Details

CompTIA Data+ Study Guide


CompTIA Data+ Study Guide

Exam DA0-001
1. Aufl.

von: Mike Chapple, Sharif Nijim

38,99 €

Verlag: Wiley
Format: PDF
Veröffentl.: 18.03.2022
ISBN/EAN: 9781119845270
Sprache: englisch
Anzahl Seiten: 368

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Beschreibungen

<p><b>Build a solid foundation in data analysis skills and pursue a coveted Data+ certification with this intuitive study guide</b></p> <p><i>CompTIA Data+ Study Guide: Exam DA0-001</i> delivers easily accessible and actionable instruction for achieving data analysis competencies required for the job and on the CompTIA Data+ certification exam. You'll learn to collect, analyze, and report on various types of commonly used data, transforming raw data into usable information for stakeholders and decision makers.</p> <p>With comprehensive coverage of data concepts and environments, data mining, data analysis, visualization, and data governance, quality, and controls, this Study Guide offers:</p> <ul> <li>All the information necessary to succeed on the exam for a widely accepted, entry-level credential that unlocks lucrative new data analytics and data science career opportunities</li> <li>100% coverage of objectives for the NEW CompTIA Data+ exam</li> <li>Access to the Sybex online learning resources, with review questions, full-length practice exam, hundreds of electronic flashcards, and a glossary of key terms</li> </ul> <p>Ideal for anyone seeking a new career in data analysis, to improve their current data science skills, or hoping to achieve the coveted CompTIA Data+ certification credential, <i>CompTIA Data+ Study Guide: Exam DA0-001</i> provides an invaluable head start to beginning or accelerating a career as an in-demand data analyst.</p>
<p>Introduction xv</p> <p>Assessment Test xxii</p> <p><b>Chapter 1 Today’s Data Analyst 1</b></p> <p>Welcome to the World of Analytics 2</p> <p>Data 2</p> <p>Storage 3</p> <p>Computing Power 4</p> <p>Careers in Analytics 5</p> <p>The Analytics Process 6</p> <p>Data Acquisition 7</p> <p>Cleaning and Manipulation 7</p> <p>Analysis 8</p> <p>Visualization 8</p> <p>Reporting and Communication 8</p> <p>Analytics Techniques 10</p> <p>Descriptive Analytics 10</p> <p>Predictive Analytics 11</p> <p>Prescriptive Analytics 11</p> <p>Machine Learning, Artificial Intelligence, and Deep Learning 11</p> <p>Data Governance 13</p> <p>Analytics Tools 13</p> <p>Summary 15</p> <p><b>Chapter 2 Understanding Data 17</b></p> <p>Exploring Data Types 18</p> <p>Structured Data Types 20</p> <p>Unstructured Data Types 31</p> <p>Categories of Data 36</p> <p>Common Data Structures 39</p> <p>Structured Data 39</p> <p>Unstructured Data 41</p> <p>Semi-structured</p> <p>Data 42</p> <p>Common File Formats 42</p> <p>Text Files 42</p> <p>JavaScript Object Notation 44</p> <p>Extensible Markup Language (XML) 45</p> <p>HyperText Markup Language (HTML) 47</p> <p>Summary 48</p> <p>Exam Essentials 49</p> <p>Review Questions 51</p> <p><b>Chapter 3 Databases and Data Acquisition 57</b></p> <p>Exploring Databases 58</p> <p>The Relational Model 59</p> <p>Relational Databases 62</p> <p>Nonrelational Databases 68</p> <p>Database Use Cases 71</p> <p>Online Transactional Processing 71</p> <p>Online Analytical Processing 74</p> <p>Schema Concepts 75</p> <p>Data Acquisition Concepts 81</p> <p>Integration 81</p> <p>Data Collection Methods 83</p> <p>Working with Data 88</p> <p>Data Manipulation 89</p> <p>Query Optimization 96</p> <p>Summary 99</p> <p>Exam Essentials 100</p> <p>Review Questions 101</p> <p><b>Chapter 4 Data Quality 105</b></p> <p>Data