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Cybersecurity Fundamentals: Governance Risk & Compliance by Bruce Brown
English | August 27, 2024 | ISBN: N/A | ASIN: B0DFHJYBWC | 125 pages | EPUB | 1.49 Mb
Discover the Secrets of Cybersecurity Governance, Risk, and Compliance with Cybersecurity Fundamentals: Governance, Risk & Compliance by Bruce Brown, CISSP, CGRC.
In the ever-evolving world of cybersecurity, understanding the intricacies of Governance, Risk, and Compliance (GRC) is not just beneficial-it's essential. Despite being one of the most crucial areas in cybersecurity, GRC is often overlooked, leaving many professionals unprepared for the challenges ahead. This book changes that narrative.
Authored by Bruce Brown, a seasoned expert with over 20 years of experience in GRC, this guide takes you deep into the world of cybersecurity. You'll learn about:Roles and Responsibilities:Discover the key roles within GRC and how they interconnect to form a robust cybersecurity framework.Tools and Techniques:Get hands-on with the essential tools that professionals use to manage governance, risk, and compliance across various industries.Critical Tasks:Master the tasks that drive successful GRC operations, ensuring your organization stays secure and compliant.Whether you're new to the field or looking to solidify your knowledge, Cybersecurity Fundamentals provides actionable insights that will empower you to excel in any industry. Packed with real-world examples and expert guidance, this book is your pathway to becoming a GRC professional.
Don't miss out on mastering the most important and often underappreciated aspect of cybersecurity. Buy Cybersecurity Fundamentals: Governance, Risk & Compliance today and start your journey to becoming a GRC expert!
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Cybersecurity in Artificial Intelligence: Attacks Defenses and Real World Application (AI Course) by Anshuman Mishra
English | 2025 | ASIN: B0FBTF1H9C | 527 pages | EPUB | 4 MB
In the era of rapid digital transformation, artificial intelligence (AI) has emerged as one of the most disruptive technologies across every conceivable industry. From healthcare and finance to smart cities and national defense, AI has dramatically reshaped the landscape of data processing, decision-making, and automation. However, as organizations and governments increasingly adopt AI, they must also confront an alarming reality: the rise of complex cybersecurity threats targeting and leveraging AI systems.
"Cybersecurity in Artificial Intelligence: Attacks, Defenses, and Real-World Applications" is a comprehensive academic and professional course book that serves as a foundational and advanced guide to understanding the intersection of artificial intelligence and cybersecurity. This book is not merely a theoretical exploration-it is a hands-on, practical resource enriched with case studies, industry practices, emerging tools, and policy discussions that bridge the gap between AI development and cybersecurity preparedness.
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Daniel Arbuckle's Mastering Python
English | 2017 | ISBN: B072178BTQ | Pages: 505 | EPUB (True) | 8.74 MB
Gain a thorough understanding of operating in a Python development environment, and some of the most important advanced topics with Daniel Arbuckle. This dynamic, concise book is full of real-world solutions for Python 3.6 problems, and advanced-level concepts such as reactive programming, microservices, ctypes and Cython.
About This Book
Covers the latest and advanced concepts of Python such as parallel processing with Python 3.6
Explore the Python language from its basic installation and setup to concepts such as reactive programming and microservices
Get introduced to the mechanism for rewriting code in a compiled language along with ctypes and Cython tools
Who This Book Is For
If you are a programmer and are familiar with the basics of Python, and you want to broaden your knowledge base to develop projects better and faster, this book is for you. Even if you are not familiar with Python, Daniel Arbuckle's Mastering Python starts with the basics and takes you on a journey to become an expert in the technology.
What You Will Learn
Get to grips with the basics of operating in a Python development environment
Build Python packages to efficiently create reusable code
Become proficient at creating tools and utility programs in Python
Use the Git version control system to protect your development environment from unwanted changes
Harness the power of Python to automate other software
Distribute computational tasks across multiple processors
Handle high I/O loads with asynchronous I/O to get a smoother performance
Take advantage of Python's metaprogramming and programmable syntax features
Get acquainted with the concepts behind reactive programming and RxPy
In Detail
Daniel Arbuckle's Mastering Python covers the basics of operating in a Python development environment, before moving on to more advanced topics. Daniel presents you with real-world solutions to Python 3.6 and advanced-level concepts, such as reactive programming, microservices, ctypes, and Cython tools.
