Search results for "Data Analytics Toolkit"
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R 580.00
Data Warehouse Toolkit
Updated new edition of Ralph Kimball's groundbreaking book on dimensional modeling for data warehousing and business intelligence! The first edition of Ralph Kimball's The Data Warehouse Toolkit introduced the industry to dimensional modeling, and now his books are considered the most authoritative guides in this space. This new third edition is a complete library of updated dimensional modeling techniques, the most comprehensive collection ever. It covers new and enhanced star schema dimensional modeling patterns, adds two new chapters on ETL techniques, includes new and expanded business matrices for 12 case studies, and more. Authored by Ralph Kimball and Margy Ross, known worldwide as educators, consultants, and influential thought leaders in data warehousing and business intelligenceBegins with fundamental design recommendations and progresses through increasingly complex scenariosPresents unique modeling techniques for business applications such as inventory management, procurement, invoicing, accounting, customer relationship management, big data analytics, and moreDraws real-world case studies from a variety of industries, including retail sales, financial services, telecommunications, education, health care, insurance, e-commerce, and more Design dimensional databases that are easy to understand and provide fast query response with The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling, 3rd Edition.
R 2,015.00
Data Toolkit
How to accelerate analysis into actionUsing data for school improvement is a key goal of Race to the Top, and now is the time to make data-driven school improvement a priority. However, many educators are drowning in data. Boost your professional learning community′s ability to translate data into action with this new book from Pam Robbins and Robert T. Hess. The Data Toolkit provides ten easy-to-use tools that don′t require statistical expertise, can be implemented in a timely manner, and facilitate problem-solving at the classroom, school, and district levels. These proven methods help educators:Frame the questionsDrive the conversationEngage in productive reflectionUncover understandingsCreate a data-driven planAchieve and monitor resultsWritten in an educator-friendly format each chapter contains instructions on using the tool, a sample scenario, and examples—practical resources that will help your PLC be the best it can be.Also included are case studies that show how data teams, PLCs, and individual teachers have used the book′s methods in their own settings. The culminating school improvement mapping tool guides the team through designing an action plan focused on increasing student learning and achievement outcomes.
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R 1,042.00
R 672.00
Microsoft Data Warehouse Toolkit
Best practices and invaluable advice from world-renowned data warehouse experts In this book, leading data warehouse experts from the Kimball Group share best practices for using the upcoming “Business Intelligence release” of SQL Server, referred to as SQL Server 2008 R2. In this new edition, the authors explain how SQL Server 2008 R2 provides a collection of powerful new tools that extend the power of its BI toolset to Excel and SharePoint users and they show how to use SQL Server to build a successful data warehouse that supports the business intelligence requirements that are common to most organizations. Covering the complete suite of data warehousing and BI tools that are part of SQL Server 2008 R2, as well as Microsoft Office, the authors walk you through a full project lifecycle, including design, development, deployment and maintenance. Features more than 50 percent new and revised material that covers the rich new feature set of the SQL Server 2008 R2 release, as well as the Office 2010 releaseIncludes brand new content that focuses on PowerPivot for Excel and SharePoint, Master Data Services, and discusses updated capabilities of SQL Server Analysis, Integration, and Reporting ServicesShares detailed case examples that clearly illustrate how to best apply the techniques described in the bookThe accompanying Web site contains all code samples as well as the sample database used throughout the case studies The Microsoft Data Warehouse Toolkit, Second Edition provides you with the knowledge of how and when to use BI tools such as Analysis Services and Integration Services to accomplish your most essential data warehousing tasks.
R 1,629.00
AI-Assisted Statistics for Data Scientists
Statistical methods are a key part of data science, yet few data scientists have formal statistical training. Courses and books on basic statistics rarely cover the topic from a data science perspective. The third edition of this popular guide expands its practical foundations in R and Python into the modern AI toolkit, with new chapters on neural networks, deep learning, and large language models. Generative AI is integrated throughout, showing how tools such as ChatGPT, Claude, and Gemini work, and how they can support real-world statistical workflows.This book highlights concepts that matter most when working with data, building predictive models, and deploying AI responsibly. If you're comfortable with R or Python and have had some exposure to basic statistics, this concise reference will boost your statistical literacy, your understanding of how AI works, and your confidence in real-world data science and AI projects.Conduct exploratory analysis of data to improve quality and model outcomesApply sampling and experimental design to reduce bias and answer questions with clarityUse regression to understand data-generating processes and detect anomaliesBuild predictive models using classification, clustering, and unsupervised learning with unbalanced data
R 1,824.00
Key Business Analytics
Key Business Analytics will help managers apply tools to turn data into insights that help them better understand their customers, optimize their internal processes and identify cost savings and growth opportunities. It includes analysis techniques within the following categories: Financial analytics – cashflow, profitability, sales forecastsMarket analytics – market size, market trends, marketing channelsCustomer analytics – customer lifetime values, social media, customer needsEmployee analytics – capacity, performance, leadershipOperational analytics – supply chains, competencies, environmental impactBare business analytics – sentiments, text, correlations Each tool will follow the bestselling Key format of being 5-6 pages long, broken into short sharp advice on the essentials: What is it?When should I use it?How do I use it?Tips and pitfallsFurther reading This essential toolkit also provides an invaluable section on how to gather original data yourself through surveys, interviews, focus groups, etc.
