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Are waterproof rings better than non-waterproof ones?
Waterproof rings are generally considered better than non-waterproof ones because they are more durable and resistant to damage from water exposure. This makes them ideal for everyday wear, especially for those with active lifestyles or jobs that involve frequent hand washing. Additionally, waterproof rings are less likely to tarnish or lose their shine over time compared to non-waterproof rings. Overall, the added protection and longevity of waterproof rings make them a more practical and reliable choice for most people. **
Where can I find non-toxic and waterproof makeup?
You can find non-toxic and waterproof makeup at various beauty stores and online retailers that specialize in natural and organic beauty products. Look for brands that are certified organic or free from harmful chemicals such as parabens, phthalates, and synthetic fragrances. Additionally, many natural beauty brands offer waterproof options for mascara, eyeliner, and other makeup products. Be sure to read the product labels and ingredients list to ensure that the makeup is both non-toxic and waterproof. **
Bernard Marr Data Strategy: How to Profit from a World of Big Data, Analytics and the Internet of Things - Non Fiction - Paperback
Title:. Data Strategy: How to Profit from a World of Big Data, Analytics and the Internet of Things Condition: BRAND NEW. Format: Paperback Overview:. Data Strategy by Bernard Marr is a practical, hard‑nosed playbook for turning data into real business value in a world where every company operates as a data business. Marr argues that data is not a by‑product but a primary strategic asset—and that most organisations leave vast opportunities untapped because they lack a clear data strategy. This paperback guides leaders through a step‑by‑step blueprint to define strategic data assets, identify the data audience, and establish the collection, governance and infrastructure needed to unlock value. Expect a clear framework for monetising data, from building the right data platforms to applying predictive analytics and machine learning. The book blends theory with real‑world examples from large organisations to illustrate how data strategies translate into smarter decisions, faster product iteration and new revenue streams. Illustrated with practical case studies from major players such as Walmart, RBS, Google and NASA, it shows how data can drive competitive advantage across sectors. For executives, data scientists and managers seeking a concrete path to data‑driven value, this is an indispensable companion. What Makes This Book Stand Out:. What sets Data Strategy apart is its laser focus on action, not abstraction. Bernard Marr equips readers with a tangible language for talking about data—defining strategic data assets, data audiences and the governance layer required to sustain momentum. The book translates complex concepts into executable steps: how to gather the right data, how to design data collection practices, how to prioritise initiatives with measurable business impact, and how to structure teams around data capabilities. The emphasis on monetisation—turning data into revenue, savings and competitive advantage—gives this title a practical edge that distinguishes it from more theoretical texts. The inclusion of concrete, real‑world examples helps readers visualise the end game: a data‑driven organisation that makes smarter decisions at every level. Who This Book Is Perfect For:. This book is a must‑read for senior leaders and decision‑makers who need to translate data into business outcomes: CEOs, COOs, CIOs, CMOs, data and analytics leaders, and strategy professionals. It’s equally valuable for heads of risk, product managers and IT executives looking to align data initiatives with corporate strategy. Students and professionals seeking a clear map of how to move from data collection to value creation will also find it highly relevant. If you’re leading a digital transformation and want a pragmatic framework that teams can rally around, Data Strategy outlines the playbook you’ll want in your corner. Key Highlights:. Clear framework for identifying and prioritising strategic data assets. Practical steps to build data governance, architecture...
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Daniel Jones Programming For Beginners Excel Programming And Data Analytics 10 Books Collection Set - Non Fiction - Paperback
Title:. Programming for Beginners: 10 Books in 1- 5 Books of Excel Programming+ 5 Books of Data Analytics Condition: BRAND NEW. Format: Paperback Overview:. This is the ultimate beginner-friendly compilation designed to demystify programming for everyday office tasks. Programming for Beginners: 10 Books in 1- 5 Books of Excel Programming+ 5 Books of Data Analytics condenses a wide range of essential skills into one comprehensive paperback. Inside, readers will explore Visual Basic for Applications (VBA), the powerhouse language that helps you automate repetitive Excel tasks and extend the capabilities of the Microsoft Office suite. The guide uses a practical, step-by-step approach so even newcomers can write their first macro with confidence, then expand into broader Excel automation, data handling, and basic analytics workflows. The “10 Books in 1” format presents a structured, incremental path: five books focused on Excel programming and macros, and five books dedicated to data analytics within a familiar spreadsheet environment. This makes the volume ideal for self-paced learners, students, professionals, admins, or anyone seeking to save time and improve accuracy through automation. The paperback format is perfect for hands-on practice, note-taking, and quick reference as you apply what you learn to real-world tasks. What Makes This Book Stand Out:. What sets this collection apart is its integrated, beginner-first design. Rather than hopping between disparate resources, you get a cohesive, progress-oriented pathway that starts with the fundamentals of VBA and macro recording, then gradually introduces You’ll learn how to automate routine Excel workflows, from data entry and formatting to complex reporting. The Data Analytics books extend those same skills into data preparation, cleaning, and interpretation, so you don’t just write code—you extract meaningful insights. The 10-in-1 format offers tremendous value: a single purchase that builds practical competence across Excel programming and data analytics, with consistent terminology, practical examples, and hands-on exercises. It’s ideal for learners who want tangible results quickly, without juggling multiple titles. Who This Book Is Perfect For:. This collection is tailor-made for absolute beginners who crave practical, outcome-focused learning. It suits students starting a stats or business analytics course, professionals looking to automate their workflow in Excel, office administrators aiming to reduce manual tasks, and small business owners who want to turn raw data into clean, shareable insights. It also functions well as a classroom or workshop companion, offering a structured path from zero to confident VBA practitioner. If you want a single, reliable resource that grows with you—from recording a macro to building data-driven dashboards—this 10-in-1 volume is a compelling fit. Key Highlights:. Comprehensive 10-in-1 format covering Excel programming and data analytics...