You don't need to be familiar with the Python language to use this book, as Daniel starts with a Python primer. Throughout, Daniel highlights the major aspects of managing your Python development environment, shows you how to handle parallel computation, and helps you to master asynchronous I/O with Python 3.6 to improve performance. Finally, Daniel will teach you the secrets of metaprogramming and unit testing in Python, helping you acquire the perfect skillset to be a Python expert.
Daniel will get you up to speed on everything from basic programming practices to high-end tools and techniques, things that will help set you apart as a successful Python programmer.
Style and Approach
Daniel Arbuckle's Mastering Python covers basic to advanced-level concepts in computer science. If you are a beginner, then Daniel will help you get started. If you are experienced, he will expand your knowledge base.
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Dark Web Intelligence and OSINT Techniques
English | 2025 | ISBN: 9783384632524| 125 pages | EPUB | 1.9 MB
This book is your ticket to the Dark Web and OSINT world. It traces OSINT's roots from WWII to today. It explains the Dark Web's start with Tor in 2002. You'll learn about Surface, Deep, and Dark Web layers. It covers whistleblowers like Snowden who shook things up. Ethics and laws get a close look-think GDPR and Silk Road trials. Tools like Maltego and Python are broken down. Dark Web markets like Hydra are dissected. Crypto's role in shady deals is revealed. You'll see how hackers and malware thrive there. It links social media to the Dark Web. Geopolitics, AI, and quantum tech show the big picture. Famous busts like AlphaBay fill the pages. It ends with future predictions and global teamwork ideas.
Unlike other books, this one doesn't just skim the surface-it dives deep with fresh angles. It blends history, tech, and real-world stakes in a way that's easy to grasp. Other guides skip the ethics or future tech like quantum threats-this doesn't. It's got practical, hands-on tips you can use, not just theory. From tracing Bitcoin to decoding hacker slang, it's a toolkit others miss. It connects the dots between social media and the Dark Web uniquely. Plus, it's got a conversational vibe-no dry lectures here. It's your edge in understanding and tackling the hidden web like never before.
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Dark Web Intelligence and OSINT Techniques
English | 2025 | ASIN: B0FD38SLKV | 184 pages | EPUB (True) | 566.09 KB
This book is your ticket to the Dark Web and OSINT world. It traces OSINT's roots from WWII to today. It explains the Dark Web's start with Tor in 2002. You'll learn about Surface, Deep, and Dark Web layers. It covers whistleblowers like Snowden who shook things up. Ethics and laws get a close look-think GDPR and Silk Road trials. Tools like Maltego and Python are broken down. Dark Web markets like Hydra are dissected. Crypto's role in shady deals is revealed. You'll see how hackers and malware thrive there. It links social media to the Dark Web. Geopolitics, AI, and quantum tech show the big picture. Famous busts like AlphaBay fill the pages. It ends with future predictions and global teamwork ideas.
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Data Aggregation
English | 2024 | ISBN: 2940180041562 | Pages: 115 | EPUB (True) | 705.21 KB
This comprehensive guide demystifies the complex world of data aggregation, breaking down essential concepts and techniques into accessible, actionable content. From understanding the fundamentals of data aggregation to diving into advanced topics like real-time processing, cloud solutions, and the impact of emerging technologies, this book equips you with the knowledge to tackle data challenges effectively.
Inside, you'll discover:
Fundamental Techniques:
Learn about batch, real-time, and incremental aggregation methods and their applications.
Practical Tools:
Explore various tools and technologies for data aggregation, including database management systems, data warehousing solutions, and integration platforms.
Real-World Applications:
Delve into case studies across different industries to see how data aggregation drives business intelligence and operational efficiency.