Quality Challenges 106</p> <p>Duplicate Data 106</p> <p>Redundant Data 107</p> <p>Missing Values 110</p> <p>Invalid Data 111</p> <p>Nonparametric data 112</p> <p>Data Outliers 113</p> <p>Specification Mismatch 114</p> <p>Data Type Validation 114</p> <p>Data Manipulation Techniques 116</p> <p>Recoding Data 116</p> <p>Derived Variables 117</p> <p>Data Merge 118</p> <p>Data Blending 119</p> <p>Concatenation 121</p> <p>Data Append 121</p> <p>Imputation 122</p> <p>Reduction 124</p> <p>Aggregation 126</p> <p>Transposition 127</p> <p>Normalization 128</p> <p>Parsing/String Manipulation 130</p> <p>Managing Data Quality 132</p> <p>Circumstances to Check for Quality 132</p> <p>Automated Validation 136</p> <p>Data Quality Dimensions 136</p> <p>Data Quality Rules and Metrics 140</p> <p>Methods to Validate Quality 142</p> <p>Summary 144</p> <p>Exam Essentials 145</p> <p>Review Questions 146</p> <p><b>Chapter 5 Data Analysis and Statistics 151</b></p> <p>Fundamentals of Statistics 152</p> <p>Descriptive Statistics 155</p> <p>Measures of Frequency 155</p> <p>Measures of Central Tendency 160</p> <p>Measures of Dispersion 164</p> <p>Measures of Position 173</p> <p>Inferential Statistics 175</p> <p>Confidence Intervals 175</p> <p>Hypothesis Testing 179</p> <p>Simple Linear Regression 186</p> <p>Analysis Techniques 190</p> <p>Determine Type of Analysis 190</p> <p>Types of Analysis 191</p> <p>Exploratory Data Analysis 192</p> <p>Summary 192</p> <p>Exam Essentials 194</p> <p>Review Questions 196</p> <p><b>Chapter 6 Data Analytics Tools 201</b></p> <p>Spreadsheets 202</p> <p>Microsoft Excel 203</p> <p>Programming Languages 205</p> <p>R 205</p> <p>Python 206</p> <p>Structured Query Language (SQL) 208</p> <p>Statistics Packages 209</p> <p>IBM SPSS 210</p> <p>SAS 211</p> <p>Stata 211</p> <p>Minitab 212</p> <p>Machine Learning 212</p> <p>IBM SPSS Modeler 213</p> <p>RapidMiner 214</p> <p>Analytics Suites 217</p> <p>IBM Cognos 217</p> <p>Power BI 218</p> <p>MicroStrategy 219</p> <p>Domo 220</p> <p>Datorama 221</p> <p>AWS QuickSight 222</p> <p>Tableau 222</p> <p>Qlik 224</p> <p>BusinessObjects 225</p> <p>Summary 225</p> <p>Exam Essentials 225</p> <p>Review Questions 227</p> <p><b>Chapter 7 Data Visualization with Reports and Dashboards 231</b></p> <p>Understanding Business Requirements 232</p> <p>Understanding Report Design Elements 235</p> <p>Report Cover Page 236</p> <p>Executive Summary 237</p> <p>Design Elements 239</p> <p>Documentation Elements 244</p> <p>Understanding Dashboard Development Methods 247</p> <p>Consumer Types 247</p> <p>Data Source Considerations 248</p> <p>Data Type Considerations 249</p> <p>Development Process 250</p> <p>Delivery Considerations 250</p> <p>Operational Considerations 252</p> <p>Exploring Visualization Types 252</p> <p>Charts 252</p> <p>Maps 258</p> <p>Waterfall 264</p> <p>Infographic 266</p> <p>Word Cloud 267</p> <p>Comparing Report Types 268</p> <p>Static and Dynamic 268</p> <p>Ad Hoc 269</p> <p>Self-Service (On-Demand) 269</p> <p>Recurring Reports 269</p> <p>Tactical and Research 270</p> <p>Summary 271</p> <p>Exam Essentials 272</p> <p>Review Questions 274</p> <p><b>Chapter 8 Data Governance 279</b></p> <p>Data Governance Concepts 280</p> <p>Data Governance Roles 281</p> <p>Access Requirements 281</p> <p>Security Requirements 286</p> <p>Storage Environment Requirements 289</p> <p>Use Requirements 291</p> <p>Entity Relationship Requirements 292</p> <p>Data Classification Requirements 292</p> <p>Jurisdiction Requirements 297</p> <p>Breach Reporting Requirements 298</p> <p>Understanding Master Data Management 299</p> <p>Processes 300</p> <p>Circumstances 301</p> <p>Summary 303</p> <p>Exam Essentials 304</p> <p>Review Questions 306</p> <p><b>Appendix Answers to the Review Questions 311</b></p> <p>Chapter 2: Understanding Data 312</p> <p>Chapter 3: Databases and Data Acquisition 314</p> <p>Chapter 4: Data Quality 315</p> <p>Chapter 5: Data Analysis and Statistics 317</p> <p>Chapter 6: Data Analytics Tools 319</p> <p>Chapter 7: Data Visualization with Reports and Dashboards 322</p> <p>Chapter 8: Data Governance 323</p> <p>Index 327</p>