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Data Game: The Story of Liverpool FC's Analytics Revolution by Josh WilliamsDescription. Data Game: The Story of Liverpool FC's Analytics Revolution explores how Liverpool rose to greatness in the 21st century with the help of big data.. Written by Josh Williams, sports podcaster and frequent contributor to Redmen TV and The Anfield Wrap.. The Anfield institution is an industry leader in the field of data science, but little is known about how Liverpool's relationship with numbers began. Josh Williams explores this untold story and explores the historic club’s unique relationship with data and analytics.. Title. Data Game: The Story of Liverpool FC's Analytics Revolution by Josh Williams. Delivery. Content. Reviews99,99 £*Shipping: 0,00 £Secure redirect to the provider
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Nigel Guenole The Power of People: Workforce Analytics for Business Performance - Non Fiction - PaperbackTitle:. The Power of People: Learn How Successful Organizations Use Workforce Analytics To Improve Business Performance Condition: BRAND NEW. Format: Paperback Overview:. Transforming the immense potential of workforce analytics into reality isn’t easy. The Power of People translates advanced analytics into practical, everyday decisions that drive real business results. Drawing on incisive case studies and candid vignettes, three seasoned experts guide you through the winds and weather of a workforce analytics project—from the very first question to the moment you present reliable, actionable insights to stakeholders. You’ll learn how to design robust research, choose the right metrics, and build a compelling narrative that aligns people data with business outcomes. The book offers a clear roadmap: where to start, how to secure essential sponsorship, and how to deliver “quick wins” that prove value and unlock momentum for bigger initiatives. Whether you’re a CHRO steering a multiyear analytics program, a data practitioner hungry for context, or a manager seeking evidence to support people decisions, this book makes complex analytics approachable, transferable, and ultimately transformative for your organization. What Makes This Book Stand Out:. What sets The Power of People apart is its insistence on practical rigor without sacrificing readability. It doesn’t drown you in theory; it immerses you in real-world challenges—data quality issues, stakeholder negotiations, and the politics of change. The three expert authors blend research discipline with hands-on storytelling, offering concrete steps, checklists, and evaluation criteria that teams can implement immediately. The book emphasizes the why as much as the how: it explains which questions matter most to leaders, how to frame analyses to reveal business drivers, and how to translate findings into actionable recommendations that people can act on today. By weaving case studies with structured guidance, it helps you build credibility, secure funding, and sustain momentum across multiple analytics initiatives, turning a promising concept into enduring business performance improvements. Who This Book Is Perfect For:. This is the essential handbook for senior HR and analytics professionals who want to turn people data into competitive advantage. It’s equally valuable for CHROs, CFOs, and operations leaders seeking a practical framework to govern workforce analytics. Data scientists and HR analysts will appreciate the emphasis on robust research design and reliable insights, while line managers and team leaders will value the clear, decision-ready recommendations. If you’re assembling an analytics program, delivering quarterly people metrics, or driving change where workforce data informs strategy, this book will become a trusted reference—and a catalyst for measurable business impact. Key Highlights:. Three experts combine analytics expertise with real-world experience to guide your project from...18,47 £*Shipping: 2,99 £Secure redirect to the provider
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Computer Science Academy Python For Data Analysis - Non Fiction - PaperbackTitle:. Python for Data Analysis: A Complete Guide for Beginners, Including Python Statistics and Big Data Analysis Condition: BRAND NEW. Format: Paperback Overview:. Step into the world of data with a practical, hands-on introduction to Python that turns complexity into clarity. This complete guide for beginners shows you how to transform raw numbers into meaningful stories, using Python as your tool of choice. From scripting the basics to mastering essential data-analysis workflows, you’ll learn-by-doing through approachable explanations, real-world datasets, and guided projects. The book blends core programming concepts with practical statistics and big-data techniques, so you can analyze trends, test hypotheses, and visualize results with confidence. Whether you’re a student starting a data science journey, a professional seeking to upskill, or a curious self-learner, this paperback is designed to be your reliable companion. You’ll encounter clear, concise code samples, step-by-step instructions, and checklists that keep you moving forward, even if you don’t have a formal math background. By the end, you’ll be able to clean, manipulate, and analyze data sets, perform basic statistical analyses, and present findings in compelling visuals. Importantly, the guide uses a structured, friendly pace that builds usable skills you can apply to projects in finance, marketing, science, or technology. It’s a practical, modern doorway to Python-powered data insight. What Makes This Book Stand Out:. Why this guide rises above other introductions is not just what you learn, but how you learn it. The book pairs plain-language explanations with hands-on practice, guiding you through short, focused exercises that cement concepts before moving on. It emphasizes real-world data and accessible statistics, helping you translate numbers into narratives you can act on. Clear, copyable code examples show you exactly how to implement techniques, while step-by-step workflows model a repeatable