...Google Analytics Google Analytics Google Analytics is a free service offered by Google that will give detailed statistics about visitors to a website. Google Analytics has the ability to track visitors from all referrers, such as search engines, display advertising, pay-per click, email and links with in documents such as PDF. Google Analytics uses a dashboard type data view to display high level data for the casual user or as I like to call them “Management”. But Google Analytics also provides more in-depth data report. With the use of Google Analytics pages that are performing poorly can be identified and as well as pages that are the “Most hit”. Google Analytics can also tell where your visitors are coming from, and how long they are staying on the site. Google Analytics can also track and return results for mobile websites, mobile apps and web enabled mobile phones. This includes high-end phones such as iPhone or Android to non-JavaScript enabled devices. Google Analytics can also be used for ecommerce reporting. Google Analytics can track sales goals and transactions, if integrated with AdWords you can track data on keywords, search queries and much more. If integrated with AdSense, you can get reports on site content that is generating the most revenue. Google Analytics offers customized reporting. Some of the reporting features include advanced analysis tools. These tools can produce advance analysis with the use of pivot tables, multi dimensions and...
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...Google Analytics March 3, 2012 Google Analytics Google analytics is a service the Google Company gives to clients. Through this service Google wants to attract more of the traffic in the internet to get more site visitors into customers for the site owner. The owner of the site can use Google Analytics to learn which online marketing initiatives are cost effective and how visitors actually interact with the site. It shows how the site owners can make informed site design improvements, drive targeted traffic, and increase your conversions and profits. Google Analytics uses a first-party cookie and Java script codes to collect information about visitors and track your advertising campaign data. Google Analytics anonymously tracks how visitors interact with a website, including where they came from, what they did on the site, and whether they completed any of the site`s conversion goals. Analytics also keep track of your e-commerce data, and combines this with campaign and conversion information to provide insight into the performance of your advertising campaigns. All this information is presented in an easy to read, yet through manner, through intuitive visual reports. Google Analytics won`t affect the performance or the appearance of your website and there are no extra files to host on your website. Some of the things Google Analytics do are: 1. Goals Track Sales and Conversions - Measure your site engagement goals against: threshold levels that you define. 2....
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...division of my company, I am not familiar with the names or metrics used to evaluate important data, but I do know from experience and part of my job function, reports and data gathered are used to make judgments and decisions about new products and constant improvements for existing services we currently provide. Surveys are completed by our travel partners and guests, and even employees. We compile reports and present them to management electronically. Our research, experience, and use of different applications, along with our IT departments, helps management and executives determine which direction to move forward. Feedback from our travel partners and guests are both direct and indirect. Upon learning about programs such as Google Analytics, the importance of webpage layout, the amount of time spent on our site, as well, as how often individuals contact our chat system and sales automation for assistance with our product gives insight to “how we are doing” as a company. Constant looping and revisiting certain pages...
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...O C T O B E R 2 0 11 m c k i n s e y g l o b a l i n s t i t u t e Are you ready for the era of ‘big data’? Brad Brown, Michael Chui, and James Manyika Radical customization, constant experimentation, and novel business models will be new hallmarks of competition as companies capture and analyze huge volumes of data. Here’s what you should know. The top marketing executive at a sizable US retailer recently found herself perplexed by the sales reports she was getting. A major competitor was steadily gaining market share across a range of profitable segments. Despite a counterpunch that combined online promotions with merchandizing improvements, her company kept losing ground. When the executive convened a group of senior leaders to dig into the competitor’s practices, they found that the challenge ran deeper than they had imagined. The competitor had made massive investments in its ability to collect, integrate, and analyze data from each store and every sales unit and had used this ability to run myriad real-world experiments. At the same time, it had linked this information to suppliers’ databases, making it possible to adjust prices in real time, to reorder hot-selling items automatically, and to shift items from store to store easily. By constantly testing, bundling, synthesizing, and making information instantly available across the organization— from the store floor to the CFO’s office—the rival company had become a different, far nimbler type of business...