<p><B>ABOUT THE AUTHORS</b></p> <p><b>Mike Chapple, PhD,</b> is Teaching Professor of IT, Analytics, and Operations at the University of Notre Dame. He’s a technology professional and educator with over 20 years of experience. Mike provides certification resources at his website, CertMike.com. <p><b>Sharif Nijim</b> is Assistant Teaching Professor of IT, Analytics, and Operations in the Mendoza College of Business at the University of Notre Dame. He teaches undergraduate and graduate courses on cloud computing, business analytics, and information technology.
<p><b>Your efficient and complete guide to preparing for the CompTIA Data+ certification exam</b></p> <p>The CompTIA<sup>®</sup> Data+<sup>®</sup> Study Guide is your one-stop resource for complete coverage of the DA0-001 exam. CompTIA Data+ validates certified professionals have the skills required to facilitate data-driven business decisions, including mining data, manipulating data, visualizing and reporting data, applying basic statistical methods, and analyzing complex datasets while adhering to governance and quality standards throughout the entire data life cycle. This Sybex Study Guide covers 100% of the DA0-001 objective domains. Focused content validates and measures exam readiness, and real-world examples and scenarios, exercises, and chapter review questions get you up to speed smarter and faster than any other study resource. Use multiple devices to access the Sybex online learning environment to reinforce and retain what you’ve learned. Get ready for the CompTIA Data+ exam with Sybex, the most trusted name in professional tech education. <p><B>Coverage of 100% of all exam objectives in this Study Guide means you’ll be ready for:</b> <ul><li>Data Concepts and Environments</li> <li>Data Mining</li> <li>Data Analysis</li> <li>Data Visualization</li> <li>Data Governance, Quality, and Controls</li></ul> <p><B>ABOUT THE COMPTIA DATA+ CERTIFICATION</b> <p>CompTIA Data+ is an early-career data analytics certification for professionals tasked with developing and promoting data-driven business decision-making. The certification validates the data analytics skills and competencies that are needed to organize, understand, and act on relevant data. <p><b>Interactive learning environment</b> <p>Take your exam prep to the next level with Sybex’s superior interactive online study tools. To access our learning environment, simply visit <b>www.wiley.com/go/sybextestprep</b>, register your book to receive your unique PIN, and instantly gain one year of FREE access after activation to: <ul><li><b>Interactive test bank</b> with 2 practice exams to help you identify areas where further review is needed. Get more than 90% of the answers correct, and you’re ready to take the certification exam.</li> <li><b>100 electronic flashcards</b> to reinforce learning and last-minute prep before the exam</li> <li><b>Comprehensive glossary</b> in PDF format gives you instant access to the key terms so you are fully prepared</li></ul>

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