{"id":65,"date":"2022-12-02T23:36:23","date_gmt":"2022-12-02T23:36:23","guid":{"rendered":"https:\/\/pressbooks.ccconline.org\/accmarketinganalytics2\/chapter\/module-1-instructor-guide\/"},"modified":"2023-03-13T18:02:13","modified_gmt":"2023-03-13T18:02:13","slug":"module-1-instructor-guide","status":"publish","type":"chapter","link":"https:\/\/pressbooks.ccconline.org\/accmarketinganalytics2\/chapter\/module-1-instructor-guide\/","title":{"raw":"Module 1: Review Activities","rendered":"Module 1: Review Activities"},"content":{"raw":"<div class=\"overview:\">\r\n\r\n<img class=\"aligncenter wp-image-64\" src=\"https:\/\/pressbooks.ccconline.org\/accmarketinganalytics\/wp-content\/uploads\/sites\/105\/2022\/12\/Picture6-300x93.jpg\" alt=\"High school teacher calling on student in classroom\" width=\"1055\" height=\"327\" \/>\r\n<h1>Overview:<\/h1>\r\n<div class=\"textbox textbox--learning-objectives\"><header class=\"textbox__header\">\r\n<p class=\"textbox__title\">In this module we review the Module 1\u00a0 fundamentals of marketing analytics and data management while focusing on addressing the following:<\/p>\r\n\r\n<\/header>\r\n<div class=\"textbox__content\">\r\n<ul>\r\n \t<li>What is meant by marketing analytics in a digital marketing context?<\/li>\r\n \t<li>How to apply principles of marketing analytics to identify the right business problem.<\/li>\r\n \t<li>Identify types of data sources<\/li>\r\n \t<li>Explain several types of data<\/li>\r\n \t<li>Define data measurement types and give examples.<\/li>\r\n \t<li>Understand the difference between predictors and target variables.<\/li>\r\n \t<li>Compare and contrast supervised and unsupervised modeling.<\/li>\r\n<\/ul>\r\n<\/div>\r\n<\/div>\r\n<p class=\"import-Normal\">Read \u201cModule 1: Readings and Videos Part II\u201d document before completing the following activities.<\/p>\r\n\r\n<h2>Review Activity #1 Datasets<\/h2>\r\n<p class=\"import-Normal\">Visit <a class=\"rId5\" href=\"http:\/\/www.data.gov\"><span class=\"import-Hyperlink\">www.data.gov<\/span><\/a> and then click on \u201cData\u201d and complete the following:<\/p>\r\n\r\n<ul>\r\n \t<li>How many datasets are currently located on the website for free?<\/li>\r\n \t<li>Select one dataset and develop a scenario where the data might be helpful for a marketing manager.<\/li>\r\n \t<li>Discuss how exploring the data could guide the marketing manager in making more informed decisions?<\/li>\r\n<\/ul>\r\n<h2>Review Activity #2<\/h2>\r\n<p class=\"import-Normal\">After watching the video on the marketing funnel explained, do a quick outline of a brand of your choice and go through each of the steps and then explain which part\/step of the funnel could be improved and why.<\/p>\r\n\r\n<h2>Review Activity #3<\/h2>\r\n<p class=\"import-Normal\">Define the following sources of secondary data and provide at least two examples of each and explain why these sources are important: Public datasets, online sites, mobile data, and channel partners.<\/p>\r\n\r\n<h2>Review Activity #4<\/h2>\r\nProduce three questions like the example in the readings and videos document of \u201cDoes the economy impact college enrollment numbers?\u201d Then for each of the three questions identify what the independent and dependent\/target and outcome variables are.\r\n<h2>Review Activity #5<\/h2>\r\n<p class=\"import-Normal\">Develop two questions that an airline company might be interested in answering. Describe types of unstructured and structured data that might be important to answering the questions. What data sources might be useful?<\/p>\r\n\r\n<h2 class=\"import-Normal\">Review Activity #6 Supervised vs. Unsupervised Learning<\/h2>\r\n<p class=\"import-Normal\"><span lang=\"en-US\" xml:lang=\"en-US\">This activity is important because depending on the nature of the business problem being addressed, <\/span><span lang=\"en-US\" xml:lang=\"en-US\">several types<\/span><span lang=\"en-US\" xml:lang=\"en-US\"> of algorithms can be used. This activity focuses on two models: supervised learning and unsupervised learning.<\/span><\/p>\r\n<p class=\"import-Normal\"><span lang=\"en-US\" xml:lang=\"en-US\">The goal of this activity is to <\/span><span lang=\"en-US\" xml:lang=\"en-US\">demonstrate<\/span><span lang=\"en-US\" xml:lang=\"en-US\"> your understanding between supervised and unsupervised learning by applying the correct method used for a series of application statements.<\/span><\/p>\r\n<em lang=\"en-US\" xml:lang=\"en-US\">Identify<\/em><em lang=\"en-US\" xml:lang=\"en-US\"> whether the data mining statement below <\/em><em lang=\"en-US\" xml:lang=\"en-US\">represents<\/em><em lang=\"en-US\" xml:lang=\"en-US\"> supervised or unsupervised learning.<\/em>\r\n\r\n[h5p id=\"1\"]\r\n<h2 class=\"import-Normal\"><span lang=\"en-US\" xml:lang=\"en-US\">Review Activity #7 Types of Databases<\/span><\/h2>\r\n<p class=\"import-Normal\"><span lang=\"en-US\" xml:lang=\"en-US\">Have you ever considered how big data is organized to create smart data that <\/span><span lang=\"en-US\" xml:lang=\"en-US\">provides<\/span><span lang=\"en-US\" xml:lang=\"en-US\"> value? All data is stored and organized in a database. A database <\/span><span lang=\"en-US\" xml:lang=\"en-US\">contains<\/span><span lang=\"en-US\" xml:lang=\"en-US\"> current data from company operations. The data must be organized for efficient retrieval and analysis by different functional departments throughout the company. Most companies store data in both relational and non-relational type databases.<\/span><\/p>\r\n<p class=\"import-Normal\"><span lang=\"en-US\" xml:lang=\"en-US\">The goal of this activity is to <\/span><span lang=\"en-US\" xml:lang=\"en-US\">demonstrate<\/span><span lang=\"en-US\" xml:lang=\"en-US\"> your understanding of relational and non-relational databases.<\/span><\/p>\r\n<p class=\"import-Normal\"><em lang=\"en-US\" xml:lang=\"en-US\">Select the correct <\/em><em lang=\"en-US\" xml:lang=\"en-US\">option<\/em><em lang=\"en-US\" xml:lang=\"en-US\"> that <\/em><em lang=\"en-US\" xml:lang=\"en-US\">represents<\/em><em lang=\"en-US\" xml:lang=\"en-US\"> whether the table is relational or non-relational.