Analytics - Revision history

Shayna.lodge: Minor copyediting, especially to third-last sentence.

2021-08-04T17:27:33Z

Minor copyediting, especially to third-last sentence.

Alexander.mason at 20:44, 9 March 2021

2021-03-09T20:44:52Z

Alamb066 at 19:18, 23 July 2020

2020-07-23T19:18:23Z

Karla.diel at 13:33, 30 March 2020

2020-03-30T13:33:41Z

Karla.diel at 13:32, 30 March 2020

2020-03-30T13:32:57Z

Karla.diel at 13:32, 30 March 2020

2020-03-30T13:32:12Z

Karla.diel at 13:31, 30 March 2020

2020-03-30T13:31:56Z

Karla.diel at 13:31, 30 March 2020

2020-03-30T13:31:29Z

Karla.diel at 13:30, 30 March 2020

2020-03-30T13:30:07Z

Karla.diel at 13:29, 30 March 2020

2020-03-30T13:29:37Z

@@ Line 8: / Line 8: @@
 . ''Unstructured Data Analytics'': “Combines text mining, association, clustering, and other unsupervised learning techniques to codify large data sets.”
-. ''Operational Analytics'': “The processes of tracking and integrating real-time streams of information, deriving conclusions based on predictive models of behaviour, and triggering automatic responses and alerts.”<br></br>
+. ''Operational Analytics'': “The processes of tracking and integrating real-time streams of information, deriving conclusions based on predictive models of behaviour, and triggering automatic responses and alerts.”<br>
-Systematic computational transformation of enterprise data into insights, for the purpose of making better decisions<ref>''Accountabilities, Responsibilities, Authorities (ARA),'' ADM (Data, Innovation and Analytics)</ref> <br></br>
+Simply put, "analytics" refers to the systematic computational transformation of enterprise data into insights, for the purpose of making better decisions.<ref>''Accountabilities, Responsibilities, Authorities (ARA),'' ADM (Data, Innovation and Analytics)</ref> <br></br>
-The [https://www.lexico.com/definition/analytics Oxford English Dictionary] refers to analytics as "The systematic computational analysis of data or statistics."
+The [https://www.lexico.com/definition/analytics Oxford English Dictionary] defines analytics as "The systematic computational analysis of data or statistics."
 <ref><nowiki>https://www.lexico.com/definition/analytics</nowiki></ref><br></br>
-// content '''''analytics''''' is relevant in many industries. <br></br>
+// Content '''''analytics''''' is relevant in many industries. <br></br>
 <references />

← Older revision		Revision as of 20:44, 9 March 2021
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−	Analytics has emerged as a catch-all term for a variety of different business intelligence (BI) and application-related initiatives. For some, it is the process of analyzing information from a particular domain, such as website analytics. For others, it is applying the breadth of BI capabilities to a specific content area (for example, sales, service, supply chain). In particular, BI vendors use the “analytics” moniker to differentiate their products from the competition. Increasingly, “analytics” is used to describe statistical and mathematical data analysis that clusters, segments, scores and predicts what scenarios are most likely to happen. Whatever the use cases, “analytics” has moved deeper into the business vernacular. Analytics has garnered a burgeoning interest from business and IT professionals looking to exploit huge mounds of internally generated and externally available data.<ref><nowiki>https://www.gartner.com/en/information-technology/glossary/analytics</nowiki></ref><br /><br />Systematic computational transformation of enterprise data into insights, for the purpose of making better decisions<ref>''Accountabilities, Responsibilities, Authorities (ARA),'' ADM (Data, Innovation and Analytics)</ref>	+	Analytics has emerged as a catch-all term for a variety of different business intelligence (BI) and application-related initiatives. For some, it is the process of analyzing information from a particular domain, such as website analytics. For others, it is applying the breadth of BI capabilities to a specific content area (for example, sales, service, supply chain). In particular, BI vendors use the “analytics” moniker to differentiate their products from the competition. Increasingly, “analytics” is used to describe statistical and mathematical data analysis that clusters, segments, scores and predicts what scenarios are most likely to happen. Whatever the use cases, “analytics” has moved deeper into the business vernacular. Analytics has garnered a burgeoning interest from business and IT professionals looking to exploit huge mounds of internally generated and externally available data.<ref><nowiki>https://www.gartner.com/en/information-technology/glossary/analytics</nowiki></ref><br /><br />
		+	The '''DAMA-DMBOK2'''<ref>DAMA-DMBOK2, 1.3.11-1.3.14, pgs 508-510</ref>recognizes 4 different types of analytics that are as follows:
		+
		+	1. ''Predictive Analytics'': “The development of probability models based on variables, including historical data related to possible events (purchases, changes in price, etc.).”
		+
		+	2. ''Prescriptive Analytics'': “Anticipates what will happen, when it will happen, and implies why it will happen.”
		+
		+	3. ''Unstructured Data Analytics'': “Combines text mining, association, clustering, and other unsupervised learning techniques to codify large data sets.”
		+
		+	4. ''Operational Analytics'': “The processes of tracking and integrating real-time streams of information, deriving conclusions based on predictive models of behaviour, and triggering automatic responses and alerts.”<br></br>
		+
		+	Systematic computational transformation of enterprise data into insights, for the purpose of making better decisions<ref>''Accountabilities, Responsibilities, Authorities (ARA),'' ADM (Data, Innovation and Analytics)</ref> <br></br>
		+	The [https://www.lexico.com/definition/analytics Oxford English Dictionary] refers to analytics as "The systematic computational analysis of data or statistics."
		+	<ref><nowiki>https://www.lexico.com/definition/analytics</nowiki></ref><br></br>
		+
		+	// content '''''analytics''''' is relevant in many industries. <br></br>
		+
	<references />		<references />