Challenges and Solutions:
Understand common issues such as data quality, scalability, and security, and find practical solutions to address them.
Future Trends:
Stay ahead of the curve with insights into the latest advancements in AI, machine learning, edge computing, and more.
Data Aggregation: Techniques, Tools, and Practices for Effective Data Management
is an essential resource for mastering the art of data management in today's data-driven world.
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Data Analysis: An In-depth Insight
English | 2025 | ASIN: B0FC1YZKC9 | 119 pages | Epub (True) | 662.28 KB
"Data Analysis: An In-depth Insight" is a comprehensive guide to the art and science of data analysis, empowering readers with the knowledge and skills to uncover actionable insights from vast amounts of information. This book provides a thorough exploration of data analysis techniques, tools, and methodologies, catering to a wide range of audiences, from aspiring data analysts to experienced professionals seeking to enhance their skills.
Delving into the intricacies of data analysis, this book equips readers with the ability to navigate the data landscape, understand different data types and formats, and employ effective data collection strategies. It emphasizes the importance of data preprocessing, including data cleaning, transformation, and normalization, to ensure the accuracy and consistency of data for analysis.
The book dedicates significant attention to exploratory data analysis (EDA), a crucial step in the data analysis process. It introduces a variety of EDA techniques, such as data visualization and statistical analysis, to help readers gain an initial understanding of the data, identify patterns and trends, and formulate hypotheses for further investigation.
Predictive modeling is another key aspect covered in depth. The book explores supervised and unsupervised learning algorithms, enabling readers to build models that can learn from data and make accurate predictions. It delves into the concepts of model selection, evaluation, and optimization, empowering readers to develop robust and reliable models for various applications.
Data visualization plays a pivotal role in communicating the results of data analysis. This book provides a comprehensive overview of data visualization techniques, including charts, graphs, and infographics. It emphasizes the importance of choosing the right visualization for the data and presenting it in a clear and concise manner to facilitate effective decision-making.
"Data Analysis: An In-depth Insight" also addresses the ethical and legal considerations associated with data analysis, ensuring that readers are aware of the importance of data privacy, confidentiality, and algorithmic bias. It explores the regulatory landscape surrounding data analysis and provides guidance on how to conduct data analysis in a responsible and ethical manner.
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Data Analysis Excel Book: The Complete Microsoft Excel Guide to Master Powerful Techniques to Drive Data Insights and Smart Decisions
English | 2025 | ASIN: B0F4KQF387 | 209 pages | Epub | 18.43 MB
Master Excel Like a Pro - Unlock Hidden Data Insights and Make Smarter Decisions!
Includes 2 FREE bonuses:
Bonus 1: Two downloadable workbooks to practice and follow along with the examples from the book. Bonus 2: Online VBA course to automate your worksheets.Are you tired of struggling with Excel, feeling overwhelmed by complex data, or unsure how to turn raw numbers into powerful insights? This Excel book is your ultimate solution.
Whether you're an intermediate or advanced Excel user, a professional looking to sharpen your data skills, or a student aiming to master data-driven decision-making, this Excel guide will transform the way you work with data.
Why This Excel Book?
Most Excel books teach formulas, but they don't show you how to apply them effectively in real-world scenarios. You don't need another dry, technical manual-you need a proven, step-by-step blueprint that walks you through Excel's most powerful features for data analysis, reporting, and visualisation.
What You Will Gain
With this Excel 365 book, you'll move beyond the basics and discover:
Hidden Excel functions that make data analysis effortless Advanced data visualisation techniques using charting techniques, Pivot Charts and interactive dashboards so you can create stunning, impactful reports Step-by-step Excel training on advanced features such as Pivot Tables, Power Query, and Power Pivot to automate your work Data cleansing secrets to fix messy data instantly-so you can analyse it with confidence How to use Excel for business intelligence-turning raw data into actionable insights Proven formulas and techniques to save hours of manual work and avoid common mistakesWait... Is This Excel Guide Book Right for Me?