approach to data analysis that you can reuse on future projects. The inclusion of big-data basics means you’ll understand the considerations and constraints of working with large datasets, from sampling to performance. The tone stays encouraging and practical, avoiding intimidating theory while building confidence through small wins. If you’re building a portfolio, the book’s projects are designed to be ready for presentation as standalone notebooks, demonstrations for interviews, or classroom assignments. In short, this guide turns a potentially daunting subject into a straightforward, repeatable process you can rely on again and again. Who This Book Is Perfect For:. Whether you’re a student starting out in data science, a professional pivoting into analytics, or a curious hobbyist who wants to decode data behind the headlines, this paperback is for you. It’s ideal for readers new to programming who want a practical, results-focused introduction to Python for data analysis. The...14,97 £*Shipping: 2,99 £Secure redirect to the provider
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Designing Data-Intensive Applications by Martin Kleppmann - Non Fiction - PaperbackTitle:. Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems Condition: BRAND NEW. Format: Paperback Overview:. Designing Data-Intensive Applications is a practical, rigorously grounded guide for software engineers, data engineers, and system architects who are building the backbone of modern applications. From the very first pages, the book demystifies the big questions that keep data teams awake at night: how to keep data reliable as systems scale, how to balance consistency with availability, and how to design architectures that endure change. Kleppmann leads you through the core ideas that underpin reliable, scalable, and maintainable data systems—models of data, storage engines, and the anatomy of data flows—then dives into the hard, real-world trade-offs faced when choosing between batch and streaming processing, replication and partitioning, and the guarantees provided by different technologies. The narrative blends clear theory with concrete patterns and concrete case studies, translating abstract concepts into practical guidance you can apply in production from day one. This paperback remains a staple for anyone eyeing long-term stability in data platforms, whether you’re rebuilding legacy pipelines, designing a new data-first service, or preparing for system-design conversations with peers and leaders. What Makes This Book Stand Out:. What sets Designing Data-Intensive Applications apart is its emphasis on mental models that travel across technologies. Kleppmann sidesteps hype and focuses on the enduring questions: how data is stored, how it moves through a system, and how to keep it correct when failures happen. The book threads together four pillars—data models, data storage and retrieval, data processing, and distributed systems—into a cohesive framework you can apply to any scale. You’ll discover principled ways to reason about consistency, latency, throughput, and fault tolerance, plus practical guidance on building robust architectures that tolerate partial failures without collapsing. The narrative leans on accessible explanations, crisp diagrams, and real-world scenarios, making complex topics approachable for experienced developers while still valuable to aspiring engineers. The result is a reference you’ll return to again and again as your systems evolve and your workload grows. Who This Book Is Perfect For:. This book is the essential read for software engineers, data engineers, and system designers who are responsible for data-driven applications. It’s ideal for teams migrating to distributed architectures, architects planning scalable platforms, and engineers preparing for system-design interviews. It also serves as a valuable resource for tech leads and CTOs who need a clear, language-agnostic view of the trade-offs that shape data infrastructure. Whether you’re at a startup building your first data pipeline or at an established tech company optimizing complex storage and...38,99 £*Shipping: 0,00 £Secure redirect to the provider
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Can a non-waterproof phone come into contact with rain?
Yes, a non-waterproof phone can come into contact with rain, but it is not recommended. Rain can potentially damage the phone if it gets wet, leading to malfunctions or permanent damage. It is best to protect the phone from rain by using a waterproof case or keeping it in a safe, dry place when it is raining. **
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How can I remove fly droppings from lacquered, non-waterproof beech and spruce wood?
To remove fly droppings from lacquered, non-waterproof beech and spruce wood, you can start by gently wiping the affected area with a soft, dry cloth to remove any loose droppings. Then, mix a small amount of mild dish soap with warm water and use a soft cloth to gently clean the area. Be sure to dry the wood thoroughly after cleaning to prevent any water damage. If the droppings are stubborn, you can try using a small amount of white vinegar mixed with water to help break down the droppings before wiping them away. Always test any cleaning solution on a small, inconspicuous area of the wood first to ensure it does not cause any damage. **
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Are SEO backlinks from link seller sites sometimes useful?
SEO backlinks from link seller sites are generally not useful and can even be harmful to a website's search engine rankings. Link seller sites often engage in black hat SEO tactics, such as buying and selling links, which violate search engine guidelines. These links are often low quality and irrelevant, and search engines like Google can penalize websites that engage in these practices. It's important to focus on building high-quality, relevant backlinks through organic means, such as creating valuable content and engaging in outreach to reputable websites in your industry. **
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What are non-operational data?