R 2,491.40
R for Non-Programmers
Unlock the Power of Data Analysis with RWhether you are a researcher, student, or professional new to programming, this book provides a step-by-step guide to mastering R for quantitative and mixed-methods analysis. Designed for those who still need to gain program- ming experience or wish to learn a new one, it demystifies data analysis, helping you tackle challenges from data wrangling to statistical modelling. Packed with practical examples, engaging explanations, and real-world applications, this book equips you with the tools to analyse data confidently, identify trends, and uncover meaningful insights.Transform Your Approach to ResearchThrough clear instructions and hands-on exercises, you will learn to prepare datasets, explore patterns with descriptive statistics, and create impactful visualisations. You will also gain confidence in performing statistical tests such as comparing groups and building predictive models using regression techniques. This book provides strategies and tools to streamline your workflow, whether handling large datasets, managing missing data, or conducting mixed-methods research.Each chapter builds your expertise incrementally, supported by accessible examples and interactive online training. The accompanying training modules, available through the book’s companion package, offer engaging exercises and extended examples to reinforce learning. These features enable you to practise skills and retain knowledge more effectively.This book, which strongly focuses on reproducible research, is an indispensable guide for anyone looking to enhance their analytical toolkit and unlock R’s full potential for data analysis and statistical modelling.
R 3,114.00
R for Non-Programmers
Unlock the Power of Data Analysis with RWhether you are a researcher, student, or professional new to programming, this book provides a step-by-step guide to mastering R for quantitative and mixed-methods analysis. Designed for those who still need to gain program- ming experience or wish to learn a new one, it demystifies data analysis, helping you tackle challenges from data wrangling to statistical modelling. Packed with practical examples, engaging explanations, and real-world applications, this book equips you with the tools to analyse data confidently, identify trends, and uncover meaningful insights.Transform Your Approach to ResearchThrough clear instructions and hands-on exercises, you will learn to prepare datasets, explore patterns with descriptive statistics, and create impactful visualisations. You will also gain confidence in performing statistical tests such as comparing groups and building predictive models using regression techniques. This book provides strategies and tools to streamline your workflow, whether handling large datasets, managing missing data, or conducting mixed-methods research.Each chapter builds your expertise incrementally, supported by accessible examples and interactive online training. The accompanying training modules, available through the book’s companion package, offer engaging exercises and extended examples to reinforce learning. These features enable you to practise skills and retain knowledge more effectively.This book, which strongly focuses on reproducible research, is an indispensable guide for anyone looking to enhance their analytical toolkit and unlock R’s full potential for data analysis and statistical modelling.
R 10,183.26
R 611.00
R 397.00
R 1,038.00
Learning AI Tools in Tableau
As businesses increasingly rely on data to drive decisions, the role of advanced analytics and AI in enhancing data interpretation is becoming crucial. For professionals tasked with optimizing data analytics platforms like Tableau, staying ahead of the curve with the latest tools isn't just beneficial-it's essential.This insightful guide takes you through the integration of Tableau Pulse and Einstein Copilot, explaining their roles within the broader Tableau and Salesforce ecosystems. Author Ann Jackson, an esteemed analytics professional with a deep expertise in Tableau, offers a step-by-step exploration of these tools, backed by real-world use cases that demonstrate their impact across various industries. By the end of this book, you will:Understand the functionalities of Tableau Pulse and Einstein Copilot and how to use themLearn to deploy Tableau Pulse effectively, ensuring it aligns with your business objectivesNavigate discussions on AI's role within Tableau, enhancing your strategic conversationsVisualize how Tableau Pulse operates through detailed images and scenariosUtilize Einstein Copilot in Tableau Desktop/Prep to streamline and enhance data analysis
R 1,368.00
R 611.00
Sustainability Analytics Toolkit for Practitioners
This book solicits meaningful contributions from key experts and practitioners that have been dealing with the emerging area of sustainability analytics. In doing so, readers would understand the cost, impact and performance of their sustainability initiatives. The book covers current analytical tools (eg: frameworks, standards, ESG indexes) to measure sustainability, and how these tools embed the Sustainable Development Goals (SDGs). In addition to that, a part of the book is also dedicated to the application of sustainability analytics, highlighting key challenges as well as the importance of engagement and communication in shaping the future direction of sustainability assessments. This book will be extremely useful to both researchers and practitioners who are looking for best--in-class practices to create value from their sustainability initiatives.
