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 |
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Chapter 1 Understanding Databases and Data Warehouses |
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Databases and Database Management Systems |
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Database Management System (DBMS) |
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Data Warehouses and Data Lakes |
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Online Transactional Processing (OLTP) |
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Online Analytical Processing (OLAP) |
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Chapter 2 Understanding Database Schemas and Dimensions |
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Star and Snowflake Schemas |
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Slowly Changing Dimensions, Keeping Historical Information, and Keeping Current Information |
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Keeping Current and Historical Information |
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Slowly Changing Dimensions |
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Chapter 3 Data Types and Types of Data |
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Introduction to Data Types |
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Storage Sizes of Various Data Types |
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Comparing and Contrasting Different Data Types |
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Categorical vs. Dimension and Discrete vs. Continuous Data Types |
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Categorical/Dimension Data Types |
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Discrete vs. Continuous Data Types |
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Types of Data: Audio, Video, and Images |
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Chapter 4 Understanding Common Data Structures and File Formats |
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Structured vs. Unstructured Data |
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Structured vs. Unstructured Data |
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JavaScript Object Notation (JSON) |
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Extensible Markup Language (XML) |
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Hypertext Markup Language (HTML) |
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Chapter 5 Understanding Data Acquisition and Monetization |
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Extract, Transform, and Load (ETL) |
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Extract, Load, and Transform (ELT) |
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Application Programming Interfaces (APIs)/Web Services |
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Chapter 6 Cleansing and Profiling Data |
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Profiling and Cleansing Basics |
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Chapter 7 Understanding and Executing Data Manipulation |
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Data Manipulation Techniques |
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Parsing/String Manipulation |
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Chapter 8 Understanding Common Techniques for Data Query Optimization and Testing |
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Temporary Table in a Query Set |
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Chapter 9 The (Un)Common Data Analytics Tools |
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Structured Query Language (SQL) |
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Chapter 10 Understanding Descriptive and Inferential Statistical Methods |
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Introduction to Descriptive and Inferential Analysis |
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Measures of Central Tendency |
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Percent Change and Percent Difference |
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Inferential Statistical Methods |
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Chapter 11 Exploring Data Analysis and Key Analysis Techniques |
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Process to Determine Type of Analysis |
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Review/Refine Business Questions |
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Exploratory Data Analysis |
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Chapter 12 Approaching Data Visualization |
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Chapter 13 Exploring the Different Types of Reports and Dashboards |
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Report Cover Page and Design Elements |
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Reference Data Sources and Dates |
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Dashboard Considerations, Development, and Delivery Process |
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Chapter 14 Data-Driven Decision Making: Leveraging Charts, Graphs, and Reports |
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Types of Data Visualizations |
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Self-Service/On-Demand Reports |
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Tactical/Research Reporting |
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Chapter 15 Data Governance Concepts: Ensuring a Baseline |
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Access and Security Requirements |
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Storage Environment Requirements |
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Use and Entity Relationship Requirements |
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Entity Relationship Requirements |
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Data Classification, Jurisdiction Requirements, and Data Breach Reporting |
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Jurisdiction Requirements |
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Chapter 16 Applying Data Quality Control |
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Data Quality Dimensions and Circumstances to Check for Quality |
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Circumstances to Check for Quality |
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Final Product, Reports, and Dashboards |
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Data Quality Rules and Metrics, Methods to Validate Quality, and Automated Validation |
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Data Quality Rules and Metrics |
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Methods to Validate Data Quality and Automated Validation |
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Chapter 17 Understanding Master Data Management (MDM) Concepts |
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Consolidation of Multiple Data Fields |
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Standardization of Data Field Names |
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Compliance with Policies and Regulations |
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Chapter 18 Getting Ready for the CompTIA Data+ Exam |
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459 | (8) |
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Getting Ready for the CompTIA Data+ Exam |
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459 | (2) |
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Tips for Taking the Real Exam |
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461 | (4) |
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Beyond the CompTIA Data+ Certification |
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465 | (2) |
Index |
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Akhil Behl is a passionate technologist and business development practitioner. He has more than 20 years of experience in the IT industry, working across several leadership, advisory, consultancy, and business development profiles across OEMs, telcos, and SI organizations. Akhil believes in cultivating an entrepreneurial culture, working across high-performance teams, identifying emerging technology trends, and ongoing innovation. For the last 7+ years, he has been working extensively with hyperscalers across industry verticals. He is employed at Red Hat, leading the Global System Integrator (GSI) partner alliances for the ANZ region.