<\/em><\/p>\r\n<p class=\"import-Normal\"><strong lang=\"en-US\" xml:lang=\"en-US\">Table 1<\/strong><\/p>\r\n\r\n<table>\r\n<tbody>\r\n<tr class=\"TableNormal-R\">\r\n<td class=\"TableNormal-C\" style=\"padding: 0 0 0 0;\">\r\n<p class=\"import-Normal\">{\u201cName\u201d: \u201cAverage Sales Price: 1.47\u201d},<\/p>\r\n<\/td>\r\n<\/tr>\r\n<tr class=\"TableNormal-R\">\r\n<td class=\"TableNormal-C\" style=\"padding: 0 0 0 0;\">\r\n<p class=\"import-Normal\">{\u201cName\u201d: \u201cTotal Volume: 113514.4\u201d},<\/p>\r\n<\/td>\r\n<\/tr>\r\n<tr class=\"TableNormal-R\">\r\n<td class=\"TableNormal-C\" style=\"padding: 0 0 0 0;\">\r\n<p class=\"import-Normal\">{\u201cName\u201d: \u201cType: organic\u201d},<\/p>\r\n<\/td>\r\n<\/tr>\r\n<tr class=\"TableNormal-R\">\r\n<td class=\"TableNormal-C\" style=\"padding: 0 0 0 0;\">\r\n<p class=\"import-Normal\">{\u201cName\u201d: \u201cRegion: Albany\u201d}<\/p>\r\n<\/td>\r\n<\/tr>\r\n<tr>\r\n<td><\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n<p class=\"import-Normal\">[h5p id=\"2\"]<\/p>\r\n<p class=\"import-Normal\"><strong lang=\"en-US\" xml:lang=\"en-US\">Table 2<\/strong><\/p>\r\n\r\n<table>\r\n<tbody>\r\n<tr class=\"TableNormal-R\">\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 143.188px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">Observation ID<\/p>\r\n<\/td>\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 200.188px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">Region<\/p>\r\n<\/td>\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 94.1875px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">Year<\/p>\r\n<\/td>\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 55.4453px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">Month<\/p>\r\n<\/td>\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 83.1875px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">Quarter<\/p>\r\n<\/td>\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 83.1875px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">Type<\/p>\r\n<\/td>\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 130.188px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">Average Price<\/p>\r\n<\/td>\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 126.188px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">Total Volume<\/p>\r\n<\/td>\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 111.188px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">Supplier ID<\/p>\r\n<\/td>\r\n<\/tr>\r\n<tr class=\"TableNormal-R\">\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 143.188px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">17038<\/p>\r\n<\/td>\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 200.188px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">Miami\/Ft. Lauderdale<\/p>\r\n<\/td>\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 94.1875px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">2016<\/p>\r\n<\/td>\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 55.4453px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">10<\/p>\r\n<\/td>\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 83.1875px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">4<\/p>\r\n<\/td>\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 83.1875px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">Organic<\/p>\r\n<\/td>\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 130.188px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">1.58<\/p>\r\n<\/td>\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 126.188px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">385.55<\/p>\r\n<\/td>\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 111.188px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">A<\/p>\r\n<\/td>\r\n<\/tr>\r\n<tr class=\"TableNormal-R\">\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 143.188px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">6381<\/p>\r\n<\/td>\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 200.188px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">Jacksonville<\/p>\r\n<\/td>\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 94.1875px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">2018<\/p>\r\n<\/td>\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 55.4453px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">11<\/p>\r\n<\/td>\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 83.1875px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">4<\/p>\r\n<\/td>\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 83.1875px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">Organic<\/p>\r\n<\/td>\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 130.188px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">1.65<\/p>\r\n<\/td>\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 126.188px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">404.62<\/p>\r\n<\/td>\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 111.188px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">C<\/p>\r\n<\/td>\r\n<\/tr>\r\n<tr class=\"TableNormal-R\">\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 143.188px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">6392<\/p>\r\n<\/td>\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 200.188px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">Orlando<\/p>\r\n<\/td>\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 94.1875px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">2018<\/p>\r\n<\/td>\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 55.4453px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">11<\/p>\r\n<\/td>\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 83.1875px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">4<\/p>\r\n<\/td>\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 83.1875px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">Organic<\/p>\r\n<\/td>\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 130.188px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">1.39<\/p>\r\n<\/td>\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 126.188px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">405.29<\/p>\r\n<\/td>\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 111.188px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">C<\/p>\r\n<\/td>\r\n<\/tr>\r\n<tr class=\"TableNormal-R\">\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 143.188px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">16826<\/p>\r\n<\/td>\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 200.188px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">Miami\/Ft. Lauderdale<\/p>\r\n<\/td>\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 