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	<title>Comments on: Can PowerPivot Pros Call Themselves Data Scientists? Part 2:  Finding a Balance Between &#8220;Yes&#8221; and &#8220;No&#8221;</title>
	<atom:link href="http://www.powerpivotpro.com/2012/10/can-powerpivot-pros-call-themselves-data-scientists-part-2-finding-a-balance-between-yes-and-no/feed/" rel="self" type="application/rss+xml" />
	<link>http://www.powerpivotpro.com/2012/10/can-powerpivot-pros-call-themselves-data-scientists-part-2-finding-a-balance-between-yes-and-no/?utm_source=rss&#038;utm_medium=rss&#038;utm_campaign=can-powerpivot-pros-call-themselves-data-scientists-part-2-finding-a-balance-between-yes-and-no</link>
	<description>Thoughts on PowerPivot, the future of Excel, and the occasional movie quote</description>
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		<title>By: Jeff "DrSynthetic" Wilson</title>
		<link>http://www.powerpivotpro.com/2012/10/can-powerpivot-pros-call-themselves-data-scientists-part-2-finding-a-balance-between-yes-and-no/#comment-7316</link>
		<dc:creator>Jeff "DrSynthetic" Wilson</dc:creator>
		<pubDate>Mon, 22 Oct 2012 18:50:39 +0000</pubDate>
		<guid isPermaLink="false">http://www.powerpivotpro.com/?p=5327#comment-7316</guid>
		<description><![CDATA[We are Data Scientists, Data Engineers
In addition I feel we are ALSO Data Plumbers. We have data that is leaking and keeping the location from being an airtight operation. It may be small it may be catastrophic but we have in effect either plug small leaks or provide re-piping service The decision-maker wants the water on when he turns on the faucet. We provide the filter that takes the water from the Cuyahoga ( I remember when it caught on fire) and remove the sludge and make it fit for human decision-making. 

Part of the idea came from Nixon&#039;s plumbers the unit he formed to plug leaks. Today we still have that problem. 

From the inception of data there has been &quot;holes&quot;. Those holes need to be plugged so we can go about the business of maximizing revenue and making intellingent decisions about expenses.

 PowerPivot does that!!!]]></description>
		<content:encoded><![CDATA[<p>We are Data Scientists, Data Engineers<br />
In addition I feel we are ALSO Data Plumbers. We have data that is leaking and keeping the location from being an airtight operation. It may be small it may be catastrophic but we have in effect either plug small leaks or provide re-piping service The decision-maker wants the water on when he turns on the faucet. We provide the filter that takes the water from the Cuyahoga ( I remember when it caught on fire) and remove the sludge and make it fit for human decision-making. </p>
<p>Part of the idea came from Nixon&#8217;s plumbers the unit he formed to plug leaks. Today we still have that problem. </p>
<p>From the inception of data there has been &#8220;holes&#8221;. Those holes need to be plugged so we can go about the business of maximizing revenue and making intellingent decisions about expenses.</p>
<p> PowerPivot does that!!!</p>
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		<title>By: Jeff Weir</title>
		<link>http://www.powerpivotpro.com/2012/10/can-powerpivot-pros-call-themselves-data-scientists-part-2-finding-a-balance-between-yes-and-no/#comment-7308</link>
		<dc:creator>Jeff Weir</dc:creator>
		<pubDate>Sun, 21 Oct 2012 10:55:03 +0000</pubDate>
		<guid isPermaLink="false">http://www.powerpivotpro.com/?p=5327#comment-7308</guid>
		<description><![CDATA[Most organisations have most data manglers banging away inefficiently in Excel producing anything BUT a decision. Let alone a good one. At ALL levels between your Type I and Type IV data workers. So there&#039;s something missing from your &quot;Amount of World&#039;s decisions powered by Excel&quot;....the thin nano-slice that says &quot;Amount of World&#039;s GOOD decisions powered by Excel&quot;. (Or maybe it&#039;s not missing. It&#039;s there, but is narrower than 1 pixel.)

Put another way, what percentage of spreadsheets do you think are ultimately are fit for some purpose? What percent of data workers across your average organisation contribute a net benefit after their salary and overheads are covered. Do organisations succeed because of all those spreadsheets, or in spite of them.

Sometimes the sum use of my well-honed powerpivot/pivot/sql/vba skills – and my econometrics degree – is to take someone&#039;s large, slow, incomprehensible model and help it reach its inevitably wrong conclusion a heck of a lot faster, with a heck of a lot less manual manipulation of dodgy input along the way. 