Akhil is a published author. Over the past decade, he has authored multiple titles on security and business communication technologies. This is his fifth book with Pearson Education. He has contributed as technical editor for over a dozen books on security, networking, and information technology. He has published several research papers in national and international journals, including IEEE Xplore, and presented at various IEEE conferences, as well as other prominent ICT, security, and telecom events. Writing and mentoring are his passions.
Akhil holds CCIE 19564 Emeritus (Collaboration and Security), CompTIA Data+, Azure Solutions Architect Expert, Google Professional Cloud Architect, Azure AI Certified Associate, Azure Data Fundamentals, CCSK, CHFI, ITIL, VCP, TOGAF, CEH, ISM, CCDP, and multiple other industry certifications. He has a bachelor's degree in technology and a master's in business administration.
Akhil lives in Melbourne, Australia, with his better half, Kanika, and two sons, Shivansh (11 years) and Shaurya (9 years). Both of them are passionate gamers and are excellent musicians, sporting guitar and keyboard, respectively.
In his spare time, Akhil likes to play cricket, chess, and console games with his sons, watch movies with his family, and write articles or blogs. The family enjoys building LEGO! The family are big Star Wars fans and have keen interest in Star Wars as well as Technic and Creator LEGOs.
Dr. Siva Ganapathy Subramanian Manoharan is a senior professional with more than 18+ years of expertise in the data, analytics, artificial intelligence, and machine learning arenas, spanning a wide range of data portfolios. He heads the Data & Analytics Business Unit for Searce Inc in his current role as global chief data officer. He is a cloud data and platform architect with a background in data engineering, management, and analytics. He has considerable experience in a variety of enterprises across sectors. He is an ambitious leader with a startup-to-scale growth mindset who has built/launched new practices and strategic business units for several corporations and scaled them to huge growth.
Siva specializes in the sales, strategic solutions, P&L consulting, pre-sales, delivery of information management advisory, data architecture, and implementation services in the various industry verticals. He has extensive experience serving more than 200 customers globally, with a travel history of more than 25 countries. Over the past 8+ years, he has been living in the United Kingdom.
Siva leads a technology-focused group of individuals and motivates them for professional certifications and knowledge sharing. He has himself attained more than 81 IT certifications. Siva mentors and guides IT professionals and youth across the globe in their journey for a successful future in information technology focused on data analytics and artificial intelligence.
Siva is a technology-integrated author. He has several IT blog posts and book publications to his credit on data and analytics, artificial intelligence, and machine learning technologies. He has contributed as a technical editor for multiple blogs and whitepapers and hosted many events on data and analytics and information technology.
Siva was awarded the International Achievers award in 2022 by IAF India, the Leader of Excellence award in 2022 by BIZEMAG, and the Most Admired Global Indians 2022 with Passion Vista. He completed a bachelor's degree in electronics communication engineering from the University of Madras, an international MBA from Russian Ulyanovsk State University, a Ph.D. from the University of Swahili, and a D.Sc. from Azteca University.
Siva lives in London with Gaurave SGS (10 years) and Thejashvini SGS (5 years). Both of them are innovative artists, passionate gamers, and excellent creators. In his leisure time, Siva likes to watch movies, travel to new locations, play with Gaurave and Thejashvini, and write whitepapers, articles, and blogs.