Non-operational data refers to information that is not directly related to the day-to-day operations of a business or organization. This type of data is often used for analysis, reporting, and decision-making purposes rather than for immediate operational use. Non-operational data can include historical sales data, customer demographics, market research findings, and other information that provides insights into the overall performance and trends of the business. This data is valuable for strategic planning and long-term decision-making. **
Packt Publishing Machine Learning for Data Mining: Advanced Predictive Modeling Techniques for Data Analysis - Non Fiction - Paperback
Title:. Machine Learning for Data Mining: Improve your data mining capabilities with advanced predictive modeling Condition: BRAND NEW. Format: Paperback. ISBN: 9781838828974 Overview:. Machine Learning for Data Mining offers a practical, hands-on pathway to elevate your data mining projects with advanced predictive modeling. Authored by Jesus Salcedo and published by Packt Publishing in 2019 as a first edition, this paperback guide is written for data scientists, analysts, and students who want to blend the strengths of machine learning with traditional data mining techniques. The book demystifies when and how to apply various ML methods within data mining workflows, from initial data preparation to final model deployment. You’ll learn a clear, step-by-step approach to building, evaluating, and refining predictive models, with an emphasis on interpretability and actionable insights. Topics include selecting the right algorithm for different data landscapes, designing robust experiments, handling real-world data challenges, and translating model outcomes into business value. The tone remains practical and outcome-focused, guiding you through common pitfalls such as overfitting, data leakage, and imbalanced datasets. If you’re aiming to upgrade your toolkit and deliver data-driven decisions with confidence, this is a essential companion for your data science journey. What Makes This Book Stand Out:. What sets this guide apart is its deliberate integration of machine learning techniques into data mining practice, giving you a concrete blueprint for smarter analyses. Salcedo emphasizes a pragmatic, results-first mindset: choose the right ML approach based on the data, validate it rigorously, and interpret outcomes in business terms. Unlike theory-only texts, this book foregrounds actionable steps—feature engineering strategies, model selection criteria, and stepwise evaluation plans—that you can apply immediately to real datasets. The content is designed to help you improve model development and performance in a range of contexts, from fraud detection and customer analytics to operational monitoring and beyond. By focusing on when and how to apply each technique, the book helps you avoid common missteps and accelerate the journey from data to decision. Who This Book Is Perfect For:. This book is ideal for data scientists, data analysts, and ML practitioners who want to deepen their data mining capabilities with predictive modeling. It also serves students and researchers seeking practical, implementable guidance on combining ML with data mining workflows. If you’re responsible for turning large, messy datasets into reliable insights, or you’re preparing for projects in market research, security analytics, or IoT data streams, this accessible paperback will become a go-to reference. Beginners will appreciate the clear, step-by-step approach, while more experienced readers will value the concrete techniques and decision-making frameworks that speed up...
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Data Science for Business: What You Need to Know About Data Mining by Foster Provost - Non Fiction - Paperback
Title:. Data Science for Business: What you need to know about data mining and data-analytic thinking Condition: BRAND NEW. Format: Paperback Overview:. Data Science for Business is a definitive, accessible primer that introduces the core ideas behind data science and shows how data-analytic thinking can drive practical business value. Written by two of the field’s most respected voices, Foster Provost and Tom Fawcett, this paperback guides readers through the fundamental principles that underpin successful data-driven decision-making. Based on Provost’s widely taught MBA course at New York University, the book grounds theory in real-world business problems, illustrating how data mining techniques translate into tangible outcomes for organisations across sectors. Whether you’re a manager seeking to collaborate more effectively with data scientists, a professional aiming to contribute to analytics projects, or a student exploring how numbers inform strategy, this book offers clear explanations, useful frameworks, and practical insights. You’ll learn to frame questions in data terms, interpret models with business context, and communicate findings with stakeholders in non-technical language. By the end, you’ll see why data science is not just a toolkit but a decision-support mindset that can shape strategy, risk management, and competitive advantage. What Makes This Book Stand Out:. This book stands out for its uniquely business-centric approach to data science. Provost and Fawcett demystify data mining and modelling with straightforward language, vivid examples, and a focus on decision-making rather than equations. The emphasis on data-analytic thinking — a disciplined way of asking the right questions, framing hypotheses, and evaluating outcomes — equips readers to engage confidently in analytics conversations, even if they’re not hands-on programmers. Across chapters, the authors weave practical frameworks that help you map data capabilities to business goals, assess risks, and avoid common pitfalls such as over-reliance on a single metric. The real-world case-style narratives demonstrate how analytics informs pricing, customer segmentation, product development, and forecasting, making the material immediately relevant to day-to-day business decisions. The blend of theory, accessible explanations, and actionable guidance makes this a rare resource: a university-grade foundation that’s genuinely useful in industry settings. Who This Book Is Perfect For:. This book is ideal for business professionals who want to understand what data science can do for their organisations without getting lost in technical detail. It’s especially well suited for managers, product owners, marketing leaders, operations coaches, and strategy teams who need to bridge the gap between business objectives and technical execution. It’s also an excellent starting point for MBA students, aspiring data scientists, and analysts who want to articulate the business value of...
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With which tool can one find SEO keywords?
One tool that can be used to find SEO keywords is Google Keyword Planner. This tool allows users to search for keywords and get information on their search volume, competition, and potential cost per click. Another popular tool is SEMrush, which provides keyword research and competitive analysis. Both of these tools can help identify relevant keywords to target for SEO optimization. **
What tools are available for SEO optimization?
