York Times Bestseller (2009). He is a cofounder at Aisle50, a Y Combinator company that sells grocery deals through the Web. Before starting Aisle50 in 2011, Steiner was a senior writer covering technology at Forbes magazine for seven years. His [&#8230;]]]></description>
				<content:encoded><![CDATA[<p><iframe src="//www.youtube.com/embed/H_aLU-NOdHM" height="315" width="560" allowfullscreen="" frameborder="0"></iframe></p>
<p>Christopher Steiner is the author of Automate This (2012) and $20 Per Gallon, a New York Times Bestseller (2009). He is a cofounder at Aisle50, a Y Combinator company that sells grocery deals through the Web. Before starting Aisle50 in 2011, Steiner was a senior writer covering technology at Forbes magazine for seven years.<br />
His writing has also appeared in The Wall Street Journal, the Chicago Tribune, Fast Company, MIT Technology Review and Skiing Magazine. He holds an engineering degree from the University of Illinois at Urbana-Champaign and a masters in journalism from Northwestern University. Steiner lives in Evanston, Ill., with his family.</p>
<p>About TEDx.<br />
TEDx was created in the spirit of TED&#8217;s mission, &#8220;ideas worth spreading.&#8221; The program is designed to give communities, organizations and individuals the opportunity to stimulate dialogue through TED-like experiences at the local level. At TEDx events, a screening of TEDTalks videos &#8212; or a combination of live presenters and TEDTalks videos &#8212; sparks deep conversation and connections. TEDx events are fully planned and coordinated independently, on a community-by-community basis.</p>
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		<title>Werner Vogels ( CTO, Amazon) is pointing out three key trends in cloud computing.</title>
		<link>http://datawithoutlimits.com/werner-vogels-cto-amazon-is-pointing-out-three-key-trends-in-cloud-computing/</link>
		<comments>http://datawithoutlimits.com/werner-vogels-cto-amazon-is-pointing-out-three-key-trends-in-cloud-computing/#comments</comments>
		<pubDate>Mon, 10 Dec 2012 08:30:57 +0000</pubDate>
		<dc:creator><![CDATA[philippe]]></dc:creator>
				<category><![CDATA[Big Data Companies]]></category>
		<category><![CDATA[Big Data Experts]]></category>
		<category><![CDATA[Amazon]]></category>
		<category><![CDATA[Big Data]]></category>
		<category><![CDATA[Big Science]]></category>
		<category><![CDATA[Cloud Computing]]></category>
		<category><![CDATA[Dropbox]]></category>
		<category><![CDATA[LeWeb]]></category>
		<category><![CDATA[Philippe Souidi]]></category>
		<category><![CDATA[Werner Vogles]]></category>

		<guid isPermaLink="false">http://datawithoutlimits.com/?p=3433</guid>
		<description><![CDATA[During the panel discussion on cloud computing at LeWeb 12 in Paris, Werner Vogels highlights three key trends: 1. Data Analytics Companies are analyzing data sets for a deeper understanding of their customers. What are their customers doing, how are they operating and how are they using the companies products. 2. Big Science Accelerated science [&#8230;]]]></description>
				<content:encoded><![CDATA[<p>During the panel discussion on cloud computing at LeWeb 12 in Paris, Werner Vogels highlights three key trends:</p>
<p><iframe src="http://www.youtube.com/embed/usk5UfHu624" height="315" width="560" allowfullscreen="" frameborder="0"></iframe></p>
<p>1. Data Analytics</p>
<ul>
<li>Companies are analyzing data sets for a deeper understanding of their customers.</li>
<li>What are their customers doing, how are they operating and how are they using the companies products.</li>
</ul>
<p>2. Big Science</p>
<ul>
<li>Accelerated science through computing power, making today calculation and search in three howers, which has taken before six month.</li>
</ul>
<p>3. Mobile</p>
<ul>
<li>All your data is in the cloud the device is just a window into it.</li>
</ul>
<p>The panels name: Our heads are in the Cloud!<br />
Moderator: Robin Wauters, European Editor, The Next Web<br />
Panelists:<br />
Aditya Agarwal, Vice President of Engineering, Dropbox<br />
Brad Garlinghouse, CEO, YouSendIt<br />
Werner Vogels, CTO, Amazon</p>
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		<title>Many Simple Models over One Complicated Model</title>
		<link>http://datawithoutlimits.com/many-simple-models-over-one-complicated-model/</link>
		<comments>http://datawithoutlimits.com/many-simple-models-over-one-complicated-model/#comments</comments>
		<pubDate>Sun, 09 Dec 2012 15:32:35 +0000</pubDate>
		<dc:creator><![CDATA[philippe]]></dc:creator>
				<category><![CDATA[Digital Innovation]]></category>
		<category><![CDATA[Entrepreneur]]></category>
		<category><![CDATA[Jurgen Appelo]]></category>
		<category><![CDATA[Models]]></category>
		<category><![CDATA[Philippe Souidi]]></category>
		<category><![CDATA[Theory]]></category>