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...volume, which is the quantity of data. The second is Variety, which the type of Data. The third is velocity, which is the speed of the data is gathered. The fourth one Variability, which is inconsistency of data can hamper processes to manage it. The final one is Veracity, which is the quality of data captured can vary. These data sets are growing rapidly mainly because they are gathered at a fairly cheap. The world's technological per-capita are doubling every 40 months. Business intelligence with data with high information density to look for trends. Big Data also increased information management specialist. Some of the largest companies like IBM and Microsoft spent over 15 billion dollars on software firms which specialize in data analytics. Governments use big data because it's efficient in terms of productivity and innovation. While gathering big data is a big benefit there are also some issues that need to brought up. Some policies involving privacy, security, and liability. Companies would need to put the right people to manage and use this data efficiently. Accessibility is also crucial because most likely there will need to be third parties included and incentives put in place to enable...
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...Date: 04-19-2015 The New Frontier: Data Analytics (Course title: Info System Decision Making) Professor: Clifton Howell Student: Deep Ajabani Data analysis is the process of finding the right data to answer your question, understanding the processes underlying the data, discovering the important patterns in the data, and then communicating your results to have the biggest possible impact. Analytics have been used in business since the management exercises were put into place by Frederick Winslow Taylor in the late 19th century. Henry Ford measured the time of each component in his newly established assembly line. But analytics began to command more attention in the late 1960s when computers were used in decision support systems. Since then, analytics have changed and formed with the development of enterprise resource planning (ERP) systems, data warehouses, and a large number of other software tools and processes. In later years the business analytics have exploded with the introduction to computers. This change has brought analytics to a whole new level and has made the possibilities endless. As far as analytics has come in history, and what the current field of analytics is today many people would never think that analytics started in the early 1900s with Mr. Ford. We are going to have a look on Big Data Analytics. Let’s have a look on advantages of big data analytics. It helps marketing companies build models based on historical data to predict...
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...Definition IoT is one of the fastest growing technologies in computing. It is an environment where people, animals, or objects are presented with unique identifiers and the ability to transfer data over a network (Rouse, 2014). It has emerged from combining wireless technologies, micro-electromechanical systems, and the internet (Rouse, 2014). See Figure 1. These wireless technologies are equipped with, or connected to a smart device allowing data collection and communication through the internet (Caron, Bosua, Maynard, & Ahmad, 2016). Figure 1. IoT Ecosystem (Medici, 2015) Benefits * Tracking behavior for real-time marketing (Borne, 2014). * Enhanced situational awareness (Borne, 2014). * Sensor-driven decision analytics (Borne, 2014). * Process optimization (Borne, 2014). * Optimized resource consumption (Borne, 2014). * Instantaneous control and response in complex autonomous systems (Borne, 2014). * Increase operational efficiency, power new business models, and improve quality of life (Harrell, 2015). * Provide an accurate analysis of customer data (Medici, 2015). Some Applications of IoF Business intelligence (BI). “The BI application ensures the analysis and measurement of the consumer’s thoughts, behaviors, relationships, buying attitudes, choices, and many more parameters that form the backbone of effective strategy building, business operations management, customer relationship management, and other business operations” ...
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...companies in every industry are using analytics to replace intuition and guesswork in their decision-making. As a result, managers are collecting and analyzing enormous data sets to discover new patterns and insights and running controlled experiments to test hypotheses. This course prepares students to understand structured data and business analytics and become leaders in these areas in business organizations. This course teaches the scientific process of transforming data into insights for making better business decisions. It covers the methodologies, algorithms, issues, and challenges related to analyzing business data. It will illustrate the processes of analytics by allowing students to apply business analytics algorithms and methodologies to real-world business datasets from finance, marketing, and operations. The use of real-world examples and cases places business analytics techniques in context and teaches students how to avoid the common pitfalls, emphasizing the importance of applying proper business analytics techniques. In addition to cases, this course features hands-on experiences with data collection using Python programs and analytics software such as SAS Enterprise Guide. Throughout the semester, each team works to frame a variety of business issues as an analytics problem, analyze data provided by the company, and generate applicable business insights as a secondary objective, while also learning essential business analytics techniques. Students benefit...