"I already know Excel basics-do I really need this?"
➡ Yes! This Excel 2025 book goes beyond the basics, showing you advanced techniques for data visualisation, automation, and business intelligence that most users never learn.
"I don't have time to learn complex Excel features."
➡ No problem! This Excel training book is structured with step-by-step instructions and real-world case studies so you can learn quickly and efficiently without feeling overwhelmed.
"I'm not a data analyst. Will I even use these techniques?"
➡ Absolutely! Whether you work in finance, marketing, supply chain, human resources, or management, mastering data analysis will help you make better decisions, save time, and boost productivity.
"Can't I just Google this information?"
➡ You could-but you'd be wasting hours piecing together scattered tutorials. This Excel book 2025 compiles everything you need in one place, with practical examples and exercises tailored for real-world application.
Who Is This For?
✔ Business professionals who need to make smarter, data-driven decisions
✔ Students and analysts who want to excel in data analytics and reporting
✔ Entrepreneurs who need to track and optimise their business performance
✔ Anyone looking for an Excel guide for beginners that also covers advanced techniques
Why Trust This Excel Guide?
This isn't just another Excel for Dummies tutorial. It's a Microsoft Excel guide book packed with real-world case studies, and practical examples to help you implement everything you learn-instantly.
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Data Analysis for Beginners
English | 2024 | ISBN: 2940180093394 | Pages: 125 | EPUB (True) | 293.05 KB
Embark on a journey into the world of data with "Data Analysis for Beginners," a comprehensive guide designed for beginners eager to unravel the secrets hidden within numbers. In this user-friendly book, you'll discover the power of data analysis and gain hands-on experience with essential tools and techniques.
Unlocking the World of Data:
Dive into the importance of data in our digital age and understand how it shapes decisions in various industries. Navigate through the basics, from terminology to the diverse types of data, as you set up your toolkit with popular software like Excel, Python, and R.
From Raw Data to Actionable Insights:
Learn the art of collecting and cleaning data, the crucial first steps in any analysis. Master exploratory data analysis (EDA) to unveil patterns and trends through descriptive statistics and compelling visualizations. Delve into statistical concepts, empowering you to draw meaningful conclusions from your data.
Machine Learning Simplified:
Demystify the world of machine learning, exploring both supervised and unsupervised learning. Walk through building and interpreting regression models, understand the intricacies of classification, and explore the power of clustering in uncovering hidden relationships within your data.
Beyond the Basics:
Discover advanced topics such as time series analysis, data wrangling, and feature engineering. Grasp the art of effective communication through data visualization, and explore the ethical considerations of handling and analyzing data.
Real-World Applications:
Immerse yourself in real-world applications through case studies and examples from diverse industries. Whether you're a student, professional, or simply curious, this book equips you with the skills to apply data analysis in practical scenarios.
Empowering Continuous Learning:
The journey doesn't end with the last page. "Data Analysis for Beginners" provides resources for further learning, tips for building a data analysis portfolio, and guidance on staying updated in this dynamic field.
Become a Data Analysis Pro:
With this accessible guide, you'll gain the confidence to tackle data challenges head-on. "Data Analysis for Beginners" is your companion on the path to becoming proficient in data analysis, offering a blend of theory, hands-on practice, and real-world applications. Uncover the potential of data and transform it into actionable insights with this must-have resource for beginners.
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Data Analysis using R: A Dummy's Approach
English | 2025 | ASIN: B0DW4FGXQJ | 88 pages | Epub | 2.38 MB
This book is for the people who wanted to get their hands dirty in Data Analysis using R programming Language. But don't know where to start? How to start?
I wrote the book in a simple, efficient way so that who does not have prior experience also can grasp quickly. Also, it will help to build the foundations strong who already exposed to 'R' but lacks confidence to write code fluently.
I want to request all my readers to go through each one of the examples without skipping one. Because each of them serves a purpose to be added. Simpler examples build the foundation strong. Then we can solve any problem no matter how complex that is. That is the sole purpose of this book.