94.1875px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">2016<\/p>\r\n<\/td>\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 55.4453px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">10<\/p>\r\n<\/td>\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 83.1875px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">4<\/p>\r\n<\/td>\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 83.1875px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">Organic<\/p>\r\n<\/td>\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 130.188px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">1.49<\/p>\r\n<\/td>\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 126.188px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">472.82<\/p>\r\n<\/td>\r\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 111.188px;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\">A<\/p>\r\n<\/td>\r\n<\/tr>\r\n<tr>\r\n<td style=\"width: 127px;\"><\/td>\r\n<td style=\"width: 184px;\"><\/td>\r\n<td style=\"width: 78px;\"><\/td>\r\n<td style=\"width: 39.2578px;\"><\/td>\r\n<td style=\"width: 67px;\"><\/td>\r\n<td style=\"width: 67px;\"><\/td>\r\n<td style=\"width: 114px;\"><\/td>\r\n<td style=\"width: 110px;\"><\/td>\r\n<td style=\"width: 95px;\"><\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n[h5p id=\"3\"]\r\n<h2 class=\"import-Normal\"><span lang=\"en-US\" xml:lang=\"en-US\">Review Activity #8 Data Quality<\/span><\/h2>\r\n<p class=\"import-Normal\"><span lang=\"en-US\" xml:lang=\"en-US\">There is a common adage that people use when referring to deficient data quality: \u201cgarbage in, garbage out.\u201d If the database <\/span><span lang=\"en-US\" xml:lang=\"en-US\">contains<\/span><span lang=\"en-US\" xml:lang=\"en-US\"> subpar-quality data, results or decisions emanating from that data will also be of <\/span><span lang=\"en-US\" xml:lang=\"en-US\">subpar<\/span> <span lang=\"en-US\" xml:lang=\"en-US\">quality<\/span><span lang=\"en-US\" xml:lang=\"en-US\">. Inaccurate data, missing fields, or data isolated from disparate sources can result in underperforming employees and dissatisfied customers. Furthermore, when data are of <\/span><span lang=\"en-US\" xml:lang=\"en-US\">subpar<\/span> <span lang=\"en-US\" xml:lang=\"en-US\">quality<\/span><span lang=\"en-US\" xml:lang=\"en-US\">, insights produced by marketing analytics will be unreliable. Although data quality can be measured by <\/span><span lang=\"en-US\" xml:lang=\"en-US\">numerous<\/span><span lang=\"en-US\" xml:lang=\"en-US\"> dimensions, the most common are timeliness, completeness, accuracy, consistency, and format.<\/span><\/p>\r\n<p class=\"import-Normal\"><span lang=\"en-US\" xml:lang=\"en-US\">The goal of this activity is to <\/span><span lang=\"en-US\" xml:lang=\"en-US\">demonstrate<\/span><span lang=\"en-US\" xml:lang=\"en-US\"> your understanding of <\/span><span lang=\"en-US\" xml:lang=\"en-US\">data<\/span><span lang=\"en-US\" xml:lang=\"en-US\"> quality issues to consider when evaluating your dataset.<\/span><\/p>\r\n<p class=\"import-Normal\"><em lang=\"en-US\" xml:lang=\"en-US\">Match the definitions with the correct term.<\/em><\/p>\r\n<p class=\"import-Normal\" style=\"text-align: left;\">[h5p id=\"4\"]<\/p>\r\n\r\n<h2 class=\"import-Normal\" style=\"text-align: left;\"><span lang=\"en-US\" xml:lang=\"en-US\">Review Activity #9 Data Understanding<\/span><\/h2>\r\n<p class=\"import-Normal\" style=\"text-align: left;\"><span lang=\"en-US\" xml:lang=\"en-US\">There are many <\/span><span lang=\"en-US\" xml:lang=\"en-US\">different sources<\/span><span lang=\"en-US\" xml:lang=\"en-US\"> of data within an organization. The marketing analyst's first job is to <\/span><span lang=\"en-US\" xml:lang=\"en-US\">identify<\/span><span lang=\"en-US\" xml:lang=\"en-US\"> where the data is stored, its format, and how it can be combined to understand the question at hand. Once a better understanding of the problem is <\/span><span lang=\"en-US\" xml:lang=\"en-US\">established<\/span><span lang=\"en-US\" xml:lang=\"en-US\">, the analyst typically samples data from the selected databases to obtain records for the analysis. Marketing analysts must have a good understanding of the types and sources of data.<\/span><\/p>\r\n<p class=\"import-Normal\" style=\"text-align: left;\"><span lang=\"en-US\" xml:lang=\"en-US\">The goal of this activity is to demonstrate your understanding of questions that can be asked after evaluating available data for analysis.<\/span><\/p>\r\n<p class=\"import-Normal\" style=\"text-align: left;\"><em lang=\"en-US\" xml:lang=\"en-US\">Evaluate the data fields available that you could use to conduct marketing analytics. After reviewing the data, select the questions you can ask to better understand computer sales.<\/em><\/p>\r\n\r\n<table>\r\n<thead>\r\n<tr style=\"height: 15.75pt;\">\r\n<td class=\"TableGrid-C\" style=\"background-color: #d9e2f3; padding: 0px; border: 1pt solid windowtext; text-align: center;\">\r\n<p class=\"import-Normal\" style=\"text-align: left;\"><strong>Variable Name<\/strong><\/p>\r\n<\/td>\r\n<td class=\"TableGrid-C\" style=\"background-color: #d9e2f3; padding: 0px; border: 1pt solid windowtext; text-align: center;\">\r\n<p class=\"import-Normal\" style=\"text-align: center;\"><strong>Description<\/strong><\/p>\r\n<\/td>\r\n<\/tr>\r\n<\/thead>\r\n<tbody>\r\n<tr class=\"TableGrid-R\" style=\"height: 52.5pt;\">\r\n<td class=\"TableGrid-C\" style=\"background-color: #ffffff; padding: 0 0 0 0; border: solid windowtext 1pt;\">\r\n<p class=\"import-Normal\" style=\"text-align: left;\">Observation<\/p>\r\n<\/td>\r\n<td class=\"TableGrid-C\" style=\"background-color: #ffffff; padding: 0 0 0 0; border: solid windowtext 1pt;\">\r\n<p class=\"import-Normal\" style=\"text-align: left;\">A unique identifier for each observation. This is a <em>primary key<\/em> that is located across multiple computer datasets. A primary key can guide the integration of data from one table to the data of another table, such as in the case of observationid.