CompTIA Data+ Study Guide / Sybex Study Guide (PDF)
Exam DA0-001
(Sprache: Englisch)
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...
CompTIA Data+ Study Guide: Exam DA0-001 delivers easily accessible and actionable instruction for achieving data analysis...
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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 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 terms
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, CompTIA Data+ Study Guide: Exam DA0-001 provides an invaluable head start to beginning or accelerating a career as an in-demand data analyst.
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 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 terms
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, CompTIA Data+ Study Guide: Exam DA0-001 provides an invaluable head start to beginning or accelerating a career as an in-demand data analyst.
Autoren-Porträt von Mike Chapple, Sharif Nijim
ABOUT THE AUTHORSMike 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.
Bibliographische Angaben
- Autoren: Mike Chapple , Sharif Nijim
- 2022, 1. Auflage, 368 Seiten, Englisch
- Verlag: John Wiley & Sons
- ISBN-10: 1119845270
- ISBN-13: 9781119845270
- Erscheinungsdatum: 18.03.2022
Abhängig von Bildschirmgrösse und eingestellter Schriftgrösse kann die Seitenzahl auf Ihrem Lesegerät variieren.
eBook Informationen
- Dateiformat: PDF
- Grösse: 20 MB
- Mit Kopierschutz
Sprache:
Englisch
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