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Introduction to Computing - David Evans

The first million years of hominid history produced tools to amplify, and later mechanize, our physical abilities to enable us to move faster, reach higher, and hit harder. We have developed tools that amplify physical force by the trillions and increase the speeds at which we can travel by the thousands.

Computing is the ultimate mental amplifier.

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Objective   10/24/2017

Web Analytics resources.

Analytics   10/24/2017

from Wikipedia

Analytics is the discovery, interpretation, and communication of meaningful patterns in data. Especially valuable in areas rich with recorded information, analytics relies on the simultaneous application of statistics, computer programming and operations research to quantify performance.

Organizations may apply analytics to business data to describe, predict, and improve business performance. Specifically, areas within analytics include predictive analytics, prescriptive analytics, enterprise decision management, descriptive analytics, cognitive analytics, retail analytics, store assortment and stock-keeping unit optimization, marketing optimization and marketing mix modeling, web analytics, call analytics, speech analytics, sales force sizing and optimization, price and promotion modeling, predictive science, credit risk analysis, and fraud analytics. Since analytics can require extensive computation (see big data), the algorithms and software used for analytics harness the most current methods in computer science, statistics, and mathematics.[1]

Analytics vs. analysis

Analytics is multidisciplinary. There is extensive use of mathematics and statistics, the use of descriptive techniques and predictive models to gain valuable knowledge from data—data analysis. The insights from data are used to recommend action or to guide decision making rooted in business context. Thus, analytics is not so much concerned with individual analyses or analysis steps, but with the entire methodology. There is a pronounced tendency to use the term analytics in business settings e.g. text analytics vs. the more generic text mining to emphasize this broader perspective.[citation needed]. There is an increasing use of the term advanced analytics,[citation needed] typically used to describe the technical aspects of analytics, especially in the emerging fields such as the use of machine learning techniques like neural networks to do predictive modeling.

Google Analytics   10/24/2017

from Wikipedia    Google Analytics

Google Analytics is a freemium web Analytics service offered by Google that tracks and reports website traffic.

Google launched the service in November 2005 after acquiring Urchin. Google Analytics is now the most widely used web analytics service on the Internet. Google Analytics is offered also in two additional versions: a subscription based Google Analytics Premium targeted at enterprise users and Google Analytics for Mobile Apps, an SDK that allows gathering usage data from iOS and Android Apps.

Google acquired Urchin Software Corp. in April 2005. Google's service was developed from Urchin on Demand. The system also brings ideas from Adaptive Path, whose product, Measure Map, was acquired and used in the redesign of Google Analytics in 2006. Google continued to sell the standalone, installable Urchin WebAnalytics Software through a network of value-added resellers until discontinuation on March 28, 2012.

The Google-branded version was rolled out in November 2005 to anyone who wished to sign up. However, due to extremely high demand for the service, new sign-ups were suspended only a week later. As capacity was added to the system, Google began using a lottery-type invitation-code model. Prior to August 2006 Google was sending out batches of invitation codes as server availability permitted; since mid-August 2006 the service has been fully available to all users – whether they use Google for advertising or not.

The newer version of Google Analytics tracking code is known as the asynchronous tracking code, which Google claims is significantly more sensitive and accurate, and is able to track even very short activities on the website. The previous version delayed page loading and so, for performance reasons, it was generally placed just before the </body> body close HTML tag. The new code can be placed between the <head>...</head> HTML head tags because, once triggered, it runs in parallel with page loading.

In April 2011 Google announced the availability of a new version of Google Analytics featuring multiple dashboards, more custom report options, and a new interface design. This version was later updated with some other features such as real-time analytics and goal flow charts.

In December 1212 the latest version of Google Analytics was announced, called 'Universal Analytics'. The key differences from the previous versions were: cross-platform tracking, flexible tracking code to collect data from any device, and the introduction of custom dimensions and custom metrics.




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