<\/p>\r\n<\/td>\r\n<\/tr>\r\n<tr class=\"TableGrid-R\" style=\"height: 15.75pt;\">\r\n<td class=\"TableGrid-C\" style=\"background-color: #ffffff; padding: 0 0 0 0; border: solid windowtext 1pt;\">\r\n<p class=\"import-Normal\" style=\"text-align: left;\">Region<\/p>\r\n<\/td>\r\n<td class=\"TableGrid-C\" style=\"background-color: #ffffff; padding: 0 0 0 0; border: solid windowtext 1pt;\">\r\n<p class=\"import-Normal\" style=\"text-align: left;\">The sales geographic location<\/p>\r\n<\/td>\r\n<\/tr>\r\n<tr class=\"TableGrid-R\" style=\"height: 15.75pt;\">\r\n<td class=\"TableGrid-C\" style=\"background-color: #ffffff; padding: 0 0 0 0; border: solid windowtext 1pt;\">\r\n<p class=\"import-Normal\" style=\"text-align: left;\">Year<\/p>\r\n<\/td>\r\n<td class=\"TableGrid-C\" style=\"background-color: #ffffff; padding: 0 0 0 0; border: solid windowtext 1pt;\">\r\n<p class=\"import-Normal\" style=\"text-align: left;\">The year of the observation<\/p>\r\n<\/td>\r\n<\/tr>\r\n<tr class=\"TableGrid-R\" style=\"height: 15.75pt;\">\r\n<td class=\"TableGrid-C\" style=\"background-color: #ffffff; padding: 0 0 0 0; border: solid windowtext 1pt;\">\r\n<p class=\"import-Normal\" style=\"text-align: left;\">Month<\/p>\r\n<\/td>\r\n<td class=\"TableGrid-C\" style=\"background-color: #ffffff; padding: 0 0 0 0; border: solid windowtext 1pt;\">\r\n<p class=\"import-Normal\" style=\"text-align: left;\">The month of the observation<\/p>\r\n<\/td>\r\n<\/tr>\r\n<tr class=\"TableGrid-R\" style=\"height: 15.75pt;\">\r\n<td class=\"TableGrid-C\" style=\"background-color: #ffffff; padding: 0 0 0 0; border: solid windowtext 1pt;\">\r\n<p class=\"import-Normal\" style=\"text-align: left;\">Quarter<\/p>\r\n<\/td>\r\n<td class=\"TableGrid-C\" style=\"background-color: #ffffff; padding: 0 0 0 0; border: solid windowtext 1pt;\">\r\n<p class=\"import-Normal\" style=\"text-align: left;\">The quarter of the observation<\/p>\r\n<\/td>\r\n<\/tr>\r\n<tr class=\"TableGrid-R\" style=\"height: 15.75pt;\">\r\n<td class=\"TableGrid-C\" style=\"background-color: #ffffff; padding: 0 0 0 0; border: solid windowtext 1pt;\">\r\n<p class=\"import-Normal\" style=\"text-align: left;\">Type<\/p>\r\n<\/td>\r\n<td class=\"TableGrid-C\" style=\"background-color: #ffffff; padding: 0 0 0 0; border: solid windowtext 1pt;\">\r\n<p class=\"import-Normal\" style=\"text-align: left;\">Conventional or organic<\/p>\r\n<\/td>\r\n<\/tr>\r\n<tr class=\"TableGrid-R\" style=\"height: 15.75pt;\">\r\n<td class=\"TableGrid-C\" style=\"background-color: #ffffff; padding: 0 0 0 0; border: solid windowtext 1pt;\">\r\n<p class=\"import-Normal\" style=\"text-align: left;\">Average Price<\/p>\r\n<\/td>\r\n<td class=\"TableGrid-C\" style=\"background-color: #ffffff; padding: 0 0 0 0; border: solid windowtext 1pt;\">\r\n<p class=\"import-Normal\" style=\"text-align: left;\">The average price of a single computer<\/p>\r\n<\/td>\r\n<\/tr>\r\n<tr class=\"TableGrid-R\" style=\"height: 17.25pt;\">\r\n<td class=\"TableGrid-C\" style=\"background-color: #ffffff; padding: 0 0 0 0; border: solid windowtext 1pt;\">\r\n<p class=\"import-Normal\" style=\"text-align: left;\">Total Volume<\/p>\r\n<\/td>\r\n<td class=\"TableGrid-C\" style=\"background-color: #ffffff; padding: 0 0 0 0; border: solid windowtext 1pt;\">\r\n<p class=\"import-Normal\" style=\"text-align: left;\">Total number of computers sold<\/p>\r\n<\/td>\r\n<\/tr>\r\n<tr class=\"TableGrid-R\" style=\"height: 18pt;\">\r\n<td class=\"TableGrid-C\" style=\"background-color: #ffffff; padding: 0 0 0 0; border: solid windowtext 1pt;\">\r\n<p class=\"import-Normal\" style=\"text-align: left;\">Supplier ID<\/p>\r\n<\/td>\r\n<td class=\"TableGrid-C\" style=\"background-color: #ffffff; padding: 0 0 0 0; border: solid windowtext 1pt;\">\r\n<p class=\"import-Normal\" style=\"text-align: left;\">A unique identifier indicating the supplier of the computer.<\/p>\r\n<\/td>\r\n<\/tr>\r\n<tr>\r\n<td><\/td>\r\n<td><\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n<p class=\"import-Normal\" style=\"text-align: left;\"><span lang=\"en-US\" xml:lang=\"en-US\">For each question below <\/span><span lang=\"en-US\" xml:lang=\"en-US\">determine<\/span><span lang=\"en-US\" xml:lang=\"en-US\"> if: <\/span><span lang=\"en-US\" xml:lang=\"en-US\">yes,<\/span><span lang=\"en-US\" xml:lang=\"en-US\"> it can be answered with this data or no, it <\/span><span lang=\"en-US\" xml:lang=\"en-US\">cannot<\/span><span lang=\"en-US\" xml:lang=\"en-US\"> be answered with this data.<\/span><\/p>\r\n[h5p id=\"5\"]\r\n<h2 class=\"import-Normal\" style=\"text-align: left; margin-left: 0pt; margin-right: 0pt;\"><span lang=\"en-US\" xml:lang=\"en-US\">Review Activity #10<\/span><\/h2>\r\n<p class=\"import-Normal\" style=\"text-align: left;\"><span lang=\"en-US\" xml:lang=\"en-US\">Type a 1-page memo providing examples and the why behind these questions.<\/span><\/p>\r\n\r\n<ul>\r\n \t<li><span lang=\"en-US\" xml:lang=\"en-US\">Congratulations, you were just hired as a marketing analyst for a large company. The VP of marketing has asked you to examine how the company might improve sales. <\/span><\/li>\r\n \t<li><span lang=\"en-US\" xml:lang=\"en-US\">What data might be helpful in the exploration? <\/span><\/li>\r\n \t<li><span lang=\"en-US\" xml:lang=\"en-US\">What might you locate the data needed? <\/span><\/li>\r\n \t<li><span lang=\"en-US\" xml:lang=\"en-US\">What questions should you ask first?<\/span><\/li>\r\n<\/ul>\r\n<p class=\"import-Normal\" style=\"text-align: left;\"><\/p>\r\n\r\n<\/div>","rendered":"<div class=\"overview:\">\n<p><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-64\" src=\"https:\/\/pressbooks.ccconline.org\/accmarketinganalytics\/wp-content\/uploads\/sites\/105\/2022\/12\/Picture6-300x93.jpg\" alt=\"High school teacher calling on student in classroom\" width=\"1055\" height=\"327\" srcset=\"https:\/\/pressbooks.ccconline.org\/accmarketinganalytics2\/wp-content\/uploads\/sites\/105\/2022\/12\/Picture6-300x93.jpg 300w, https:\/\/pressbooks.ccconline.org\/accmarketinganalytics2\/wp-content\/uploads\/sites\/105\/2022\/12\/Picture6-65x20.jpg 65w, https:\/\/pressbooks.ccconline.org\/accmarketinganalytics2\/wp-content\/uploads\/sites\/105\/2022\/12\/Picture6-225x70.jpg 225w, https:\/\/pressbooks.ccconline.org\/accmarketinganalytics2\/wp-content\/uploads\/sites\/105\/2022\/12\/Picture6-350x108.jpg 350w, https:\/\/pressbooks.ccconline.org\/accmarketinganalytics2\/wp-content\/uploads\/sites\/105\/2022\/12\/Picture6.jpg 620w\" sizes=\"auto, (max-width: 1055px) 100vw, 1055px\" \/><\/p>\n<h1>Overview:<\/h1>\n<div class=\"textbox textbox--learning-objectives\">\n<header class=\"textbox__header\">\n<p class=\"textbox__title\">In this module we review the Module 1\u00a0 fundamentals of marketing analytics and data management while focusing on addressing the following:<\/p>\n<\/header>\n<div class=\"textbox__content\">\n<ul>\n<li>What is meant by marketing analytics in a digital marketing context?