/home/leansigm/public_html/components/com_easyblog/services<title>Changes in Data Analytics over a decade.</title>
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	<h1>Changes in Data Analytics over a decade.</h1>
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			<span class="post-date">Jul 17</span>

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				Posted by <a href="/forum/user/2332-aakansha-gupta">Aakansha Gupta</a>				in <a href="/resources/sigmaway-blog/analytics">Analytics</a>			</span>
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	<p><span style="color: #000000; font-family: Calibri, sans-serif; font-size: 14.6667px; line-height: normal;">The last decade saw the massive growth of <a href="/our-services/analytics.html" target="_blank" rel="noopener noreferrer">big data</a>. During that time, all the technologies did not change but there have been a lot of transformations. Cloud analytics, uses a range of analytical tools to help companies extract information from a massive amount of data and present it in a form that is readily available via web browser, has become popular among the companies with the emerging new data sources. With the need to store and process big data, a whole constellation of open source software such as <a href="/our-services/analytics.html" target="_blank" rel="noopener noreferrer">Hadoop</a> emerged, which is used to store and do a basic processing on big data and is also cheaper than a data warehouse for similar volumes of data. Scripting languages like Hive, Pig, and Python along with many open source tools like Spark are gaining much popularity. Read more at: <a href="https://hbr.org/2017/06/how-analytics-has-changed-in-the-last-10-years-and-how-its-stayed-the-same" target="_blank" rel="noopener noreferrer">https://hbr.org/2017/06/how-analytics-has-changed-in-the-last-10-years-and-how-its-stayed-the-same</a></span></p>
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		<span itemprop="keywords">Hive</span>
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		<a href="/blog/tags/analytics">
		<span itemprop="keywords">analytics</span>
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		<span itemprop="keywords">cloud analytics</span>
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