CompTIA Data+ DA0-001 Exam Cram
Pearson IT Certification
978-0-13-763729-4 (ISBN)
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
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.
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
| Erscheint lt. Verlag | 3.5.2023 |
|---|---|
| Verlagsort | Upper Saddle River |
| Sprache | englisch |
| Maße | 153 x 229 mm |
| Gewicht | 739 g |
| Themenwelt | Mathematik / Informatik ► Informatik ► Datenbanken |
| Informatik ► Weitere Themen ► Zertifizierung | |
| ISBN-10 | 0-13-763729-2 / 0137637292 |
| ISBN-13 | 978-0-13-763729-4 / 9780137637294 |
| Zustand | Neuware |
| Haben Sie eine Frage zum Produkt? |
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