← Older revision		Revision as of 19:18, 23 July 2020
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−	Analytics has emerged as a catch-all term for a variety of different business intelligence (BI)- and application-related initiatives. For some, it is the process of analyzing information from a particular domain, such as website analytics. For others, it is applying the breadth of BI capabilities to a specific content area (for example, sales, service, supply chain). In particular, BI vendors use the “analytics” moniker to differentiate their products from the competition. Increasingly, “analytics” is used to describe statistical and mathematical data analysis that clusters, segments, scores and predicts what scenarios are most likely to happen. Whatever the use cases, “analytics” has moved deeper into the business vernacular. Analytics has garnered a burgeoning interest from business and IT professionals looking to exploit huge mounds of internally generated and externally available data.<ref><nowiki>https://www.gartner.com/en/information-technology/glossary/analytics</nowiki></ref><br /><br />Systematic computational transformation of enterprise data into insights, for the purpose of making better decisions<ref>''Accountabilities, Responsibilities, Authorities (ARA),'' ADM (Data, Innovation and Analytics)</ref>	+	Analytics has emerged as a catch-all term for a variety of different business intelligence (BI) and application-related initiatives. For some, it is the process of analyzing information from a particular domain, such as website analytics. For others, it is applying the breadth of BI capabilities to a specific content area (for example, sales, service, supply chain). In particular, BI vendors use the “analytics” moniker to differentiate their products from the competition. Increasingly, “analytics” is used to describe statistical and mathematical data analysis that clusters, segments, scores and predicts what scenarios are most likely to happen. Whatever the use cases, “analytics” has moved deeper into the business vernacular. Analytics has garnered a burgeoning interest from business and IT professionals looking to exploit huge mounds of internally generated and externally available data.<ref><nowiki>https://www.gartner.com/en/information-technology/glossary/analytics</nowiki></ref><br /><br />Systematic computational transformation of enterprise data into insights, for the purpose of making better decisions<ref>''Accountabilities, Responsibilities, Authorities (ARA),'' ADM (Data, Innovation and Analytics)</ref>
	<references />		<references />

← Older revision		Revision as of 13:33, 30 March 2020
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−	Analytics has emerged as a catch-all term for a variety of different business intelligence (BI)- and application-related initiatives. For some, it is the process of analyzing information from a particular domain, such as website analytics. For others, it is applying the breadth of BI capabilities to a specific content area (for example, sales, service, supply chain). In particular, BI vendors use the “analytics” moniker to differentiate their products from the competition. Increasingly, “analytics” is used to describe statistical and mathematical data analysis that clusters, segments, scores and predicts what scenarios are most likely to happen. Whatever the use cases, “analytics” has moved deeper into the business vernacular. Analytics has garnered a burgeoning interest from business and IT professionals looking to exploit huge mounds of internally generated and externally available data.<ref><nowiki>https://www.gartner.com/en/information-technology/glossary/analytics</nowiki></ref><br /><br />Systematic computational transformation of enterprise data into insights, for the purpose of making better decisions<ref~~><br /><br /~~>''Accountabilities, Responsibilities, Authorities (ARA),'' ADM (Data, Innovation and Analytics)</ref>	+	Analytics has emerged as a catch-all term for a variety of different business intelligence (BI)- and application-related initiatives. For some, it is the process of analyzing information from a particular domain, such as website analytics. For others, it is applying the breadth of BI capabilities to a specific content area (for example, sales, service, supply chain). In particular, BI vendors use the “analytics” moniker to differentiate their products from the competition. Increasingly, “analytics” is used to describe statistical and mathematical data analysis that clusters, segments, scores and predicts what scenarios are most likely to happen. Whatever the use cases, “analytics” has moved deeper into the business vernacular. Analytics has garnered a burgeoning interest from business and IT professionals looking to exploit huge mounds of internally generated and externally available data.<ref><nowiki>https://www.gartner.com/en/information-technology/glossary/analytics</nowiki></ref><br /><br />Systematic computational transformation of enterprise data into insights, for the purpose of making better decisions<ref>''Accountabilities, Responsibilities, Authorities (ARA),'' ADM (Data, Innovation and Analytics)</ref>
	<references />		<references />

