CompTIA Data+ DA0-001 Exam Cram, 1st edition

Published by Pearson IT Certification (January 3, 2023) © 2023

  • Akhil Behl
  • Siva G Subramanian
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Businesses now more than ever are relying on data analysis to maximize sales and understand consumer trends. Regardless of your role or job function, just about everyone in today's climate is expected to have some skills in this area. As the field of data analysis becomes more integral to business strategy it is imperative to gain the knowledge that will set yourself apart from the competition and benefit your career prospects. CompTIA Data+ DA0-001 Exam Cram is designed to prepare candidates for success on the exam, using the proven Exam Cram method of study. This latest addition to the Exam Cram series is geared toward early-career business and data analysts, and as with all Exam Cram books, includes:

  • Chapters that map directly to the exam objectives Comprehensive foundational learning on all topics covered on the exam
  • An extensive collection of practice questions
  • Access to the Pearson Test Prep practice test software that provides real-time practice and feedback, online or offline
  • Flash cards to drill on key concepts
  • The Cram Sheet tear-out card including tips, acronyms, and memory joggers not available anywhere else;mdash;perfect for last-minute study

All the topics in the exam are covered here, including: mining data, manipulating data, applying basic statistical methods, and analyzing complex datasets while adhering to governance and quality standards throughout the entire data life cycle. This book is in complete alignment with the CompTIA Data+ certification exam blueprint. It will take you systematically through the five major domains, and the subtopics within those domains, which constitute the ComptTIA Data+ exam. It is an invaluable guide to preparing to pass the CompTIA Data+ exam.

Introduction. . . . . . xx

CHAPTER 1: Understanding Databases and Data Warehouses. . . 1

Databases and Database Management Systems.. . . 2

Data Warehouses and Data Lakes.. . . . 15

OLTP and OLAP.. . . . . 24

What Next?.. . . . . . 30

CHAPTER 2: Understanding Database Schemas and Dimensions.. . 31

Schema Concepts.. . . . . 32

Star and Snowflake Schemas. . . . 37

Slowly Changing Dimensions, Keeping Historical Information, and Keeping Current Information.  . 45

What Next?.. . . . . . 51

CHAPTER 3: Data Types and Types of Data. . . . . 53

Introduction to Data Types. . . . 54

Comparing and Contrasting Different Data Types. . 60

Categorical vs. Dimension and Discrete vs. Continuous Data Types. 67

Types of Data: Audio, Video, and Images.. . . 72

What Next?.. . . . . . 86

CHAPTER 4: Understanding Common Data Structures and File Formats.. . 87

Structured vs. Unstructured Data.. . . . 88

Data File Formats.. . . . . 98

What Next?.. . . . . . 110

CHAPTER 5: Understanding Data Acquisition and Monetization. . . 111

Integration. . . . . . 112

Data Collection Methods.. . . . . 126

What Next?.. . . . . . 135

CHAPTER 6: Cleansing and Profiling Data. . . . . 137

Profiling and Cleansing Basics.. . . . 138

What Next?.. . . . . . 151

CHAPTER 7: Understanding and Executing Data Manipulation. . . 153

Data Manipulation Techniques.. . . . 154

What Next?.. . . . . . 182

CHAPTER 8: Understanding Common Techniques for Data Query Optimization and Testing... . 183

Query Optimization.. . . . . 184

What Next?.. . . . . . 206

CHAPTER 9: The (Un)Common Data Analytics Tools.. . . . 207

Data Analytics Tools.. . . . . 208

What Next?.. . . . . . 224

CHAPTER 10: Understanding Descriptive and Inferential Statistical Methods.. . 225

Introduction to Descriptive and Inferential Analysis. . 226

Inferential Statistical Methods.. . . . 238

What Next?.. . . . . . 253

CHAPTER 11: Exploring Data Analysis and Key Analysis Techniques.. . 255

Process to Determine Type of Analysis. . . 256

Types of Analysis. . . . . 265

What Next?.. . . . . . 278

CHAPTER 12: Approaching Data Visualization.. . . . 279

Business Reports. . . . . 280

What Next?.. . . . . . 297

CHAPTER 13: Exploring the Different Types of Reports and Dashboards.. . 299

Report Cover Page and Design Elements. . . 300

Documentation Elements. . . . . 316

Dashboard Considerations, Development, and Delivery Process.. 321

What Next?.. . . . . . 337

CHAPTER 14: Data-Driven Decision Making: Leveraging Charts, Graphs, and Reports. . . 339

Types of Data Visualizations.. . . . 340

Reports.. . . . . . 358

What Next?.. . . . . . 366

CHAPTER 15: Data Governance Concepts: Ensuring a Baseline. . . 367

Access and Security Requirements. . . . 370

Storage Environment Requirements.. . . . 383

Use and Entity Relationship Requirements. . . 388

Data Classification, Jurisdiction Requirements, and

Data Breach Reporting.. . . . . 399

What Next?.. . . . . . 410

CHAPTER 16: Applying Data Quality Control. . . . . 411

Data Quality Dimensions and Circumstances to Check for Quality.. 412

Data Quality Rules and Metrics, Methods to Validate Quality, and

Automated Validation.. . . . . 424

What Next?.. . . . . . 439

CHAPTER 17: Understanding Master Data Management (MDM) Concepts.. . 441

Processes.. . . . . . 442

Circumstances for MDM.. . . . . 454

What Next?.. . . . . . 458

CHAPTER 18: Getting Ready for the CompTIA Data+ Exam.. . . 459

Getting Ready for the CompTIA Data+ Exam.. . . 459

Tips for Taking the Real Exam.. . . . 461

Beyond the CompTIA Data+ Certification. . . 465

 

9780137637294, TOC, 11/17/2022

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