R 2,422.00
Decision-Making and Analytics
In today's data-driven business world, organizations struggle to extract actionable insights from vast amounts of information. This textbook bridges theory and practice, offering structured approaches to leverage data for enhanced decision-making through machine learning, AI, and optimization modeling—transforming raw data into competitive business intelligence.Decision Making and Analytics: Data-Driven Business Intelligence and Optimization features advanced analytical methodologies paired with real-world implementation studies, creating a progressive learning path from customer behavior analysis through hybrid decision models. By integrating fuzzy logic, neural networks, text mining, and reinforcement learning, it provides a comprehensive toolkit applicable across business scenarios, turning abstract concepts into practical solutions.Serving multiple audiences, this resource bridges the gap between classroom theory and industry practice for students in industrial engineering, business analytics, and management information systems. Practitioners gain applicable methodologies to improve organizational decision-making. At the same time, researchers benefit from cutting-edge approaches across various domains, and policymakers can develop data-informed strategies—addressing the growing demand for professionals who translate data into strategic decisions.The textbook employs open-ended questions that develop analytical reasoning skills without predetermined solutions, better preparing students for real-world complexity. Supporting materials include high-quality figure slides, as well as PowerPoint slides, for qualified adopters, enabling engaging learning environments that effectively communicate complex concepts while building practical, data-driven decision-making skills.
R 5,165.00
R 428.00
Scalable Data Analytics with Azure Data Explorer
Write efficient and powerful KQL queries to query and visualize your data and implement best practices to improve KQL execution performanceKey FeaturesApply Azure Data Explorer best practices to manage your data at scale and reduce KQL execution timeDiscover how to query and visualize your data using the powerful KQLManage cluster performance and monthly costs by understanding how to size your ADX cluster correctlyBook DescriptionAzure Data Explorer (ADX) enables developers and data scientists to make data-driven business decisions. This book will help you rapidly explore and query your data at scale and secure your ADX clusters.The book begins by introducing you to ADX, its architecture, core features, and benefits. You'll learn how to securely deploy ADX instances and navigate through the ADX Web UI, cover data ingestion, and discover how to query and visualize your data using the powerful Kusto Query Language (KQL). Next, you'll get to grips with KQL operators and functions to efficiently query and explore your data, as well as perform time series analysis and search for anomalies and trends in your data. As you progress through the chapters, you'll explore advanced ADX topics, including deploying your ADX instances using Infrastructure as Code (IaC). The book also shows you how to manage your cluster performance and monthly ADX costs by handling cluster scaling and data retention periods. Finally, you'll understand how to secure your ADX environment by restricting access with best practices for improving your KQL query performance.By the end of this Azure book, you'll be able to securely deploy your own ADX instance, ingest data from multiple sources, rapidly query your data, and produce reports with KQL and Power BI.What you will learnBecome well-versed with the core features of the Azure Data Explorer architectureDiscover how ADX can help manage your data at scale on AzureGet to grips with deploying your ADX environment and ingesting and analyzing your dataExplore KQL and learn how to query your dataQuery and visualize your data using the ADX UI and Power BIIngest structured and unstructured data types from an array of sourcesUnderstand how to deploy, scale, secure, and manage ADXWho this book is forThis book is for data analysts, data engineers, and data scientists who are responsible for analyzing and querying their team's large volumes of data on Azure. SRE and DevOps engineers who deploy, maintain, and secure infrastructure will also find this book useful. Prior knowledge of Azure and basic data querying will help you to get the most out of this book.