There are several tools available for SEO optimization, including keyword research tools such as Google Keyword Planner and SEMrush, which help identify relevant keywords for a website. On-page optimization tools like Yoast SEO and Moz Pro can help optimize content and meta tags for better search engine visibility. Additionally, tools like Google Search Console and Bing Webmaster Tools provide insights into a website's performance and help identify and fix technical SEO issues. Finally, backlink analysis tools like Ahrefs and Majestic can help monitor and improve a website's link profile for better search rankings. **
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Bernard Marr Data Strategy: How to Profit from a World of Big Data, Analytics and the Internet of Things - Non Fiction - PaperbackTitle:. Data Strategy: How to Profit from a World of Big Data, Analytics and the Internet of Things Condition: BRAND NEW. Format: Paperback Overview:. Data Strategy by Bernard Marr is a practical, hard‑nosed playbook for turning data into real business value in a world where every company operates as a data business. Marr argues that data is not a by‑product but a primary strategic asset—and that most organisations leave vast opportunities untapped because they lack a clear data strategy. This paperback guides leaders through a step‑by‑step blueprint to define strategic data assets, identify the data audience, and establish the collection, governance and infrastructure needed to unlock value. Expect a clear framework for monetising data, from building the right data platforms to applying predictive analytics and machine learning. The book blends theory with real‑world examples from large organisations to illustrate how data strategies translate into smarter decisions, faster product iteration and new revenue streams. Illustrated with practical case studies from major players such as Walmart, RBS, Google and NASA, it shows how data can drive competitive advantage across sectors. For executives, data scientists and managers seeking a concrete path to data‑driven value, this is an indispensable companion. What Makes This Book Stand Out:. What sets Data Strategy apart is its laser focus on action, not abstraction. Bernard Marr equips readers with a tangible language for talking about data—defining strategic data assets, data audiences and the governance layer required to sustain momentum. The book translates complex concepts into executable steps: how to gather the right data, how to design data collection practices, how to prioritise initiatives with measurable business impact, and how to structure teams around data capabilities. The emphasis on monetisation—turning data into revenue, savings and competitive advantage—gives this title a practical edge that distinguishes it from more theoretical texts. The inclusion of concrete, real‑world examples helps readers visualise the end game: a data‑driven organisation that makes smarter decisions at every level. Who This Book Is Perfect For:. This book is a must‑read for senior leaders and decision‑makers who need to translate data into business outcomes: CEOs, COOs, CIOs, CMOs, data and analytics leaders, and strategy professionals. It’s equally valuable for heads of risk, product managers and IT executives looking to align data initiatives with corporate strategy. Students and professionals seeking a clear map of how to move from data collection to value creation will also find it highly relevant. If you’re leading a digital transformation and want a pragmatic framework that teams can rally around, Data Strategy outlines the playbook you’ll want in your corner. Key Highlights:. Clear framework for identifying and prioritising strategic data assets. Practical steps to build data governance, architecture...17,97 £*Shipping: 2,99 £Secure redirect to the provider
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Daniel Jones Programming For Beginners Excel Programming And Data Analytics 10 Books Collection Set - Non Fiction - PaperbackTitle:. Programming for Beginners: 10 Books in 1- 5 Books of Excel Programming+ 5 Books of Data Analytics Condition: BRAND NEW. Format: Paperback Overview:. This is the ultimate beginner-friendly compilation designed to demystify programming for everyday office tasks. Programming for Beginners: 10 Books in 1- 5 Books of Excel Programming+ 5 Books of Data Analytics condenses a wide range of essential skills into one comprehensive paperback. Inside, readers will explore Visual Basic for Applications (VBA), the powerhouse language that helps you automate repetitive Excel tasks and extend the capabilities of the Microsoft Office suite. The guide uses a practical, step-by-step approach so even newcomers can write their first macro with confidence, then expand into broader Excel automation, data handling, and basic analytics workflows. The “10 Books in 1” format presents a structured, incremental path: five books focused on Excel programming and macros, and five books dedicated to data analytics within a familiar spreadsheet environment. This makes the volume ideal for self-paced learners, students, professionals, admins, or anyone seeking to save time and improve accuracy through automation. The paperback format is perfect for hands-on practice, note-taking, and quick reference as you apply what you learn to real-world tasks. What Makes This Book Stand Out:. What sets this collection apart is its integrated, beginner-first design. Rather than hopping between disparate resources, you get a cohesive, progress-oriented pathway that starts with the fundamentals of VBA and macro recording, then gradually introduces You’ll learn how to automate routine Excel workflows, from data entry and formatting to complex reporting. The Data Analytics books extend those same skills into data preparation, cleaning, and interpretation, so you don’t just write code—you extract meaningful insights. The 10-in-1 format offers tremendous value: a single purchase that builds practical competence across Excel programming and data analytics, with consistent terminology, practical examples, and hands-on exercises. It’s ideal for learners who want tangible results quickly, without juggling multiple titles. Who This Book Is Perfect For:. This collection is tailor-made for absolute beginners who crave practical, outcome-focused learning. It suits students starting a stats or business analytics course, professionals looking to automate their workflow in Excel, office administrators aiming to reduce manual tasks, and small business owners who want to turn raw data into clean, shareable insights. It also functions well as a classroom or workshop companion, offering a structured path from zero to confident VBA practitioner. If you want a single, reliable resource that grows with you—from recording a macro to building data-driven dashboards—this 10-in-1 volume is a compelling fit. Key Highlights:. Comprehensive 10-in-1 format covering Excel programming and data analytics...39,97 £*Shipping: 0,00 £Secure redirect to the provider