<\/li>\n<li>How to apply principles of marketing analytics to identify the right business problem.<\/li>\n<li>Identify types of data sources<\/li>\n<li>Explain several types of data<\/li>\n<li>Define data measurement types and give examples.<\/li>\n<li>Understand the difference between predictors and target variables.<\/li>\n<li>Compare and contrast supervised and unsupervised modeling.<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<p class=\"import-Normal\">Read \u201cModule 1: Readings and Videos Part II\u201d document before completing the following activities.<\/p>\n<h2>Review Activity #1 Datasets<\/h2>\n<p class=\"import-Normal\">Visit <a class=\"rId5\" href=\"http:\/\/www.data.gov\"><span class=\"import-Hyperlink\">www.data.gov<\/span><\/a> and then click on \u201cData\u201d and complete the following:<\/p>\n<ul>\n<li>How many datasets are currently located on the website for free?<\/li>\n<li>Select one dataset and develop a scenario where the data might be helpful for a marketing manager.<\/li>\n<li>Discuss how exploring the data could guide the marketing manager in making more informed decisions?<\/li>\n<\/ul>\n<h2>Review Activity #2<\/h2>\n<p class=\"import-Normal\">After watching the video on the marketing funnel explained, do a quick outline of a brand of your choice and go through each of the steps and then explain which part\/step of the funnel could be improved and why.<\/p>\n<h2>Review Activity #3<\/h2>\n<p class=\"import-Normal\">Define the following sources of secondary data and provide at least two examples of each and explain why these sources are important: Public datasets, online sites, mobile data, and channel partners.<\/p>\n<h2>Review Activity #4<\/h2>\n<p>Produce three questions like the example in the readings and videos document of \u201cDoes the economy impact college enrollment numbers?\u201d Then for each of the three questions identify what the independent and dependent\/target and outcome variables are.<\/p>\n<h2>Review Activity #5<\/h2>\n<p class=\"import-Normal\">Develop two questions that an airline company might be interested in answering. Describe types of unstructured and structured data that might be important to answering the questions. What data sources might be useful?<\/p>\n<h2 class=\"import-Normal\">Review Activity #6 Supervised vs. Unsupervised Learning<\/h2>\n<p class=\"import-Normal\"><span lang=\"en-US\" xml:lang=\"en-US\">This activity is important because depending on the nature of the business problem being addressed, <\/span><span lang=\"en-US\" xml:lang=\"en-US\">several types<\/span><span lang=\"en-US\" xml:lang=\"en-US\"> of algorithms can be used. This activity focuses on two models: supervised learning and unsupervised learning.<\/span><\/p>\n<p class=\"import-Normal\"><span lang=\"en-US\" xml:lang=\"en-US\">The goal of this activity is to <\/span><span lang=\"en-US\" xml:lang=\"en-US\">demonstrate<\/span><span lang=\"en-US\" xml:lang=\"en-US\"> your understanding between supervised and unsupervised learning by applying the correct method used for a series of application statements.<\/span><\/p>\n<p><em lang=\"en-US\" xml:lang=\"en-US\">Identify<\/em><em lang=\"en-US\" xml:lang=\"en-US\"> whether the data mining statement below <\/em><em lang=\"en-US\" xml:lang=\"en-US\">represents<\/em><em lang=\"en-US\" xml:lang=\"en-US\"> supervised or unsupervised learning.<\/em><\/p>\n<div id=\"h5p-1\">\n<div class=\"h5p-iframe-wrapper\"><iframe id=\"h5p-iframe-1\" class=\"h5p-iframe\" data-content-id=\"1\" style=\"height:1px\" src=\"about:blank\" frameBorder=\"0\" scrolling=\"no\" title=\"Module 1.1 Interactive\"><\/iframe><\/div>\n<\/div>\n<h2 class=\"import-Normal\"><span lang=\"en-US\" xml:lang=\"en-US\">Review Activity #7 Types of Databases<\/span><\/h2>\n<p class=\"import-Normal\"><span lang=\"en-US\" xml:lang=\"en-US\">Have you ever considered how big data is organized to create smart data that <\/span><span lang=\"en-US\" xml:lang=\"en-US\">provides<\/span><span lang=\"en-US\" xml:lang=\"en-US\"> value? All data is stored and organized in a database. A database <\/span><span lang=\"en-US\" xml:lang=\"en-US\">contains<\/span><span lang=\"en-US\" xml:lang=\"en-US\"> current data from company operations. The data must be organized for efficient retrieval and analysis by different functional departments throughout the company. Most companies store data in both relational and non-relational type databases.<\/span><\/p>\n<p class=\"import-Normal\"><span lang=\"en-US\" xml:lang=\"en-US\">The goal of this activity is to <\/span><span lang=\"en-US\" xml:lang=\"en-US\">demonstrate<\/span><span lang=\"en-US\" xml:lang=\"en-US\"> your understanding of relational and non-relational databases.<\/span><\/p>\n<p class=\"import-Normal\"><em lang=\"en-US\" xml:lang=\"en-US\">Select the correct <\/em><em lang=\"en-US\" xml:lang=\"en-US\">option<\/em><em lang=\"en-US\" xml:lang=\"en-US\"> that <\/em><em lang=\"en-US\" xml:lang=\"en-US\">represents<\/em><em lang=\"en-US\" xml:lang=\"en-US\"> whether the table is relational or non-relational.<\/em><\/p>\n<p class=\"import-Normal\"><strong lang=\"en-US\" xml:lang=\"en-US\">Table 1<\/strong><\/p>\n<table>\n<tbody>\n<tr class=\"TableNormal-R\">\n<td class=\"TableNormal-C\" style=\"padding: 0 0 0 0;\">\n<p class=\"import-Normal\">{\u201cName\u201d: \u201cAverage Sales Price: 1.47\u201d},<\/p>\n<\/td>\n<\/tr>\n<tr class=\"TableNormal-R\">\n<td class=\"TableNormal-C\" style=\"padding: 0 0 0 0;\">\n<p class=\"import-Normal\">{\u201cName\u201d: \u201cTotal Volume: 113514.4\u201d},<\/p>\n<\/td>\n<\/tr>\n<tr class=\"TableNormal-R\">\n<td class=\"TableNormal-C\" style=\"padding: 0 0 0 0;\">\n<p class=\"import-Normal\">{\u201cName\u201d: \u201cType: organic\u201d},<\/p>\n<\/td>\n<\/tr>\n<tr class=\"TableNormal-R\">\n<td class=\"TableNormal-C\" style=\"padding: 0 0 0 0;\">\n<p class=\"import-Normal\">{\u201cName\u201d: \u201cRegion: Albany\u201d}<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p class=\"import-Normal\">\n<div id=\"h5p-2\">\n<div class=\"h5p-iframe-wrapper\"><iframe id=\"h5p-iframe-2\" class=\"h5p-iframe\" data-content-id=\"2\" style=\"height:1px\" src=\"about:blank\" frameBorder=\"0\" scrolling=\"no\" title=\"Module 1.2 Interactive\"><\/iframe><\/div>\n<\/div>\n<p class=\"import-Normal\"><strong lang=\"en-US\" xml:lang=\"en-US\">Table 2<\/strong><\/p>\n<table>\n<tbody>\n<tr class=\"TableNormal-R\">\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 