<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"
	xmlns:content="http://purl.org/rss/1.0/modules/content/"
	xmlns:dc="http://purl.org/dc/elements/1.1/"
	xmlns:atom="http://www.w3.org/2005/Atom"
	xmlns:sy="http://purl.org/rss/1.0/modules/syndication/"
		>
<channel>
	<title>Comments on: Business Data Analysis : Comparing Data Populations with SQL</title>
	<atom:link href="http://technology-advisors.net/06/business-data-analysis-data-sql/feed/" rel="self" type="application/rss+xml" />
	<link>http://technology-advisors.net/06/business-data-analysis-data-sql/</link>
	<description>Guides for Risk Mgmt, Managed Services, Business Continuity Security, Information Assurance, Enterprise Content Management</description>
	<lastBuildDate>Tue, 15 Dec 2009 22:18:24 +0000</lastBuildDate>
	<sy:updatePeriod>hourly</sy:updatePeriod>
	<sy:updateFrequency>1</sy:updateFrequency>
	<generator>http://wordpress.org/?v=3.3.2</generator>
	<item>
		<title>By: Technology</title>
		<link>http://technology-advisors.net/06/business-data-analysis-data-sql/comment-page-1/#comment-134</link>
		<dc:creator>Technology</dc:creator>
		<pubDate>Sun, 14 Jun 2009 05:23:40 +0000</pubDate>
		<guid isPermaLink="false">http://technology-advisors.net/?p=109#comment-134</guid>
		<description>Perfect question! IMO from a technical or IT perspective your query is perfect and the most efficient way to write it and would be the best way if we were dealing with perfect data set. However, from a business analysis perspective, more often than not you will be more efficient with the sub queries especially when you are first &lt;strong&gt;researching &lt;/strong&gt;an unknown data population. 
Here is an example, in the &#039;Left Join Query&#039; above where there are 30 loans in the in the original population and not in the returned population. Leaving the &#039;select * from original_loan_pop&#039; allows you to see the details of the loans or data set and easily add or remove fields from the query. This allows flexibility in researching the issue or variance.</description>
		<content:encoded><![CDATA[<p>Perfect question! IMO from a technical or IT perspective your query is perfect and the most efficient way to write it and would be the best way if we were dealing with perfect data set. However, from a business analysis perspective, more often than not you will be more efficient with the sub queries especially when you are first <strong>researching </strong>an unknown data population.<br />
Here is an example, in the &#8216;Left Join Query&#8217; above where there are 30 loans in the in the original population and not in the returned population. Leaving the &#8216;select * from original_loan_pop&#8217; allows you to see the details of the loans or data set and easily add or remove fields from the query. This allows flexibility in researching the issue or variance.</p>
]]></content:encoded>
	</item>
	<item>
		<title>By: Nick Fotopoulos</title>
		<link>http://technology-advisors.net/06/business-data-analysis-data-sql/comment-page-1/#comment-133</link>
		<dc:creator>Nick Fotopoulos</dc:creator>
		<pubDate>Sun, 14 Jun 2009 03:46:32 +0000</pubDate>
		<guid isPermaLink="false">http://technology-advisors.net/?p=109#comment-133</guid>
		<description>Why write the select list as sub queries when you don&#039;t have any additional joins and where clauses in them.

Select * from
(select * from original_loan_pop)a
join
(select * from returned_loan_pop)b
on a.loan_num = b.loan_num

is the same as

Select * from
original_loan_pop a
join
returned_loan_pop b
on a.loan_num = b.loan_num

???</description>
		<content:encoded><![CDATA[<p>Why write the select list as sub queries when you don&#8217;t have any additional joins and where clauses in them.</p>
<p>Select * from<br />
(select * from original_loan_pop)a<br />
join<br />
(select * from returned_loan_pop)b<br />
on a.loan_num = b.loan_num</p>
<p>is the same as</p>
<p>Select * from<br />
original_loan_pop a<br />
join<br />
returned_loan_pop b<br />
on a.loan_num = b.loan_num</p>
<p>???</p>
]]></content:encoded>
	</item>
</channel>
</rss>

<!-- Dynamic page generated in 0.442 seconds. -->
<!-- Cached page generated by WP-Super-Cache on 2012-05-20 21:31:41 -->
<!-- Compression = gzip -->