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...Disruptive Innovation: A new era of Crowdsourced Data Analytics! Abstract: The existing business paradigm of data analytics is set for a transformation. Today, companies are experimenting to replicate the “Outsourced data analytics” model to “Crowdsourced data analytics”. Companies like Kaggle, Crowdanalytix and others are hitting the headlines of top analytics blogs across the globe. The reason is that the new business model promises a drastic decrease in the cost of analytics for companies long with the flexibility to get the problem solved anytime with much less effort. In short, it’s not just crowdsourcing that is the novelty of the concept, but the manner in which it is put to use that steals the show. Abstract: The existing business paradigm of data analytics is set for a transformation. Today, companies are experimenting to replicate the “Outsourced data analytics” model to “Crowdsourced data analytics”. Companies like Kaggle, Crowdanalytix and others are hitting the headlines of top analytics blogs across the globe. The reason is that the new business model promises a drastic decrease in the cost of analytics for companies long with the flexibility to get the problem solved anytime with much less effort. In short, it’s not just crowdsourcing that is the novelty of the concept, but the manner in which it is put to use that steals the show. General Management General Management MBA Core, 2nd Year MBA Core, 2nd Year Ayush Malhotra NMIMS,Mumbai Ayush Malhotra ...
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...Spring 2016 | Elective | FIN | FIN7503 | EQUITIES | Spring 2016 | Elective | FIN | FIN7504 | RISK MANAGEMENT | Spring 2016 | Elective | FIN | FIN7511 | CORP FIN I:RASNG CAP | Spring 2016 | Elective | FIN | FIN7513 | FIXED INCOME | Spring 2016 | Elective | FIN | FIN7516 | CORP FIN II:EVAL OPP | Spring 2016 | Elective | FIN | FIN7517 | FIN & VAL SUSTNBLTY | Spring 2016 | Elective | FIN | FIN7518 | Managing Portfolios | Spring 2016 | Elective | FIN | FIN7565 | RE INV FUNDAMENTALS | Spring 2016 | Elective | FIN | FIN7572 | BABSON COLLEGE FUND | Spring 2016 | Elective | FIN | FIN7573 | INVESTMENT BANKING | Spring 2016 | Elective | FIN | FIN7578 | RE DEVELOPMENT | Spring 2016 | Elective | MATH | QTM7571 | Bus Intel, Analytics, Visualization | Spring 2016 | Elective | MATH | QTM9515...
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...become an analytic competitor. Questions as to what are the sources of Decision Making to an analytic competitor will also be discussed. A discussion on how influential quantitative modeling is and its utility in business decision making will be summarized. Finally, a Christian view that presents an ethical perspective on quantitative modeling and decision making will be presented. In an ever increasing global environment, maintaining a competitive advantage can be sustained through quantitative modeling, which can make a company a viable analytic competitor. How Can a Company Become and Be an Analytics Competitor Competitors make it increasingly more difficult to maintain a strategic competitive advantage when exclusive technologies, products and services can be duplicated (Davenport, Cohen & Jacobson, 2005). Organizations are now framing their strategies to accomplish optimization of “key business processes”: serving optimal customers, optimize supply chains, and understand and create optimal financial performance (Davenport, et al., 2005, p. 1). Optimization strategies demand that organizations now gather extensive data and perform extensive analysis that will guide executives in the decision-making process. The data and the analysis must be specific to the issues. In other words, they must relate in order to be useful in decision-making for the firm. In order to benefit from this competitive advantage companies also have to possess the analytic capabilities...