		<guid isPermaLink="false">http://datawithoutlimits.com/?p=3435</guid>
		<description><![CDATA[Jurgen Appelo has an interesting theory; when people have invested time and energy in a model (tool, framework, method), people have a tendency to make their models more and more complicated. “Let’s add another dimension.” “Let’s deepen the domains.” “Let’s add some columns or swim lanes.” “Let’s draw an extra diagram.” The main approach to [&#8230;]]]></description>
				<content:encoded><![CDATA[<p>Jurgen Appelo has an interesting theory; when people have invested time and energy in a model (tool, framework, method), <strong>people have a tendency to make their models more and more complicated</strong>. “Let’s add another dimension.” “Let’s deepen the domains.” “Let’s add some columns or swim lanes.” “Let’s draw an extra diagram.”</p>
<p>The main approach to solve Big Data challenges is to take out the complexity of the data sets.</p>
<p><em>Complexity itself is anti-methodology. It is against &#8220;one size fits all.&#8221;</em><br />
- Tom Petzinger, <a href="http://www.amazon.com/gp/product/B000RMPSXK/ref=as_li_ss_tl?ie=UTF8&amp;camp=1789&amp;creative=390957&amp;creativeASIN=B000RMPSXK&amp;linkCode=as2&amp;tag=noopnl-20"><em>Interaction of Complexity and Management</em></a></p>
<p>This means it makes more sense to <strong>use multiple simple models instead of one complicated model</strong>. Having a toolkit of methods and frameworks, which each fail in their own way, is a smarter approach than relying on one method or framework to deal with all situations.</p>
<p>Read more on:</p>
<p><a href="http://www.noop.nl/2012/10/many-simple-models-over-one-complicated-model.html">Jurgen Appelo&#8217;s blog noop.nl</a></p>
<p><a href="http://www.noop.nl/2012/10/many-simple-models-over-one-complicated-model.html"> </a></p>
<p>&nbsp;</p>
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		<title>The Pragmatic Definition of Big Data by Mike Gualtieri</title>
		<link>http://datawithoutlimits.com/the-pragmatic-definition-of-big-data-by-mike-gualtieri/</link>
		<comments>http://datawithoutlimits.com/the-pragmatic-definition-of-big-data-by-mike-gualtieri/#comments</comments>
		<pubDate>Thu, 06 Dec 2012 13:33:56 +0000</pubDate>
		<dc:creator><![CDATA[philippe]]></dc:creator>
				<category><![CDATA[Big Data Experts]]></category>
		<category><![CDATA[Big Data]]></category>
		<category><![CDATA[Forrester]]></category>
		<category><![CDATA[Philippe Souidi]]></category>

		<guid isPermaLink="false">http://datawithoutlimits.com/?p=3437</guid>
		<description><![CDATA[Mike Gualtieri says; forget about the three Vs Big data is not defined by how you can measure data in terms of volume, velocity, and variety. The three Vs are just measures of data — how much, how fast, and how diverse? A quaint definition of big data to be sure, but not an actionable, [&#8230;]]]></description>
				<content:encoded><![CDATA[<p><strong><a href="http://blogs.forrester.com/mike_gualtieri">Mike Gualtieri</a> says; forget about the three Vs</strong></p>
<p><b>Big data is </b><em><b>not</b></em><b> defined by how you can measure data in terms of volume, velocity, and variety. The <a href="http://blogs.forrester.com/mike_gualtieri/12-05-17-whats_your_big_data_score">three Vs are just measures of data</a> </b><b>—</b><b> how much, how fast, and how diverse? A quaint definition of big data to be sure, but not an actionable, complete definition for IT and business professionals. A more pragmatic definition of big data must acknowledge that:</b></p>
<ul>
<li>Exponential data growth makes it continuously difficult to manage — store, process, and access.</li>
<li>Data contains nonobvious information that firms can discover to improve business outcomes.</li>
<li>Measures of <a href="http://blogs.forrester.com/mike_gualtieri/12-12-05-is_750mb_big_data">data are relative</a>; one firm’s big data is another firm’s peanut.</li>
</ul>
<p>A pragmatic definition of big data must be actionable for <em>both</em> IT and business professionals.</p>
<p><strong>The Definition Of Big Data</strong></p>
<p><em>Big Data is the frontier of a firm’s ability to store, process, and access (SPA) all the data it needs to operate effectively, make decisions, reduce risks, and serve customers.</em></p>
<p>To remember the pragmatic definition of big data, think SPA — the three questions of big data:</p>
<ul>
<li><strong>Store.</strong><b> </b>Can you capture and store the data?</li>
<li><strong>Process.</strong><b> </b>Can you cleanse, enrich, and analyze the data?</li>
<li><strong>Access.</strong><b> </b>Can you retrieve, search, integrate, and visualize the data?</li>
</ul>
<p>Hear me explain this definition on a special episode of Forrester TechnoPolitics: <a href="http://blogs.forrester.com/mike_gualtieri/12-12-16-technopolitics_podcast_the_pragmatic_definition_of_big_data_explained">The Pragmatic Definition of Big Data Explained</a></p>
<p><a href="http://blogs.forrester.com/mike_gualtieri/12-12-05-the_pragmatic_definition_of_big_data">Read more on:</a> <a href="http://blogs.forrester.com/">Forrester Blogs</a></p>
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