143.188px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">Observation ID<\/p>\n<\/td>\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 200.188px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">Region<\/p>\n<\/td>\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 94.1875px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">Year<\/p>\n<\/td>\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 55.4453px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">Month<\/p>\n<\/td>\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 83.1875px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">Quarter<\/p>\n<\/td>\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 83.1875px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">Type<\/p>\n<\/td>\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 130.188px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">Average Price<\/p>\n<\/td>\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 126.188px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">Total Volume<\/p>\n<\/td>\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 111.188px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">Supplier ID<\/p>\n<\/td>\n<\/tr>\n<tr class=\"TableNormal-R\">\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 143.188px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">17038<\/p>\n<\/td>\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 200.188px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">Miami\/Ft. Lauderdale<\/p>\n<\/td>\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 94.1875px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">2016<\/p>\n<\/td>\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 55.4453px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">10<\/p>\n<\/td>\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 83.1875px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">4<\/p>\n<\/td>\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 83.1875px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">Organic<\/p>\n<\/td>\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 130.188px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">1.58<\/p>\n<\/td>\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 126.188px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">385.55<\/p>\n<\/td>\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 111.188px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">A<\/p>\n<\/td>\n<\/tr>\n<tr class=\"TableNormal-R\">\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 143.188px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">6381<\/p>\n<\/td>\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 200.188px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">Jacksonville<\/p>\n<\/td>\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 94.1875px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">2018<\/p>\n<\/td>\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 55.4453px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">11<\/p>\n<\/td>\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 83.1875px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">4<\/p>\n<\/td>\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 83.1875px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">Organic<\/p>\n<\/td>\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 130.188px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">1.65<\/p>\n<\/td>\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 126.188px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">404.62<\/p>\n<\/td>\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 111.188px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">C<\/p>\n<\/td>\n<\/tr>\n<tr class=\"TableNormal-R\">\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 143.188px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">6392<\/p>\n<\/td>\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 200.188px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">Orlando<\/p>\n<\/td>\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 94.1875px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">2018<\/p>\n<\/td>\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 55.4453px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">11<\/p>\n<\/td>\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 83.1875px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">4<\/p>\n<\/td>\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 83.1875px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">Organic<\/p>\n<\/td>\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 130.188px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">1.39<\/p>\n<\/td>\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 126.188px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">405.29<\/p>\n<\/td>\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 111.188px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">C<\/p>\n<\/td>\n<\/tr>\n<tr class=\"TableNormal-R\">\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 143.188px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">16826<\/p>\n<\/td>\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 200.188px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">Miami\/Ft. Lauderdale<\/p>\n<\/td>\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 94.1875px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">2016<\/p>\n<\/td>\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 55.4453px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">10<\/p>\n<\/td>\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 83.1875px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">4<\/p>\n<\/td>\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 83.1875px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">Organic<\/p>\n<\/td>\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 130.188px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">1.49<\/p>\n<\/td>\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 126.188px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">472.82<\/p>\n<\/td>\n<td class=\"TableNormal-C\" style=\"padding: 0px; width: 111.188px;\">\n<p class=\"import-Normal\" style=\"text-align: center;\">A<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td style=\"width: 127px;\"><\/td>\n<td style=\"width: 184px;\"><\/td>\n<td style=\"width: 78px;\"><\/td>\n<td style=\"width: 39.2578px;\"><\/td>\n<td style=\"width: 67px;\"><\/td>\n<td style=\"width: 67px;\"><\/td>\n<td style=\"width: 114px;\"><\/td>\n<td style=\"width: 110px;\"><\/td>\n<td style=\"width: 95px;\"><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<div id=\"h5p-3\">\n<div class=\"h5p-iframe-wrapper\"><iframe id=\"h5p-iframe-3\" class=\"h5p-iframe\" data-content-id=\"3\" style=\"height:1px\" src=\"about:blank\" frameBorder=\"0\" scrolling=\"no\" title=\"Module 1.3 Interactive\"><\/iframe><\/div>\n<\/div>\n<h2 class=\"import-Normal\"><span lang=\"en-US\" xml:lang=\"en-US\">Review Activity #8 Data Quality<\/span><\/h2>\n<p class=\"import-Normal\"><span lang=\"en-US\" xml:lang=\"en-US\">There is a common adage that people use when referring to deficient data quality: \u201cgarbage in, garbage out.