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Data Game: The Story of Liverpool FC's Analytics Revolution by Josh WilliamsDescription. Data Game: The Story of Liverpool FC's Analytics Revolution explores how Liverpool rose to greatness in the 21st century with the help of big data.. Written by Josh Williams, sports podcaster and frequent contributor to Redmen TV and The Anfield Wrap.. The Anfield institution is an industry leader in the field of data science, but little is known about how Liverpool's relationship with numbers began. Josh Williams explores this untold story and explores the historic club’s unique relationship with data and analytics.. Title. Data Game: The Story of Liverpool FC's Analytics Revolution by Josh Williams. Delivery. Content. Reviews99,99 £*Shipping: 0,00 £Secure redirect to the provider
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Nigel Guenole The Power of People: Workforce Analytics for Business Performance - Non Fiction - PaperbackTitle:. The Power of People: Learn How Successful Organizations Use Workforce Analytics To Improve Business Performance Condition: BRAND NEW. Format: Paperback Overview:. Transforming the immense potential of workforce analytics into reality isn’t easy. The Power of People translates advanced analytics into practical, everyday decisions that drive real business results. Drawing on incisive case studies and candid vignettes, three seasoned experts guide you through the winds and weather of a workforce analytics project—from the very first question to the moment you present reliable, actionable insights to stakeholders. You’ll learn how to design robust research, choose the right metrics, and build a compelling narrative that aligns people data with business outcomes. The book offers a clear roadmap: where to start, how to secure essential sponsorship, and how to deliver “quick wins” that prove value and unlock momentum for bigger initiatives. Whether you’re a CHRO steering a multiyear analytics program, a data practitioner hungry for context, or a manager seeking evidence to support people decisions, this book makes complex analytics approachable, transferable, and ultimately transformative for your organization. What Makes This Book Stand Out:. What sets The Power of People apart is its insistence on practical rigor without sacrificing readability. It doesn’t drown you in theory; it immerses you in real-world challenges—data quality issues, stakeholder negotiations, and the politics of change. The three expert authors blend research discipline with hands-on storytelling, offering concrete steps, checklists, and evaluation criteria that teams can implement immediately. The book emphasizes the why as much as the how: it explains which questions matter most to leaders, how to frame analyses to reveal business drivers, and how to translate findings into actionable recommendations that people can act on today. By weaving case studies with structured guidance, it helps you build credibility, secure funding, and sustain momentum across multiple analytics initiatives, turning a promising concept into enduring business performance improvements. Who This Book Is Perfect For:. This is the essential handbook for senior HR and analytics professionals who want to turn people data into competitive advantage. It’s equally valuable for CHROs, CFOs, and operations leaders seeking a practical framework to govern workforce analytics. Data scientists and HR analysts will appreciate the emphasis on robust research design and reliable insights, while line managers and team leaders will value the clear, decision-ready recommendations. If you’re assembling an analytics program, delivering quarterly people metrics, or driving change where workforce data informs strategy, this book will become a trusted reference—and a catalyst for measurable business impact. Key Highlights:. Three experts combine analytics expertise with real-world experience to guide your project from...18,47 £*Shipping: 2,99 £Secure redirect to the provider
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Are waterproof rings better than non-waterproof ones?
Waterproof rings are generally considered better than non-waterproof ones because they are more durable and resistant to damage from water exposure. This makes them ideal for everyday wear, especially for those with active lifestyles or jobs that involve frequent hand washing. Additionally, waterproof rings are less likely to tarnish or lose their shine over time compared to non-waterproof rings. Overall, the added protection and longevity of waterproof rings make them a more practical and reliable choice for most people. **
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Where can I find non-toxic and waterproof makeup?
You can find non-toxic and waterproof makeup at various beauty stores and online retailers that specialize in natural and organic beauty products. Look for brands that are certified organic or free from harmful chemicals such as parabens, phthalates, and synthetic fragrances. Additionally, many natural beauty brands offer waterproof options for mascara, eyeliner, and other makeup products. Be sure to read the product labels and ingredients list to ensure that the makeup is both non-toxic and waterproof. **
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Can a non-waterproof phone come into contact with rain?
Yes, a non-waterproof phone can come into contact with rain, but it is not recommended. Rain can potentially damage the phone if it gets wet, leading to malfunctions or permanent damage. It is best to protect the phone from rain by using a waterproof case or keeping it in a safe, dry place when it is raining. **
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How can I remove fly droppings from lacquered, non-waterproof beech and spruce wood?