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...The New Frontier: Data Analytics Phylicia Marie Phillips Professor Progress Mtshali, Ph. D. Information Systems Decision-Making April 17, 2016 In the past, analytics was reserved for back-room debates by data geeks producing monthly reports on how things are going. Today, analytics make a difference in how a company does business, day to day, and even minute by minute; more specifically how Walmart does business. As many know, Walmart is an American based multinational retail corporation that operates a chain of hypermarkets, grocery stores and discount stores. With over eleven thousand stores and clubs in 27 countries, information technology and data analytics play a major role in Walmart’s survival and helps maintain its competitive advantage. Data Analytics Overview The business intelligence and analytic technologies and applications currently adopted in industry can be considered as BI&A 1.0, where data are mostly structured, collected by companies through various legacy systems, and often stored in commercial relational database management systems (Bottles and Begoli, 2014). The analytical techniques most commonly used in these systems, popularized in the 1990s, are mainly grounded in statistical methods developed in the 1970s and data mining techniques developed in the 1980s (Chiang, 2012). The digitalization of information has created more data and the development of cloud computing, and faster and faster computers has made the increased data more accessible...
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...3/3/2016 Google: The World’s First Information Utility? Springer 4 How Google innovates Innovation at Google has been internally focused on building an IT infrastructure that is robust and enables easy creation of new products and services. Going forward, the information utility will require more externally oriented innovation focused on supporting external developers and customer applications. But how does Google foster the innovation that leads to new applications? This is an important question because most companies cannot expect to imitate its IT infrastructure, but they can imitate its innovation strategies. Google uses the following four strategies. 4.1 Explicit focus on R&D Google’s extraordinary revenue enables it to have a luxury few firms can enjoy today – an R&D lab that focuses on developing revolutionary hardware and software ideas along with complementary services. More than onehalf of the company’s employees are engineers and scientists, and there might be hundreds of projects in development at any given time. Many prototypes are made available on the lab’s website for the interested public to download and try in the beta stage. By launching these beta products and services publicly to be tried out, Google can see which ones take off, get feedback, and incrementally improve them without having to scrap a product that might take off with further development. 4.2 Acquisition of talented people Google is among the most active hightech companies in hiring top ...
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...E-Commerce Marketing Plan | August 21 2011 | Internet marketing strategy for Tesla Tech | At Tesla Tech they offer a variety of computer related services. Services offered include standard computer repair, upgrades, custom gaming personal computers, accessories, and much more. Tesla Tech’s Marketing niche will be fairly pinpointed, set to cater to the older generation that needs and wants to learn how to use modern day computers and do not have the means to learn. This strategy will bring new business and keep customers returning to our website to learn about different applications and functions of the new computer that they purchased from Tesla Tech. This market is fairly untapped in the online and even onsite marketplace. Tesla Tech plans to offer this online service free of charge to customers that buy custom made or brand new desktop or laptop computers from our online e-commerce website. This will allow the company to generate many new customers within the age rages of 45+ who may be timid or reluctant to buy a new pc because of their perception that they do not have the necessary tools or knowledge to complete basic computer related tasks. Sales of new computer will increase since our entire strategy will thrive on the fact that consumers will know that they will be able to log-in to our video tutorial database and educate themselves on whatever subject they need help with. Our main demographic will be single or married woman age 45 and up. This demographic was...
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...embrace it were online and startup firms. Firms like Google, eBay, LinkedIn, and Facebook were built around big data from the beginning. Like many new information technologies, big data can bring about dramatic cost reductions, substantial improvements in the time required to perform a computing task, or new product and service offerings. Davenport.T (2013). Big Data is emerging from the realms of science projects at Web companies to help companies like telecommunication giants understand exactly which customers are unhappy with service and what processes caused the dissatisfaction, and predict which customers are going to change carriers. To obtain this information, billions of loosely-structured bytes of data in different locations needs to be processed until the needle in the haystack is found. The analysis enables executive management to fix faulty processes or people and maybe be able to reach out to retain the at-risk customers. The real business impact is that big data technologies can do this in weeks or months, four-or-more-times faster than traditional data warehousing approaches. Floyer.D (2015). Literature Review The IT techniques and tools to execute big data processing are new, very important and exciting. Big data is data that is too large to process using traditional methods. It originated with Web search companies who had the problem of querying very large distributed aggregations of loosely-structured data. Google developed MapReduce to support distributed computing...
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