← Older revision		Revision as of 13:32, 30 March 2020
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−	Analytics has emerged as a catch-all term for a variety of different business intelligence (BI)- and application-related initiatives. For some, it is the process of analyzing information from a particular domain, such as website analytics. For others, it is applying the breadth of BI capabilities to a specific content area (for example, sales, service, supply chain). In particular, BI vendors use the “analytics” moniker to differentiate their products from the competition. Increasingly, “analytics” is used to describe statistical and mathematical data analysis that clusters, segments, scores and predicts what scenarios are most likely to happen. Whatever the use cases, “analytics” has moved deeper into the business vernacular. Analytics has garnered a burgeoning interest from business and IT professionals looking to exploit huge mounds of internally generated and externally available data.<ref><nowiki>https://www.gartner.com/en/information-technology/glossary/analytics</nowiki></ref><br /><br />Systematic computational transformation of enterprise data into insights, for the purpose of making better decisions<ref>''Accountabilities, Responsibilities, Authorities (ARA),'' ADM (Data, Innovation and Analytics)</ref>	+	Analytics has emerged as a catch-all term for a variety of different business intelligence (BI)- and application-related initiatives. For some, it is the process of analyzing information from a particular domain, such as website analytics. For others, it is applying the breadth of BI capabilities to a specific content area (for example, sales, service, supply chain). In particular, BI vendors use the “analytics” moniker to differentiate their products from the competition. Increasingly, “analytics” is used to describe statistical and mathematical data analysis that clusters, segments, scores and predicts what scenarios are most likely to happen. Whatever the use cases, “analytics” has moved deeper into the business vernacular. Analytics has garnered a burgeoning interest from business and IT professionals looking to exploit huge mounds of internally generated and externally available data.<ref><nowiki>https://www.gartner.com/en/information-technology/glossary/analytics</nowiki></ref><br /><br />Systematic computational transformation of enterprise data into insights, for the purpose of making better decisions<ref><br /><br />''Accountabilities, Responsibilities, Authorities (ARA),'' ADM (Data, Innovation and Analytics)</ref>
	<references />		<references />

@@ Line 1: / Line 1: @@
 # Analytics has emerged as a catch-all term for a variety of different business intelligence (BI)- and application-related initiatives. For some, it is the process of analyzing information from a particular domain, such as website analytics. For others, it is applying the breadth of BI capabilities to a specific content area (for example, sales, service, supply chain). In particular, BI vendors use the “analytics” moniker to differentiate their products from the competition. Increasingly, “analytics” is used to describe statistical and mathematical data analysis that clusters, segments, scores and predicts what scenarios are most likely to happen. Whatever the use cases, “analytics” has moved deeper into the business vernacular. Analytics has garnered a burgeoning interest from business and IT professionals looking to exploit huge mounds of internally generated and externally available data.<ref><nowiki>https://www.gartner.com/en/information-technology/glossary/analytics</nowiki></ref>
-<br /><br /># Systematic computational transformation of enterprise data into insights, for the purpose of making better decisions<ref>''Accountabilities, Responsibilities, Authorities (ARA),'' ADM (Data, Innovation and Analytics)</ref>
+<br /><br />Systematic computational transformation of enterprise data into insights, for the purpose of making better decisions<ref>''Accountabilities, Responsibilities, Authorities (ARA),'' ADM (Data, Innovation and Analytics)</ref>
 <references />

← Older revision		Revision as of 13:29, 30 March 2020
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	Analytics has emerged as a catch-all term for a variety of different business intelligence (BI)- and application-related initiatives. For some, it is the process of analyzing information from a particular domain, such as website analytics. For others, it is applying the breadth of BI capabilities to a specific content area (for example, sales, service, supply chain). In particular, BI vendors use the “analytics” moniker to differentiate their products from the competition. Increasingly, “analytics” is used to describe statistical and mathematical data analysis that clusters, segments, scores and predicts what scenarios are most likely to happen. Whatever the use cases, “analytics” has moved deeper into the business vernacular. Analytics has garnered a burgeoning interest from business and IT professionals looking to exploit huge mounds of internally generated and externally available data.<ref><nowiki>https://www.gartner.com/en/information-technology/glossary/analytics</nowiki></ref>		Analytics has emerged as a catch-all term for a variety of different business intelligence (BI)- and application-related initiatives. For some, it is the process of analyzing information from a particular domain, such as website analytics. For others, it is applying the breadth of BI capabilities to a specific content area (for example, sales, service, supply chain). In particular, BI vendors use the “analytics” moniker to differentiate their products from the competition. Increasingly, “analytics” is used to describe statistical and mathematical data analysis that clusters, segments, scores and predicts what scenarios are most likely to happen. Whatever the use cases, “analytics” has moved deeper into the business vernacular. Analytics has garnered a burgeoning interest from business and IT professionals looking to exploit huge mounds of internally generated and externally available data.<ref><nowiki>https://www.gartner.com/en/information-technology/glossary/analytics</nowiki></ref>
		+
		+	Systematic computational transformation of enterprise data into insights, for the purpose of making better decisions<ref>''Accountabilities, Responsibilities, Authorities (ARA),'' ADM (Data, Innovation and Analytics)</ref>
		+	<references />