R 1,889.00
Data-Driven Smart Community Design
This book couples data analytics with social behavioural studies and participatory design to derive deeper insights on city dwellers’ present needs and future aspirations, thereby enabling the development of targeted spatial and programmatic interventions for diverse communities.Public housing in Singapore has been regarded internationally as a success story – and this book outlines the latest strategies and concepts for addressing the emerging social challenges of ageing population, shrinking household size, diverse demographics and widening inequality fostering resilient neighbourhoods. Adopting an interdisciplinary approach, it: • Outlines an innovative data-driven planning process for housing neighbourhood and community design • Provides a framework for planners and designers to synthesize qualitative and quantitative data analyses • Presents a comprehensive set of tested urban analytics tools, digital platforms and participatory toolkits used to design and develop community initiatives.A recommended reading for students undertaking urban planning and design, urban design, housing design, architecture, real estate, urban sociology, and community design, the book’s strategies for evidence-based neighbourhood designs will also appeal to practitioners and policy makers.
R 2,727.54
R 2,603.00
R 306.00
R 813.90
Data Analytics & Visualization All-in-One For Dummies
Install data analytics into your brain with this comprehensive introduction Data Analytics & Visualization All-in-One For Dummies collects the essential information on mining, organizing, and communicating data, all in one place. Clocking in at around 850 pages, this tome of a reference delivers eight books in one, so you can build a solid foundation of knowledge in data wrangling. Data analytics professionals are highly sought after these days, and this book will put you on the path to becoming one. You’ll learn all about sources of data like data lakes, and you’ll discover how to extract data using tools like Microsoft Power BI, organize the data in Microsoft Excel, and visually present the data in a way that makes sense using a Tableau. You’ll even get an intro to the Python, R, and SQL coding needed to take your data skills to a new level. With this Dummies guide, you’ll be well on your way to becoming a priceless data jockey. Mine data from data sourcesOrganize and analyze data Use data to tell a story with TableauExpand your know-how with Python and R New and novice data analysts will love this All-in-One reference on how to make sense of data. Get ready to watch as your career in data takes off.
R 1,175.00
R 782.31
Causal Analytics for Applied Risk Analysis
Causal analytics methods can revolutionize the use of data to make effective decisions by revealing how different choices affect probabilities of various outcomes. This book presents and illustrates models, algorithms, principles, and software for deriving causal models from data and for using them to optimize decisions with uncertain outcomes. It discusses how to describe and summarize situations; detect changes; evaluate effects of policies or interventions; learn what works best under different conditions; predict values of as-yet unobserved quantities from available data; and identify the most likely explanations for observed outcomes, including surprises and anomalies. The book resents practical techniques for causal modeling and analytics that practitioners can apply to improve understanding of how choices affect probabilities of consequences and, based on this understanding, to recommend choices that are more likely to accomplish their intended objectives.The book begins with a survey of modern analytics methods, focusing mainly on techniques useful for decision, risk, and policy analysis. Chapter 2 introduces free in-browser software, including the Causal Analytics Toolkit (CAT) software, to enable readers to perform the analyses described and to apply modern analytics methods easily to their own data sets. Chapters 3 through 11 show how to apply causal analytics and risk analytics to practical risk analysis challenges, mainly related to public and occupational health risks from pathogens in food or from pollutants in air. Chapters 12 through 15 turn to broader questions of how to improve risk management decision-making by individuals, groups, organizations, institutions, and multi-generation societies with different cultures and norms for cooperation. These chapters examine organizational learning, community resilience, societal risk management, and intergenerational collaboration and justice in managing risks.
R 11,007.31
R 416.00
R 1,008.00
R 611.00
Data Analytics for IT Networks
Use data analytics to drive innovation and value throughout your network infrastructure Network and IT professionals capture immense amounts of data from their networks. Buried in this data are multiple opportunities to solve and avoid problems, strengthen security, and improve network performance. To achieve these goals, IT networking experts need a solid understanding of data science, and data scientists need a firm grasp of modern networking concepts. Data Analytics for IT Networks fills these knowledge gaps, allowing both groups to drive unprecedented value from telemetry, event analytics, network infrastructure metadata, and other network data sources. Drawing on his pioneering experience applying data science to large-scale Cisco networks, John Garrett introduces the specific data science methodologies and algorithms network and IT professionals need, and helps data scientists understand contemporary network technologies, applications, and data sources. After establishing this shared understanding, Garrett shows how to uncover innovative use cases that integrate data science algorithms with network data. He concludes with several hands-on, Python-based case studies reflecting Cisco Customer Experience (CX) engineers’ supporting its largest customers. These are designed to serve as templates for developing custom solutions ranging from advanced troubleshooting to service assurance. Understand the data analytics landscape and its opportunities in Networking See how elements of an analytics solution come together in the practical use cases Explore and access network data sources, and choose the right data for your problem Innovate more successfully by understanding mental models and cognitive biases Walk through common analytics use cases from many industries, and adapt them to your environment Uncover new data science use cases for optimizing large networks Master proven algorithms, models, and methodologies for solving network problems Adapt use cases built with traditional statistical methods Use data science to improve network infrastructure analysisAnalyze control and data planes with greater sophistication Fully leverage your existing Cisco tools to collect, analyze, and visualize data
R 1,879.00
Tableau Your Data!
