Published by Pearson IT Certification (January 26, 2023) © 2023
Akhil Behl | Siva SubramanianCompTIA® Data+ DA0-001 Exam Cram is an all-inclusive study guide designed to help you pass the CompTIA Data+ DA0-001 exam. Prepare for test day success with complete coverage of exam objectives and topics, plus hundreds of realistic practice questions. Extensive prep tools include quizzes, Exam Alerts, and our essential last-minute review CramSheet. The powerful Pearson Test Prep practice software provides real-time assessment and feedback with two complete exams.
Covers the critical information needed to score higher on your Data+ DA0-001 exam!
- Understand data concepts, environments, mining, analysis, visualization, governance, quality, and controls
- Work with databases, data warehouses, database schemas, dimensions, data types, structures, and file formats
- Acquire data and understand how it can be monetized
- Clean and profile data so it;s more accurate, consistent, and useful
- Review essential techniques for manipulating and querying data
- Explore essential tools and techniques of modern data analytics
- Understand both descriptive and inferential statistical methods
- Get started with data visualization, reporting, and dashboards
- Leverage charts, graphs, and reports for data-driven decision-making
- Learn important data governance concepts
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