This book covers foundational R programming, Data Analysis, some statistical process.
Hope this book will help my readers to gain confidence to write their own 'R' code for any scenario.
Wish you all the best!! !
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Data Analyst: Careers in data analysis
English | 2019 | ISBN: B07P9JY5FW | Pages: 243 | EPUB (True) | 2.69 MB
Data is constantly increasing and data analysts are in higher demand than ever. This book is an essential guide to the role of data analyst. Aspiring data analysts will discover what data analysts do all day, what skills they will need for the role, and what regulations they will be required to adhere to. Practising data analysts can explore useful data analysis tools, methods and techniques, brush up on best practices and look at how they can advance their career.
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Data Analytics A to Z: Becoming a Data Analyst
English | 2025 | ASIN: B0DYF9QXJ7 | 99 pages | Epub | 1.02 MB
Data Analyst A to Z: A Practical Guide to Mastering Data Analytics
In today's data-driven world, businesses and organizations rely on data analysts to extract insights, optimize strategies, and drive decision-making. "Data Analyst A to Z" is the ultimate guide for anyone looking to break into the field of data analytics, whether you're a beginner or an aspiring professional.
This book takes you through the entire data analytics process, from data collection and cleaning to exploratory data analysis, predictive modeling, and visualization. You'll learn essential skills in SQL, Python, R, and Excel, along with real-world applications in business, healthcare, finance, and marketing.
What You'll Learn:
The fundamentals of data analytics and statistical concepts Data cleaning, transformation, and preprocessing techniques Exploratory Data Analysis (EDA) and data visualization with Python and Tableau Machine learning basics for predictive modeling How to structure and communicate insights effectively Career paths and tips for landing a job as a data analystPacked with step-by-step tutorials, industry use cases, and hands-on projects, "Data Analyst A to Z" is your complete roadmap to building a successful career in data analytics.
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Data Analytics and Data Processing Essentials
English | 2024 | ISBN: B0DJXWBVQZ | Pages: 569 | EPUB (True) | 300.69 KB
IntroducingData Analytics and Data Processing Essentials: Unlocking Visualization, SQL, and AI Techniques for Modern Data Science
-your comprehensive guide to navigating the fast-paced world of data analytics. Whether you're just starting or looking to elevate your skills, this book provides the essential knowledge and practical tools you need to thrive in today's data-driven industries.
Why This Book?
This all-in-one resource covers every critical aspect ofdata science, fromdata processingtovisualization, and even advanced topics likeAI and machine learning. With easy-to-follow explanations and real-world examples, you'll learn how to:
Master Data Analytics Fundamentals: Explore key components of data analytics, including data collection, cleaning, and storage techniques.
Unlock SQL Power: Discover how to leverage SQL to efficiently manage and manipulate data.
Visualize Data Like a Pro: Gain hands-on experience with powerful visualization tools and techniques that make your data come to life.
Dive into AI Techniques: Learn about AI applications and machine learning models to solve complex problems and drive decision-making.
Explore Big Data Technologies: Get introduced to platforms like Hadoop and Spark to handle large datasets with ease.
Focus on Data Security and Privacy: Understand the importance of data governance, security, and ethical considerations in your projects.
Who Should Read This?
This book is designed forstudents,business analysts,data professionals, and anyone passionate about understanding and mastering data. With comprehensive explanations and step-by-step guides, it offers insights into how data science transforms industries such asfinance,healthcare,retail, andtechnology.
Why Wait?
Equip yourself with the skills to excel in the modern data-driven world. Whether you're interested in advancing your career or enhancing your business, this guide will help you unlock the full potential of data analytics and AI.Grab your copy today and start mastering the essentials!
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Data Driven
English | 2025 | ISBN: 9788235257888 | Pages: 186 | EPUB (True) | 827.47 KB
In today's competitive business environment, "Data Driven" argues that leveraging data analytics and customer insights is crucial for marketing success. This book provides a comprehensive guide to shifting towards data-driven decision-making, emphasizing that relying on intuition alone is no longer sufficient for sustainable growth. It highlights the evolution of marketing and the increasing importance of understanding data quality, as well as the ethical considerations involved in data handling.