Transform your organization's data into actionable insights with Tableau Tableau is designed specifically to provide fast and easy visual analytics. The intuitive drag-and-drop interface helps you create interactive reports, dashboards, and visualizations, all without any special or advanced training. This all new edition of Tableau Your Data! is your Tableau companion, helping you get the most out of this invaluable business toolset.Tableau Your Data! shows you how to build dynamic, best of breed visualizations using the Tableau Software toolset. This comprehensive guide covers the core feature set for data analytics, and provides clear step-by-step guidance toward best practices and advanced techniques that go way beyond the user manual. You'll learn how Tableau is different from traditional business information analysis tools, and how to navigate your way around the Tableau 9.0 desktop before delving into functions and calculations, as well as sharing with the Tableau Server. Analyze data more effectively with Tableau Desktop Customize Tableau's settings for your organization's needs with detailed real-world examples on data security, scaling, syntax, and moreDeploy visualizations to consumers throughout the enterprise - from sales to marketing, operations to finance, and beyondUnderstand Tableau functions and calculations and leverage Tableau across every link in the value chainLearn from actual working models of the book's visualizations and other web-based resources via a companion website Tableau helps you unlock the stories within the numbers, and Tableau Your Data! puts the software's full functionality right at your fingertips.
R 1,368.00
R 1,527.00
R 737.96
R 916.00
Hands-on Data Analytics for Business
The knowledge and skills of data analytics enable business professionals to make evidence-based decisions rather than just by intuition. To appreciate the knowledge and skills, one needs to understand the theory, hands-on statistical operations using computer software, business application case studies and the analytics project maturity roadmap.Hands-on Data Analytics for Business is a concise all-in-one analytics textbook for business professionals and university students who want to:Understand the essential theories and concepts of data analyticsGrasp hands-on practical statistical and analytics skills step-by-step using SPSS and ExcelAppreciate real-world well-known case studies in human resources, marketing and supply chain on how data analytics is applied in business.This book is for business professionals or university students seeking to master data analytics knowledge and technical skills to a level allowing them to practice data analytics hands-on and manage data analytics projects at scale. For business professionals, the book is written in a way to help learn statistical skills in a concise way with practical real-world examples to inspire business applications. For students, this book is organized in a sequence readily deliverable for a university course, with classes combining theory or concepts, hands-on practice and case studies. For all readers, the book is an essential guide on using data analytics to tackle modern complex activities for companies to gain a competitive edge.
R 2,674.00
Data-Driven Smart Community Design
This book couples data analytics with social behavioural studies and participatory design to derive deeper insights on city dwellers’ present needs and future aspirations, thereby enabling the development of targeted spatial and programmatic interventions for diverse communities.Public housing in Singapore has been regarded internationally as a success story – and this book outlines the latest strategies and concepts for addressing the emerging social challenges of ageing population, shrinking household size, diverse demographics and widening inequality fostering resilient neighbourhoods. Adopting an interdisciplinary approach, it: • Outlines an innovative data-driven planning process for housing neighbourhood and community design • Provides a framework for planners and designers to synthesize qualitative and quantitative data analyses • Presents a comprehensive set of tested urban analytics tools, digital platforms and participatory toolkits used to design and develop community initiatives.A recommended reading for students undertaking urban planning and design, urban design, housing design, architecture, real estate, urban sociology, and community design, the book’s strategies for evidence-based neighbourhood designs will also appeal to practitioners and policy makers.
R 9,325.10
R 1,008.00
R 659.52
R 489.00
R 2,762.00
R 531.00
R 878.00
Fundamentals of Data Analytics
This book introduces the basic methodologies for successful data analytics. Matrix optimization and approximation are explained in detail and extensively applied to dimensionality reduction by principal component analysis and multidimensional scaling. Diffusion maps and spectral clustering are derived as powerful tools. The methodological overlap between data science and machine learning is emphasized by demonstrating how data science is used for classification as well as supervised and unsupervised learning.
R 2,390.18
