Comptia Data+ Study Guide - Exam Da0-001

Informationen zum Autor ABOUT THE AUTHORS Mike Chapple, PhD, 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. Sharif Nijim 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. Klappentext Build a solid foundation in data analysis skills and pursue a coveted Data+ certification with this intuitive study guideCompTIA Data+ Study Guide: Exam DA0-001 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.With comprehensive coverage of data concepts and environments, data mining, data analysis, visualization, and data governance, quality, and controls, this Study Guide offers:* 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* 100% coverage of objectives for the NEW CompTIA Data+ exam* Access to the Sybex online learning resources, with review questions, full-length practice exam, hundreds of electronic flashcards, and a glossary of key termsIdeal 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, CompTIA Data+ Study Guide: Exam DA0-001 provides an invaluable head start to beginning or accelerating a career as an in-demand data analyst. Zusammenfassung Build a solid foundation in data analysis skills and pursue a coveted Data+ certification with this intuitive study guideCompTIA Data+ Study Guide: Exam DA0-001 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.With comprehensive coverage of data concepts and environments, data mining, data analysis, visualization, and data governance, quality, and controls, this Study Guide offers:* 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* 100% coverage of objectives for the NEW CompTIA Data+ exam* Access to the Sybex online learning resources, with review questions, full-length practice exam, hundreds of electronic flashcards, and a glossary of key termsIdeal 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, CompTIA Data+ Study Guide: Exam DA0-001 provides an invaluable head start to beginning or accelerating a career as an in-demand data analyst. Inhaltsverzeichnis Introduction xv Assessment Test xxii Chapter 1 Today's Data Analyst 1 Welcome to the World of Analytics 2 Data 2 Storage 3 Computing Power 4 Careers in Analytics 5 The Analytics Process 6 Data Acquisition 7 Cleaning and Manipulation 7 Analysis 8 Visualization 8 Reporting and Communication 8 Analytics Techniques 10 Descriptive Analytics 10 Predictive Analytics 11 Prescriptive Analytics 11 Machine Learning, Arti...

List of contents

Introduction xv
 
Assessment Test xxii
 
Chapter 1 Today's Data Analyst 1
 
Welcome to the World of Analytics 2
 
Data 2
 
Storage 3
 
Computing Power 4
 
Careers in Analytics 5
 
The Analytics Process 6
 
Data Acquisition 7
 
Cleaning and Manipulation 7
 
Analysis 8
 
Visualization 8
 
Reporting and Communication 8
 
Analytics Techniques 10
 
Descriptive Analytics 10
 
Predictive Analytics 11
 
Prescriptive Analytics 11
 
Machine Learning, Artificial Intelligence, and Deep Learning 11
 
Data Governance 13
 
Analytics Tools 13
 
Summary 15
 
Chapter 2 Understanding Data 17
 
Exploring Data Types 18
 
Structured Data Types 20
 
Unstructured Data Types 31
 
Categories of Data 36
 
Common Data Structures 39
 
Structured Data 39
 
Unstructured Data 41
 
Semi-structured
 
Data 42
 
Common File Formats 42
 
Text Files 42
 
JavaScript Object Notation 44
 
Extensible Markup Language (XML) 45
 
HyperText Markup Language (HTML) 47
 
Summary 48
 
Exam Essentials 49
 
Review Questions 51
 
Chapter 3 Databases and Data Acquisition 57
 
Exploring Databases 58
 
The Relational Model 59
 
Relational Databases 62
 
Nonrelational Databases 68
 
Database Use Cases 71
 
Online Transactional Processing 71
 
Online Analytical Processing 74
 
Schema Concepts 75
 
Data Acquisition Concepts 81
 
Integration 81
 
Data Collection Methods 83
 
Working with Data 88
 
Data Manipulation 89
 
Query Optimization 96
 
Summary 99
 
Exam Essentials 100
 
Review Questions 101
 
Chapter 4 Data Quality 105
 
Data Quality Challenges 106
 
Duplicate Data 106
 
Redundant Data 107
 
Missing Values 110
 
Invalid Data 111
 
Nonparametric data 112
 
Data Outliers 113
 
Specification Mismatch 114
 
Data Type Validation 114
 
Data Manipulation Techniques 116
 
Recoding Data 116
 
Derived Variables 117
 
Data Merge 118
 
Data Blending 119
 
Concatenation 121
 
Data Append 121
 
Imputation 122
 
Reduction 124
 
Aggregation 126
 
Transposition 127
 
Normalization 128
 
Parsing/String Manipulation 130
 
Managing Data Quality 132
 
Circumstances to Check for Quality 132
 
Automated Validation 136
 
Data Quality Dimensions 136
 
Data Quality Rules and Metrics 140
 
Methods to Validate Quality 142
 
Summary 144
 
Exam Essentials 145
 
Review Questions 146
 
Chapter 5 Data Analysis and Statistics 151
 
Fundamentals of Statistics 152
 
Descriptive Statistics 155
 
Measures of Frequency 155
 
Measures of Central Tendency 160
 
Measures of Dispersion 164
 
Measures of Position 173
 
Inferential Statistics 175
 
Confidence Intervals 175
 
Hypothesis Testing 179
 
Simple Linear Regression 186
 
Analysis Techniques 190
 
Determine Type of Analysis 190
 
Types of Analysis 191
 
Exploratory Data Analysis 192
 
Summary 192
 
Exam Essentials 194
 
Review Questions 196
 
Chapter 6 Data Analytics Tools 201
 
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Product details

• Authors: Mike Chapple, Mike (University of Notre Dame) Nijim Chapple, Chapple Mike, Sharif Nijim
• Publisher: Wiley, John and Sons Ltd
• Languages: English
• Product format: Paperback / Softback
• Released: 23.05.2022
• EAN: 9781119845256
• ISBN: 978-1-119-84525-6
• No. of pages: 368
• Series: Sybex Study Guide
• Subjects: Natural sciences, medicine, IT, technology > IT, data processing > IT; Statistik, Datenanalyse, Prüfungsvorbereitung, Statistics, Zertifizierung, test prep, Comptia, data analysis, Zertifizierung f. MSCE u. Novell, Certification (MSCE, Novell, etc.)