The book explores the foundational principles of data analytics, the extraction of actionable customer insights, and the practical application of data-driven strategies across various marketing channels. For instance, understanding customer behavior through data mining and segmentation analysis enables businesses to create personalized customer experiences, leading to optimized marketing investments and a higher return on investment (ROI). Real-world case studies illustrate how leading companies have successfully implemented data-driven initiatives.
Beginning with an introduction to core data analytics concepts, the book progresses through customer insight methodologies and the practical application of data-driven strategies across key marketing channels like digital advertising and social media. It culminates with a discussion on building a data-driven marketing organization, emphasizing data governance and continuous improvement.
Ultimately, "Data Driven" provides the frameworks needed to foster collaboration between data scientists, marketers, and business leaders, leading to a cultural transformation within organizations.
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Data Engineering Best Practices: Architect robust and cost-effective data solutions in the cloud era
English | 2024 | ASIN: B0DG5HHLWK | 1226 pages | EPUB (True) | 15.18 MB
Explore modern data engineering techniques and best practices to build scalable, efficient, and future-proof data processing systems across cloud platforms
Key Features
Architect and engineer optimized data solutions in the cloud with best practices for performance and cost-effectiveness
Explore design patterns and use cases to balance roles, technology choices, and processes for a future-proof design
Learn from experts to avoid common pitfalls in data engineering projects
Purchase of the print or Kindle book includes a free PDF eBook
Book Description
Revolutionize your approach to data processing in the fast-paced business landscape with this essential guide to data engineering. Discover the power of scalable, efficient, and secure data solutions through expert guidance on data engineering principles and techniques. Written by two industry experts with over 60 years of combined experience, it offers deep insights into best practices, architecture, agile processes, and cloud-based pipelines.
You'll start by defining the challenges data engineers face and understand how this agile and future-proof comprehensive data solution architecture addresses them. As you explore the extensive toolkit, mastering the capabilities of various instruments, you'll gain the knowledge needed for independent research. Covering everything you need, right from data engineering fundamentals, the guide uses real-world examples to illustrate potential solutions. It elevates your skills to architect scalable data systems, implement agile development processes, and design cloud-based data pipelines. The book further equips you with the knowledge to harness serverless computing and microservices to build resilient data applications.
By the end, you'll be armed with the expertise to design and deliver high-performance data engineering solutions that are not only robust, efficient, and secure but also future-ready.
What you will learn
Architect scalable data solutions within a well-architected framework
Implement agile software development processes tailored to your organization's needs
Design cloud-based data pipelines for analytics, machine learning, and AI-ready data products
Optimize data engineering capabilities to ensure performance and long-term business value
Apply best practices for data security, privacy, and compliance
Harness serverless computing and microservices to build resilient, scalable, and trustworthy data pipelines
Who this book is for
If you are a data engineer, ETL developer, or big data engineer who wants to master the principles and techniques of data engineering, this book is for you. A basic understanding of data engineering concepts, ETL processes, and big data technologies is expected. This book is also for professionals who want to explore advanced data engineering practices, including scalable data solutions, agile software development, and cloud-based data processing pipelines.
Table of Contents
Overview of the Business Problem Statement
A Data Engineer's Journey - Background Challenges
A Data Engineer's Journey - IT's Vision and Mission
Architecture Principles
Architecture Framework - Conceptual Architecture Best Practices
Architecture Framework - Logical Architecture Best Practices
Architecture Framework - Physical Architecture Best Practices
Software Engineering Best Practice Considerations
Key Considerations for Agile SDLC Best Practices
Key Considerations for Quality Testing Best Practices
Key Considerations for IT Operational Service Best Practices
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Data Engineering with AWS Cookbook: A recipe-based approach to help you tackle data engineering problems with AWS services
English | 2024 | ISBN: 1805127284 | 528 pages | EPUB (True) | 35.64 MB
Master AWS data engineering services and techniques for orchestrating pipelines, building layers, and managing migrations
Key Features
Get up to speed with the different AWS technologies for data engineering
Learn the different aspects and considerations of building data lakes, such as security, storage, and operations
Get hands on with key AWS services such as Glue, EMR, Redshift, QuickSight, and Athena for practical learning
Purchase of the print or Kindle book includes a free PDF eBook
Book Description
Performing data engineering with Amazon Web Services (AWS) combines AWS's scalable infrastructure with robust data processing tools, enabling efficient data pipelines and analytics workflows. This comprehensive guide to AWS data engineering will teach you all you need to know about data lake management, pipeline orchestration, and serving layer construction.