Often the only gratification I can take from my role is that if someone wants something pretty much irrelevant done, then with my skillset and toolset I can help them achieve it with the minimum efficiency drag on the organisation.

For the majority of organisations, science doesn’t drive most spreadsheets. Dogma does.

While we could do with more people with better tools to help solve the world’s data problems, we also need requisite growth in more/smarter managers capable of asking themselves &quot;Before I make this data monkey crunch all this data, how will I know if the result they come up with is credible? What makes we think we have the data to answer this question? Is this our most pressing question? Will knowing the answer change my behaviour? Do I already know the answer? 

Or am I just looking for a safe secure blanket that makes me feel comfortable?]]></description>
		<content:encoded><![CDATA[<p>Most organisations have most data manglers banging away inefficiently in Excel producing anything BUT a decision. Let alone a good one. At ALL levels between your Type I and Type IV data workers. So there&#8217;s something missing from your &#8220;Amount of World&#8217;s decisions powered by Excel&#8221;&#8230;.the thin nano-slice that says &#8220;Amount of World&#8217;s GOOD decisions powered by Excel&#8221;. (Or maybe it&#8217;s not missing. It&#8217;s there, but is narrower than 1 pixel.)</p>
<p>Put another way, what percentage of spreadsheets do you think are ultimately are fit for some purpose? What percent of data workers across your average organisation contribute a net benefit after their salary and overheads are covered. Do organisations succeed because of all those spreadsheets, or in spite of them.</p>
<p>Sometimes the sum use of my well-honed powerpivot/pivot/sql/vba skills – and my econometrics degree – is to take someone&#8217;s large, slow, incomprehensible model and help it reach its inevitably wrong conclusion a heck of a lot faster, with a heck of a lot less manual manipulation of dodgy input along the way. </p>
<p>Often the only gratification I can take from my role is that if someone wants something pretty much irrelevant done, then with my skillset and toolset I can help them achieve it with the minimum efficiency drag on the organisation.</p>
<p>For the majority of organisations, science doesn’t drive most spreadsheets. Dogma does.</p>
<p>While we could do with more people with better tools to help solve the world’s data problems, we also need requisite growth in more/smarter managers capable of asking themselves &#8220;Before I make this data monkey crunch all this data, how will I know if the result they come up with is credible? What makes we think we have the data to answer this question? Is this our most pressing question? Will knowing the answer change my behaviour? Do I already know the answer? </p>
<p>Or am I just looking for a safe secure blanket that makes me feel comfortable?</p>
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		<title>By: greg</title>
		<link>http://www.powerpivotpro.com/2012/10/can-powerpivot-pros-call-themselves-data-scientists-part-2-finding-a-balance-between-yes-and-no/#comment-7278</link>
		<dc:creator>greg</dc:creator>
		<pubDate>Fri, 19 Oct 2012 15:21:17 +0000</pubDate>
		<guid isPermaLink="false">http://www.powerpivotpro.com/?p=5327#comment-7278</guid>
		<description><![CDATA[Great topic 

With only a month of PP under my belt i am already finding out how I can use my knowledge of business combined with superior data crunching skills to come up with new ways to analyses large data sets.  

i have not seen anything that power pivot does that I could not do in some back ended way in excel (i.e. with pivots, vlookups, and then in some cases doing repivots of a hard code of the pivot results).  But it is faster (sometimes) to put together, definitely more flexible, cleaner, better controlled, and processes way quicker than plain excel.

I also like the concept of data analysis.  The idea of the business to IT conduit has been something that has been talked about for a while and this is a good example of it coming to fruition.]]></description>
		<content:encoded><![CDATA[<p>Great topic </p>
<p>With only a month of PP under my belt i am already finding out how I can use my knowledge of business combined with superior data crunching skills to come up with new ways to analyses large data sets.  </p>
<p>i have not seen anything that power pivot does that I could not do in some back ended way in excel (i.e. with pivots, vlookups, and then in some cases doing repivots of a hard code of the pivot results).  But it is faster (sometimes) to put together, definitely more flexible, cleaner, better controlled, and processes way quicker than plain excel.</p>
<p>I also like the concept of data analysis.  The idea of the business to IT conduit has been something that has been talked about for a while and this is a good example of it coming to fruition.</p>
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