To remove fly droppings from lacquered, non-waterproof beech and spruce wood, you can start by gently wiping the affected area with a soft, dry cloth to remove any loose droppings. Then, mix a small amount of mild dish soap with warm water and use a soft cloth to gently clean the area. Be sure to dry the wood thoroughly after cleaning to prevent any water damage. If the droppings are stubborn, you can try using a small amount of white vinegar mixed with water to help break down the droppings before wiping them away. Always test any cleaning solution on a small, inconspicuous area of the wood first to ensure it does not cause any damage. **
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Computer Science Academy Python For Data Analysis - Non Fiction - PaperbackTitle:. Python for Data Analysis: A Complete Guide for Beginners, Including Python Statistics and Big Data Analysis Condition: BRAND NEW. Format: Paperback Overview:. Step into the world of data with a practical, hands-on introduction to Python that turns complexity into clarity. This complete guide for beginners shows you how to transform raw numbers into meaningful stories, using Python as your tool of choice. From scripting the basics to mastering essential data-analysis workflows, you’ll learn-by-doing through approachable explanations, real-world datasets, and guided projects. The book blends core programming concepts with practical statistics and big-data techniques, so you can analyze trends, test hypotheses, and visualize results with confidence. Whether you’re a student starting a data science journey, a professional seeking to upskill, or a curious self-learner, this paperback is designed to be your reliable companion. You’ll encounter clear, concise code samples, step-by-step instructions, and checklists that keep you moving forward, even if you don’t have a formal math background. By the end, you’ll be able to clean, manipulate, and analyze data sets, perform basic statistical analyses, and present findings in compelling visuals. Importantly, the guide uses a structured, friendly pace that builds usable skills you can apply to projects in finance, marketing, science, or technology. It’s a practical, modern doorway to Python-powered data insight. What Makes This Book Stand Out:. Why this guide rises above other introductions is not just what you learn, but how you learn it. The book pairs plain-language explanations with hands-on practice, guiding you through short, focused exercises that cement concepts before moving on. It emphasizes real-world data and accessible statistics, helping you translate numbers into narratives you can act on. Clear, copyable code examples show you exactly how to implement techniques, while step-by-step workflows model a repeatable approach to data analysis that you can reuse on future projects. The inclusion of big-data basics means you’ll understand the considerations and constraints of working with large datasets, from sampling to performance. The tone stays encouraging and practical, avoiding intimidating theory while building confidence through small wins. If you’re building a portfolio, the book’s projects are designed to be ready for presentation as standalone notebooks, demonstrations for interviews, or classroom assignments. In short, this guide turns a potentially daunting subject into a straightforward, repeatable process you can rely on again and again. Who This Book Is Perfect For:. Whether you’re a student starting out in data science, a professional pivoting into analytics, or a curious hobbyist who wants to decode data behind the headlines, this paperback is for you. It’s ideal for readers new to programming who want a practical, results-focused introduction to Python for data analysis. The...14,97 £*Shipping: 2,99 £Secure redirect to the provider
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Designing Data-Intensive Applications by Martin Kleppmann - Non Fiction - PaperbackTitle:. Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems Condition: BRAND NEW. Format: Paperback Overview:. Designing Data-Intensive Applications is a practical, rigorously grounded guide for software engineers, data engineers, and system architects who are building the backbone of modern applications. From the very first pages, the book demystifies the big questions that keep data teams awake at night: how to keep data reliable as systems scale, how to balance consistency with availability, and how to design architectures that endure change. Kleppmann leads you through the core ideas that underpin reliable, scalable, and maintainable data systems—models of data, storage engines, and the anatomy of data flows—then dives into the hard, real-world trade-offs faced when choosing between batch and streaming processing, replication and partitioning, and the guarantees provided by different technologies. The narrative blends clear theory with concrete patterns and concrete case studies, translating abstract concepts into practical guidance you can apply in production from day one. This paperback remains a staple for anyone eyeing long-term stability in data platforms, whether you’re rebuilding legacy pipelines, designing a new data-first service, or preparing for system-design conversations with peers and leaders. What Makes This Book Stand Out:. What sets Designing Data-Intensive Applications apart is its emphasis on mental models that travel across technologies. Kleppmann sidesteps hype and focuses on the enduring questions: how data is stored, how it moves through a system, and how to keep it correct when failures happen. The book threads together four pillars—data models, data storage and retrieval, data processing, and distributed systems—into a cohesive framework you can apply to any scale. You’ll discover principled ways to reason about consistency, latency, throughput, and fault tolerance, plus practical guidance on building robust architectures that tolerate partial failures without collapsing. The narrative leans on accessible explanations, crisp diagrams, and real-world scenarios, making complex topics approachable for experienced developers while still valuable to aspiring engineers. The result is a reference you’ll return to again and again as your systems evolve and your workload grows. Who This Book Is Perfect For:. This book is the essential read for software engineers, data engineers, and system designers who are responsible for data-driven applications. It’s ideal for teams migrating to distributed architectures, architects planning scalable platforms, and engineers preparing for system-design interviews. It also serves as a valuable resource for tech leads and CTOs who need a clear, language-agnostic view of the trade-offs that shape data infrastructure. Whether you’re at a startup building your first data pipeline or at an established tech company optimizing complex storage and...38,99 £*Shipping: 0,00 £Secure redirect to the provider
