/home/leansigm/public_html/components/com_easyblog/services<title>Five ways to handle large datasets</title>
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	<h1>Five ways to handle large datasets</h1>
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			<span class="post-date">Jul 04</span>

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				Posted by <a href="/forum/user/1368-jamila-dhamangamwala">Jamila dhamangamwala </a>				in <a href="/resources/sigmaway-blog/analytics">Analytics</a>			</span>
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	<p>&nbsp;Instead of cracking your head on the entire data available it is of utmost importance to target the data which actually matters. Here are 5 ways to do so:-</p>
<p>1. First, find out the KPI (key performance indicator) of interest.</p>
<p>2. Drain out the noise that is creating useless buzz. This includes activities like likes and retweets graphs.</p>
<p>3. Filter the data patterns that make sense and avoid irrelevant or accidental patterns.</p>
<p>4. Use these data patterns to generate meaningful conclusions.</p>
<p>5. Avoid redundancies by sharing information. This is a key point in the field of analytics.</p>
<p>To read more, follow:&nbsp;<a href="http://marketingland.com/blinded-by-data-181971" target="-blank">http://marketingland.com/blinded-by-data-181971</a></p>
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		<a href="/blog/tags/data-patterns">
		<span itemprop="keywords">data patterns</span>
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		<a href="/blog/tags/kpi">
		<span itemprop="keywords">KPI</span>
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		<a href="/blog/tags/key-performance-indicator">
		<span itemprop="keywords">Key Performance Indicator</span>
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