\u201d If the database <\/span><span lang=\"en-US\" xml:lang=\"en-US\">contains<\/span><span lang=\"en-US\" xml:lang=\"en-US\"> subpar-quality data, results or decisions emanating from that data will also be of <\/span><span lang=\"en-US\" xml:lang=\"en-US\">subpar<\/span> <span lang=\"en-US\" xml:lang=\"en-US\">quality<\/span><span lang=\"en-US\" xml:lang=\"en-US\">. Inaccurate data, missing fields, or data isolated from disparate sources can result in underperforming employees and dissatisfied customers. Furthermore, when data are of <\/span><span lang=\"en-US\" xml:lang=\"en-US\">subpar<\/span> <span lang=\"en-US\" xml:lang=\"en-US\">quality<\/span><span lang=\"en-US\" xml:lang=\"en-US\">, insights produced by marketing analytics will be unreliable. Although data quality can be measured by <\/span><span lang=\"en-US\" xml:lang=\"en-US\">numerous<\/span><span lang=\"en-US\" xml:lang=\"en-US\"> dimensions, the most common are timeliness, completeness, accuracy, consistency, and format.<\/span><\/p>\n<p class=\"import-Normal\"><span lang=\"en-US\" xml:lang=\"en-US\">The goal of this activity is to <\/span><span lang=\"en-US\" xml:lang=\"en-US\">demonstrate<\/span><span lang=\"en-US\" xml:lang=\"en-US\"> your understanding of <\/span><span lang=\"en-US\" xml:lang=\"en-US\">data<\/span><span lang=\"en-US\" xml:lang=\"en-US\"> quality issues to consider when evaluating your dataset.<\/span><\/p>\n<p class=\"import-Normal\"><em lang=\"en-US\" xml:lang=\"en-US\">Match the definitions with the correct term.<\/em><\/p>\n<p class=\"import-Normal\" style=\"text-align: left;\">\n<div id=\"h5p-4\">\n<div class=\"h5p-iframe-wrapper\"><iframe id=\"h5p-iframe-4\" class=\"h5p-iframe\" data-content-id=\"4\" style=\"height:1px\" src=\"about:blank\" frameBorder=\"0\" scrolling=\"no\" title=\"Module 1.4 Interactive\"><\/iframe><\/div>\n<\/div>\n<h2 class=\"import-Normal\" style=\"text-align: left;\"><span lang=\"en-US\" xml:lang=\"en-US\">Review Activity #9 Data Understanding<\/span><\/h2>\n<p class=\"import-Normal\" style=\"text-align: left;\"><span lang=\"en-US\" xml:lang=\"en-US\">There are many <\/span><span lang=\"en-US\" xml:lang=\"en-US\">different sources<\/span><span lang=\"en-US\" xml:lang=\"en-US\"> of data within an organization. The marketing analyst&#8217;s first job is to <\/span><span lang=\"en-US\" xml:lang=\"en-US\">identify<\/span><span lang=\"en-US\" xml:lang=\"en-US\"> where the data is stored, its format, and how it can be combined to understand the question at hand. Once a better understanding of the problem is <\/span><span lang=\"en-US\" xml:lang=\"en-US\">established<\/span><span lang=\"en-US\" xml:lang=\"en-US\">, the analyst typically samples data from the selected databases to obtain records for the analysis. Marketing analysts must have a good understanding of the types and sources of data.<\/span><\/p>\n<p class=\"import-Normal\" style=\"text-align: left;\"><span lang=\"en-US\" xml:lang=\"en-US\">The goal of this activity is to demonstrate your understanding of questions that can be asked after evaluating available data for analysis.<\/span><\/p>\n<p class=\"import-Normal\" style=\"text-align: left;\"><em lang=\"en-US\" xml:lang=\"en-US\">Evaluate the data fields available that you could use to conduct marketing analytics. After reviewing the data, select the questions you can ask to better understand computer sales.<\/em><\/p>\n<table>\n<thead>\n<tr style=\"height: 15.75pt;\">\n<td class=\"TableGrid-C\" style=\"background-color: #d9e2f3; padding: 0px; border: 1pt solid windowtext; text-align: center;\">\n<p class=\"import-Normal\" style=\"text-align: left;\"><strong>Variable Name<\/strong><\/p>\n<\/td>\n<td class=\"TableGrid-C\" style=\"background-color: #d9e2f3; padding: 0px; border: 1pt solid windowtext; text-align: center;\">\n<p class=\"import-Normal\" style=\"text-align: center;\"><strong>Description<\/strong><\/p>\n<\/td>\n<\/tr>\n<\/thead>\n<tbody>\n<tr class=\"TableGrid-R\" style=\"height: 52.5pt;\">\n<td class=\"TableGrid-C\" style=\"background-color: #ffffff; padding: 0 0 0 0; border: solid windowtext 1pt;\">\n<p class=\"import-Normal\" style=\"text-align: left;\">Observation<\/p>\n<\/td>\n<td class=\"TableGrid-C\" style=\"background-color: #ffffff; padding: 0 0 0 0; border: solid windowtext 1pt;\">\n<p class=\"import-Normal\" style=\"text-align: left;\">A unique identifier for each observation. This is a <em>primary key<\/em> that is located across multiple computer datasets. A primary key can guide the integration of data from one table to the data of another table, such as in the case of observationid.<\/p>\n<\/td>\n<\/tr>\n<tr class=\"TableGrid-R\" style=\"height: 15.75pt;\">\n<td class=\"TableGrid-C\" style=\"background-color: #ffffff; padding: 0 0 0 0; border: solid windowtext 1pt;\">\n<p class=\"import-Normal\" style=\"text-align: left;\">Region<\/p>\n<\/td>\n<td class=\"TableGrid-C\" style=\"background-color: #ffffff; padding: 0 0 0 0; border: solid windowtext 1pt;\">\n<p class=\"import-Normal\" style=\"text-align: left;\">The sales geographic location<\/p>\n<\/td>\n<\/tr>\n<tr class=\"TableGrid-R\" style=\"height: 15.75pt;\">\n<td class=\"TableGrid-C\" style=\"background-color: #ffffff; padding: 0 0 0 0; border: solid windowtext 1pt;\">\n<p class=\"import-Normal\" style=\"text-align: left;\">Year<\/p>\n<\/td>\n<td class=\"TableGrid-C\" style=\"background-color: #ffffff; padding: 0 0 0 0; border: solid windowtext 1pt;\">\n<p class=\"import-Normal\" style=\"text-align: left;\">The year of the observation<\/p>\n<\/td>\n<\/tr>\n<tr class=\"TableGrid-R\" style=\"height: 15.75pt;\">\n<td class=\"TableGrid-C\" style=\"background-color: #ffffff; padding: 0 0 0 0; border: solid windowtext 1pt;\">\n<p