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Packt Publishing Machine Learning for Data Mining: Advanced Predictive Modeling Techniques for Data Analysis - Non Fiction - PaperbackTitle:. Machine Learning for Data Mining: Improve your data mining capabilities with advanced predictive modeling Condition: BRAND NEW. Format: Paperback. ISBN: 9781838828974 Overview:. Machine Learning for Data Mining offers a practical, hands-on pathway to elevate your data mining projects with advanced predictive modeling. Authored by Jesus Salcedo and published by Packt Publishing in 2019 as a first edition, this paperback guide is written for data scientists, analysts, and students who want to blend the strengths of machine learning with traditional data mining techniques. The book demystifies when and how to apply various ML methods within data mining workflows, from initial data preparation to final model deployment. You’ll learn a clear, step-by-step approach to building, evaluating, and refining predictive models, with an emphasis on interpretability and actionable insights. Topics include selecting the right algorithm for different data landscapes, designing robust experiments, handling real-world data challenges, and translating model outcomes into business value. The tone remains practical and outcome-focused, guiding you through common pitfalls such as overfitting, data leakage, and imbalanced datasets. If you’re aiming to upgrade your toolkit and deliver data-driven decisions with confidence, this is a essential companion for your data science journey. What Makes This Book Stand Out:. What sets this guide apart is its deliberate integration of machine learning techniques into data mining practice, giving you a concrete blueprint for smarter analyses. Salcedo emphasizes a pragmatic, results-first mindset: choose the right ML approach based on the data, validate it rigorously, and interpret outcomes in business terms. Unlike theory-only texts, this book foregrounds actionable steps—feature engineering strategies, model selection criteria, and stepwise evaluation plans—that you can apply immediately to real datasets. The content is designed to help you improve model development and performance in a range of contexts, from fraud detection and customer analytics to operational monitoring and beyond. By focusing on when and how to apply each technique, the book helps you avoid common missteps and accelerate the journey from data to decision. Who This Book Is Perfect For:. This book is ideal for data scientists, data analysts, and ML practitioners who want to deepen their data mining capabilities with predictive modeling. It also serves students and researchers seeking practical, implementable guidance on combining ML with data mining workflows. If you’re responsible for turning large, messy datasets into reliable insights, or you’re preparing for projects in market research, security analytics, or IoT data streams, this accessible paperback will become a go-to reference. Beginners will appreciate the clear, step-by-step approach, while more experienced readers will value the concrete techniques and decision-making frameworks that speed up...22,97 £*Shipping: 2,99 £Secure redirect to the provider
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Data Science for Business: What You Need to Know About Data Mining by Foster Provost - Non Fiction - PaperbackTitle:. Data Science for Business: What you need to know about data mining and data-analytic thinking Condition: BRAND NEW. Format: Paperback Overview:. Data Science for Business is a definitive, accessible primer that introduces the core ideas behind data science and shows how data-analytic thinking can drive practical business value. Written by two of the field’s most respected voices, Foster Provost and Tom Fawcett, this paperback guides readers through the fundamental principles that underpin successful data-driven decision-making. Based on Provost’s widely taught MBA course at New York University, the book grounds theory in real-world business problems, illustrating how data mining techniques translate into tangible outcomes for organisations across sectors. Whether you’re a manager seeking to collaborate more effectively with data scientists, a professional aiming to contribute to analytics projects, or a student exploring how numbers inform strategy, this book offers clear explanations, useful frameworks, and practical insights. You’ll learn to frame questions in data terms, interpret models with business context, and communicate findings with stakeholders in non-technical language. By the end, you’ll see why data science is not just a toolkit but a decision-support mindset that can shape strategy, risk management, and competitive advantage. What Makes This Book Stand Out:. This book stands out for its uniquely business-centric approach to data science. Provost and Fawcett demystify data mining and modelling with straightforward language, vivid examples, and a focus on decision-making rather than equations. The emphasis on data-analytic thinking — a disciplined way of asking the right questions, framing hypotheses, and evaluating outcomes — equips readers to engage confidently in analytics conversations, even if they’re not hands-on programmers. Across chapters, the authors weave practical frameworks that help you map data capabilities to business goals, assess risks, and avoid common pitfalls such as over-reliance on a single metric. The real-world case-style narratives demonstrate how analytics informs pricing, customer segmentation, product development, and forecasting, making the material immediately relevant to day-to-day business decisions. The blend of theory, accessible explanations, and actionable guidance makes this a rare resource: a university-grade foundation that’s genuinely useful in industry settings. Who This Book Is Perfect For:. This book is ideal for business professionals who want to understand what data science can do for their organisations without getting lost in technical detail. It’s especially well suited for managers, product owners, marketing leaders, operations coaches, and strategy teams who need to bridge the gap between business objectives and technical execution. It’s also an excellent starting point for MBA students, aspiring data scientists, and analysts who want to articulate the business value of...24,85 £*Shipping: 2,99 £Secure redirect to the provider
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Are SEO backlinks from link seller sites sometimes useful?
SEO backlinks from link seller sites are generally not useful and can even be harmful to a website's search engine rankings. Link seller sites often engage in black hat SEO tactics, such as buying and selling links, which violate search engine guidelines. These links are often low quality and irrelevant, and search engines like Google can penalize websites that engage in these practices. It's important to focus on building high-quality, relevant backlinks through organic means, such as creating valuable content and engaging in outreach to reputable websites in your industry. **
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What are non-operational data?
Non-operational data refers to information that is not directly related to the day-to-day operations of a business or organization. This type of data is often used for analysis, reporting, and decision-making purposes rather than for immediate operational use. Non-operational data can include historical sales data, customer demographics, market research findings, and other information that provides insights into the overall performance and trends of the business. This data is valuable for strategic planning and long-term decision-making. **
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With which tool can one find SEO keywords?
One tool that can be used to find SEO keywords is Google Keyword Planner. This tool allows users to search for keywords and get information on their search volume, competition, and potential cost per click. Another popular tool is SEMrush, which provides keyword research and competitive analysis. Both of these tools can help identify relevant keywords to target for SEO optimization. **
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What tools are available for SEO optimization?
There are several tools available for SEO optimization, including keyword research tools such as Google Keyword Planner and SEMrush, which help identify relevant keywords for a website. On-page optimization tools like Yoast SEO and Moz Pro can help optimize content and meta tags for better search engine visibility. Additionally, tools like Google Search Console and Bing Webmaster Tools provide insights into a website's performance and help identify and fix technical SEO issues. Finally, backlink analysis tools like Ahrefs and Majestic can help monitor and improve a website's link profile for better search rankings. **
* All prices are inclusive of VAT and, if applicable, plus shipping costs. The offer information is based on the details provided by the respective shop and is updated through automated processes. Real-time updates do not occur, so deviations can occur in individual cases. ** Note: Parts of this content were created by AI.