Through clear explanations and hands-on exercises, you'll master essential AWS services such as Glue, EMR, Redshift, QuickSight, and Athena. Additionally, you'll explore various data platform topics such as data governance, data quality, DevOps, CI/CD, planning and performing data migration, and creating Infrastructure as Code. As you progress, you will gain insights into how to enrich your platform and use various AWS cloud services such as AWS EventBridge, AWS DataZone, and AWS SCT and DMS to solve data platform challenges.
Each recipe in this book is tailored to a daily challenge that a data engineer team faces while building a cloud platform. By the end of this book, you will be well-versed in AWS data engineering and have gained proficiency in key AWS services and data processing techniques. You will develop the necessary skills to tackle large-scale data challenges with confidence.
What you will learn
Define your centralized data lake solution, and secure and operate it at scale
Identify the most suitable AWS solution for your specific needs
Build data pipelines using multiple ETL technologies
Discover how to handle data orchestration and governance
Explore how to build a high-performing data serving layer
Delve into DevOps and data quality best practices
Migrate your data from on-premises to AWS
Who this book is for
If you're involved in designing, building, or overseeing data solutions on AWS, this book provides proven strategies for addressing challenges in large-scale data environments. Data engineers as well as big data professionals looking to enhance their understanding of AWS features for optimizing their workflow, even if they're new to the platform, will find value. Basic familiarity with AWS security (users and roles) and command shell is recommended.
Table of Contents
Managing Data Lake Storage
Sharing Your Data Across Environments and Accounts
Ingesting and Transforming Your Data with AWS Glue
A Deep Dive into AWS Orchestration Frameworks
Running Big Data Workloads with Amazon EMR
Governing Your Platform
Data Quality Management
DevOps - Defining IaC and Building CI/CD Pipelines
Monitoring Data Lake Cloud Infrastructure
Building a Serving Layer with AWS Analytics Services
Migrating to AWS - Steps, Strategies, and Best Practices for Modernizing Your Analytics and Big Data Workloads
Harnessing the Power of AWS for Seamless Data Warehouse Migration
Strategizing Hadoop Migrations - Cost, Data, and Workflow Modernization with AWS
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Data Engineering with AWS Cookbook: A recipe-based approach to help you tackle data engineering problems with AWS services
English | 2024 | ISBN: B0DFCS5CJZ | Pages: 847 | PDF | 369.81 KB
Performing data engineering with Amazon Web Services (AWS) combines AWS's scalable infrastructure with robust data processing tools, enabling efficient data pipelines and analytics workflows. This comprehensive guide to AWS data engineering will teach you all you need to know about data lake management, pipeline orchestration, and serving layer construction.
Through clear explanations and hands-on exercises, you'll master essential AWS services such as Glue, EMR, Redshift, QuickSight, and Athena. Additionally, you'll explore various data platform topics such as data governance, data quality, DevOps, CI/CD, planning and performing data migration, and creating Infrastructure as Code. As you progress, you will gain insights into how to enrich your platform and use various AWS cloud services such as AWS EventBridge, AWS DataZone, and AWS SCT and DMS to solve data platform challenges.
Each recipe in this book is tailored to a daily challenge that a data engineer team faces while building a cloud platform. By the end of this book, you will be well-versed in AWS data engineering and have gained proficiency in key AWS services and data processing techniques. You will develop the necessary skills to tackle large-scale data challenges with confidence.