class=\"import-Normal\" style=\"text-align: left;\">Month<\/p>\n<\/td>\n<td class=\"TableGrid-C\" style=\"background-color: #ffffff; padding: 0 0 0 0; border: solid windowtext 1pt;\">\n<p class=\"import-Normal\" style=\"text-align: left;\">The month of the observation<\/p>\n<\/td>\n<\/tr>\n<tr class=\"TableGrid-R\" style=\"height: 15.75pt;\">\n<td class=\"TableGrid-C\" style=\"background-color: #ffffff; padding: 0 0 0 0; border: solid windowtext 1pt;\">\n<p class=\"import-Normal\" style=\"text-align: left;\">Quarter<\/p>\n<\/td>\n<td class=\"TableGrid-C\" style=\"background-color: #ffffff; padding: 0 0 0 0; border: solid windowtext 1pt;\">\n<p class=\"import-Normal\" style=\"text-align: left;\">The quarter of the observation<\/p>\n<\/td>\n<\/tr>\n<tr class=\"TableGrid-R\" style=\"height: 15.75pt;\">\n<td class=\"TableGrid-C\" style=\"background-color: #ffffff; padding: 0 0 0 0; border: solid windowtext 1pt;\">\n<p class=\"import-Normal\" style=\"text-align: left;\">Type<\/p>\n<\/td>\n<td class=\"TableGrid-C\" style=\"background-color: #ffffff; padding: 0 0 0 0; border: solid windowtext 1pt;\">\n<p class=\"import-Normal\" style=\"text-align: left;\">Conventional or organic<\/p>\n<\/td>\n<\/tr>\n<tr class=\"TableGrid-R\" style=\"height: 15.75pt;\">\n<td class=\"TableGrid-C\" style=\"background-color: #ffffff; padding: 0 0 0 0; border: solid windowtext 1pt;\">\n<p class=\"import-Normal\" style=\"text-align: left;\">Average Price<\/p>\n<\/td>\n<td class=\"TableGrid-C\" style=\"background-color: #ffffff; padding: 0 0 0 0; border: solid windowtext 1pt;\">\n<p class=\"import-Normal\" style=\"text-align: left;\">The average price of a single computer<\/p>\n<\/td>\n<\/tr>\n<tr class=\"TableGrid-R\" style=\"height: 17.25pt;\">\n<td class=\"TableGrid-C\" style=\"background-color: #ffffff; padding: 0 0 0 0; border: solid windowtext 1pt;\">\n<p class=\"import-Normal\" style=\"text-align: left;\">Total Volume<\/p>\n<\/td>\n<td class=\"TableGrid-C\" style=\"background-color: #ffffff; padding: 0 0 0 0; border: solid windowtext 1pt;\">\n<p class=\"import-Normal\" style=\"text-align: left;\">Total number of computers sold<\/p>\n<\/td>\n<\/tr>\n<tr class=\"TableGrid-R\" style=\"height: 18pt;\">\n<td class=\"TableGrid-C\" style=\"background-color: #ffffff; padding: 0 0 0 0; border: solid windowtext 1pt;\">\n<p class=\"import-Normal\" style=\"text-align: left;\">Supplier ID<\/p>\n<\/td>\n<td class=\"TableGrid-C\" style=\"background-color: #ffffff; padding: 0 0 0 0; border: solid windowtext 1pt;\">\n<p class=\"import-Normal\" style=\"text-align: left;\">A unique identifier indicating the supplier of the computer.<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td><\/td>\n<td><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p class=\"import-Normal\" style=\"text-align: left;\"><span lang=\"en-US\" xml:lang=\"en-US\">For each question below <\/span><span lang=\"en-US\" xml:lang=\"en-US\">determine<\/span><span lang=\"en-US\" xml:lang=\"en-US\"> if: <\/span><span lang=\"en-US\" xml:lang=\"en-US\">yes,<\/span><span lang=\"en-US\" xml:lang=\"en-US\"> it can be answered with this data or no, it <\/span><span lang=\"en-US\" xml:lang=\"en-US\">cannot<\/span><span lang=\"en-US\" xml:lang=\"en-US\"> be answered with this data.<\/span><\/p>\n<div id=\"h5p-5\">\n<div class=\"h5p-iframe-wrapper\"><iframe id=\"h5p-iframe-5\" class=\"h5p-iframe\" data-content-id=\"5\" style=\"height:1px\" src=\"about:blank\" frameBorder=\"0\" scrolling=\"no\" title=\"Module 1.5 Interactive\"><\/iframe><\/div>\n<\/div>\n<h2 class=\"import-Normal\" style=\"text-align: left; margin-left: 0pt; margin-right: 0pt;\"><span lang=\"en-US\" xml:lang=\"en-US\">Review Activity #10<\/span><\/h2>\n<p class=\"import-Normal\" style=\"text-align: left;\"><span lang=\"en-US\" xml:lang=\"en-US\">Type a 1-page memo providing examples and the why behind these questions.<\/span><\/p>\n<ul>\n<li><span lang=\"en-US\" xml:lang=\"en-US\">Congratulations, you were just hired as a marketing analyst for a large company. The VP of marketing has asked you to examine how the company might improve sales. <\/span><\/li>\n<li><span lang=\"en-US\" xml:lang=\"en-US\">What data might be helpful in the exploration? <\/span><\/li>\n<li><span lang=\"en-US\" xml:lang=\"en-US\">What might you locate the data needed? <\/span><\/li>\n<li><span lang=\"en-US\" xml:lang=\"en-US\">What questions should you ask first?<\/span><\/li>\n<\/ul>\n<p class=\"import-Normal\" style=\"text-align: left;\">\n<\/div>\n","protected":false},"author":83,"menu_order":4,"template":"","meta":{"pb_show_title":"on","pb_short_title":"","pb_subtitle":"","pb_authors":[],"pb_section_license":""},"chapter-type":[],"contributor":[],"license":[],"class_list":["post-65","chapter","type-chapter","status-publish","hentry"],"part":18,"_links":{"self":[{"href":"https:\/\/pressbooks.ccconline.org\/accmarketinganalytics2\/wp-json\/pressbooks\/v2\/chapters\/65","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/pressbooks.ccconline.org\/accmarketinganalytics2\/wp-json\/pressbooks\/v2\/chapters"}],"about":[{"href":"https:\/\/pressbooks.ccconline.org\/accmarketinganalytics2\/wp-json\/wp\/v2\/types\/chapter"}],"author":[{"embeddable":true,"href":"https:\/\/pressbooks.ccconline.org\/accmarketinganalytics2\/wp-json\/wp\/v2\/users\/83"}],"version-history":[{"count":6,"href":"https:\/\/pressbooks.ccconline.org\/accmarketinganalytics2\/wp-json\/pressbooks\/v2\/chapters\/65\/revisions"}],"predecessor-version":[{"id":101,"href":"https:\/\/pressbooks.ccconline.org\/accmarketinganalytics2\/wp-json\/pressbooks\/v2\/chapters\/65\/revisions\/101"}],"part":[{"href":"https:\/\/pressbooks.ccconline.org\/accmarketinganalytics2\/wp-json\/pressbooks\/v2\/parts\/18"}],"metadata":[{"href":"https:\/\/pressbooks.ccconline.org\/accmarketinganalytics2\/wp-json\/pressbooks\/v2\/chapters\/65\/metadata\/"}],"wp:attachment":[{"href":"https:\/\/pressbooks.ccconline.org\/accmarketinganalytics2\/wp-json\/wp\/v2\/media?parent=65"}],"wp:term":[{"taxonomy":"chapter-type","embeddable":true,"href":"https:\/\/pressbooks.ccconline.org\/accmarketinganalytics2\/wp-json\/pressbooks\/v2\/chapter-type?post=65"},{"taxonomy":"contributor","embeddable":true,"href":"https:\/\/pressbooks.ccconline.org\/accmarketinganalytics2\/wp-json\/wp\/v2\/contributor?post=65"},{"taxonomy":"license","embeddable":true,"href":"https:\/\/pressbooks.ccconline.org\/accmarketinganalytics2\/wp-json\/wp\/v2\/license?post=65"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}