CompTIA data+ study guide : exam DA0-001

CompTIA data+ study guide exam DA0-001

Build a solid foundation in data analysis skills and pursue a coveted Data+ certification with this intuitive study guide CompTIA 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 Dat...

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Bibliographic Details
Other Authors: Chapple, Mike, author (author)
Format: eBook
Language:Inglés
Published: Indianapolis, IN : John Wiley & Sons, Inc [2022]
Subjects:
Computing Technology Industry Association > Examinations > Study guides.
Electronic data processing > Examinations > Study guides.
Electronic data processing personnel > Certification > Examinations > Study guides.
See on Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009657497406719
Table of Contents:
  • Cover
  • Title Page
  • Copyright Page
  • Contents at a Glance
  • Contents
  • Introduction
  • The Data+ Exam
  • Taking the Exam
  • After the Data+ Exam
  • What Does This Book Cover?
  • Study Guide Elements
  • Interactive Online Learning Environment and Test Bank
  • Exam DA0-001 Exam Objectives
  • DA0-001 Certification Exam Objective Map
  • Assessment Test
  • Answers to Assessment Test
  • Chapter 1 Today's Data Analyst
  • Welcome to the World of Analytics
  • Data
  • Storage
  • Computing Power
  • Careers in Analytics
  • The Analytics Process
  • Data Acquisition
  • Cleaning and Manipulation
  • Analysis
  • Visualization
  • Reporting and Communication
  • Analytics Techniques
  • Descriptive Analytics
  • Predictive Analytics
  • Prescriptive Analytics
  • Machine Learning, Artificial Intelligence, and Deep Learning
  • Data Governance
  • Analytics Tools
  • Summary
  • Chapter 2 Understanding Data
  • Exploring Data Types
  • Structured Data Types
  • Unstructured Data Types
  • Categories of Data
  • Common Data Structures
  • Structured Data
  • Unstructured Data
  • Semi-structured Data
  • Common File Formats
  • Text Files
  • JavaScript Object Notation
  • Extensible Markup Language (XML)
  • HyperText Markup Language (HTML)
  • Summary
  • Exam Essentials
  • Review Questions
  • Chapter 3 Databases and Data Acquisition
  • Exploring Databases
  • The Relational Model
  • Relational Databases
  • Nonrelational Databases
  • Database Use Cases
  • Online Transactional Processing
  • Online Analytical Processing
  • Schema Concepts
  • Data Acquisition Concepts
  • Integration
  • Data Collection Methods
  • Working with Data
  • Data Manipulation
  • Query Optimization
  • Summary
  • Exam Essentials
  • Review Questions
  • Chapter 4 Data Quality
  • Data Quality Challenges
  • Duplicate Data
  • Redundant Data
  • Missing Values
  • Invalid Data
  • Nonparametric data
  • Data Outliers.
  • Specification Mismatch
  • Data Type Validation
  • Data Manipulation Techniques
  • Recoding Data
  • Derived Variables
  • Data Merge
  • Data Blending
  • Concatenation
  • Data Append
  • Imputation
  • Reduction
  • Aggregation
  • Transposition
  • Normalization
  • Parsing/String Manipulation
  • Managing Data Quality
  • Circumstances to Check for Quality
  • Automated Validation
  • Data Quality Dimensions
  • Data Quality Rules and Metrics
  • Methods to Validate Quality
  • Summary
  • Exam Essentials
  • Review Questions
  • Chapter 5 Data Analysis and Statistics
  • Fundamentals of Statistics
  • Common Symbols in Statistics
  • Descriptive Statistics
  • Measures of Frequency
  • Measures of Central Tendency
  • Measures of Dispersion
  • Measures of Position
  • Inferential Statistics
  • Confidence Intervals
  • Hypothesis Testing
  • Simple Linear Regression
  • Analysis Techniques
  • Determine Type of Analysis
  • Types of Analysis
  • Exploratory Data Analysis
  • Summary
  • Exam Essentials
  • Review Questions
  • Chapter 6 Data Analytics Tools
  • Spreadsheets
  • Microsoft Excel
  • Programming Languages
  • R
  • Python
  • Structured Query Language (SQL)
  • Statistics Packages
  • IBM SPSS
  • SAS
  • Stata
  • Minitab
  • Machine Learning
  • IBM SPSS Modeler
  • RapidMiner
  • Analytics Suites
  • IBM Cognos
  • Power BI
  • MicroStrategy
  • Domo
  • Datorama
  • AWS QuickSight
  • Tableau
  • Qlik
  • BusinessObjects
  • Summary
  • Exam Essentials
  • Review Questions
  • Chapter 7 Data Visualization with Reports and Dashboards
  • Understanding Business Requirements
  • Understanding Report Design Elements
  • Report Cover Page
  • Executive Summary
  • Design Elements
  • Documentation Elements
  • Understanding Dashboard Development Methods
  • Consumer Types
  • Data Source Considerations
  • Data Type Considerations
  • Development Process
  • Delivery Considerations.
  • Operational Considerations
  • Exploring Visualization Types
  • Charts
  • Maps
  • Waterfall
  • Infographic
  • Word Cloud
  • Comparing Report Types
  • Static and Dynamic
  • Ad Hoc
  • Self-Service (On-Demand)
  • Recurring Reports
  • Tactical and Research
  • Summary
  • Exam Essentials
  • Review Questions
  • Chapter 8 Data Governance
  • Data Governance Concepts
  • Data Governance Roles
  • Access Requirements
  • Security Requirements
  • Storage Environment Requirements
  • Use Requirements
  • Entity Relationship Requirements
  • Data Classification Requirements
  • Jurisdiction Requirements
  • Breach Reporting Requirements
  • Understanding Master Data Management
  • Processes
  • Circumstances
  • Summary
  • Exam Essentials
  • Review Questions
  • Appendix Answers to the Review Questions
  • Chapter 2: Understanding Data
  • Chapter 3: Databases and Data Acquisition
  • Chapter 4: Data Quality
  • Chapter 5: Data Analysis and Statistics
  • Chapter 6: Data Analytics Tools
  • Chapter 7: Data Visualization with Reports and Dashboards
  • Chapter 8: Data Governance
  • Index
  • EULA.

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