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Data Engineering with Python for Beginners
English | 2024 | ISBN: 2940179608172 | Pages: 180 | EPUB (True) | 676.28 KB
"Data Engineering with Python: Comprehensive Clear Guide" is your gateway to the exciting world of data engineering, designed especially for those new to the field. Whether you're an aspiring data engineer, a business analyst, or a developer looking to broaden your skills, this book will provide you with the knowledge and tools you need to work with data and build data pipelines using the versatile Python programming language.
In the digital age, data is the lifeblood of organizations, and the demand for professionals who can effectively collect, process, and transform data has never been higher. This book takes you on a journey from the fundamentals of Python programming to the intricacies of data engineering, giving you the confidence and skills to navigate this dynamic field.
Key Features:
·
Hands-on Learning:
Each chapter includes practical examples, exercises, and step-by-step tutorials, enabling you to apply what you've learned immediately.
·
Real-world Applications:
Dive into real-world case studies and projects, from social media analytics to e-commerce data processing, to see how data engineering is applied in various industries.
·
Comprehensive Coverage:
Gain a deep understanding of data manipulation, data extraction, transformation, data storage, ETL pipelines, data quality, real-time data processing, and more.
·
Python-Focused:
Explore the power of Python as a data engineering tool, utilizing libraries such as Pandas, NumPy, and Apache Airflow, to streamline your data workflows.
·
Best Practices:
Learn from industry best practices, performance optimization techniques, and troubleshooting tips to build robust and efficient data pipelines.
·
Preparation for the Future:
Discover the latest trends and emerging technologies in data engineering, ensuring you stay ahead in this ever-evolving field.
Whether you're looking to embark on a new career path or enhance your existing skills, "Data Engineering with Python" is the perfect guide to help you grasp the essentials of data engineering and set you on the path to becoming a proficient data engineer. Unlock the potential of data and gain the skills to transform it into meaningful insights and valuable information. Get started on your data engineering journey today!
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Data for Joy: Restoring Balance in the Age of Algorithms
English | 2024 | ASIN: B0DG37BY4Y | 202 pages | Epub | 1.71 MB
A Data Scientist's Quest for Digital Wellness and Inner Peace
MIT engineer Phylis Savari witnessed the unfolding of big data in the heart of Silicon Valley. As the tech industry's unchecked ambition collided with ethical dilemmas and personal burnout, a chance encounter in a redwood forest sparked an unexpected journey of self-discovery. Several years later, Phylis launched a company to help others make conscious, healthy choices in the online world. Data for Joy charts a quest to balance logic with intuition, ambition with well-being, and cutting-edge technology with timeless wisdom.
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Data Lakes & Pipelines : A Modern Azure Guide
English | 2025 | ASIN: B0F9HQHNMN | 427 pages | EPUB (True) | 1.70 MB
Unlock the full potential of your data with Data Lakes & Pipelines: A Modern Azure Guide. This comprehensive book is your essential companion for mastering the design and implementation of scalable data architectures on Microsoft Azure.
Aimed at data engineers, architects, and cloud professionals, this guide covers the end-to-end process of building cloud-native data solutions-from ingesting raw data into data lakes to orchestrating robust, automated pipelines for real-time and batch processing. You'll explore key Azure services including Azure Data Factory, Azure Synapse Analytics, Data Lake Storage Gen2, and more, gaining hands-on knowledge and architectural insights.
Through detailed explanations, best practices, and real-world case studies, this book equips you to:
Architect cloud-native data lakes and pipelines
Design efficient ETL and ELT workflows
Integrate structured and unstructured data at scale
Optimize data transformation and orchestration with Azure Data Factory
Ensure data governance, security, and compliance
Leverage Azure Synapse for analytics and BI integration
Whether you're modernizing legacy systems or designing a greenfield data platform, Data Lakes & Pipelines delivers the practical tools and strategic vision needed to thrive in the cloud era of data engineering.
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