One of the most influential data visualization books—updated with new techniques, technologies, and examples Visualize This demonstrates how to explain data visually, so that you can present and communicate information in a way that is appealing and easy to understand. Today, there is a continuous flow of data available to answer almost any question. Thoughtful charts, maps, and analysis can help us make sense of this data. But the data does not speak for itself. As leading data expert Nathan Yau explains in this book, graphics provide little value unless they are built upon a firm understanding of the data behind them. Visualize This teaches you a data-first approach from a practical point of view. You'll start by exploring what your data has to say, and then you'll design visualizations that are both remarkable and meaningful. With this book, you'll discover what tools are available to you without becoming overwhelmed with options. You'll be exposed to a variety of software and code and jump right into real-world datasets so that you can learn visualization by doing. You'll learn to ask and answer questions with data, so that you can make charts that are both beautiful and useful. Visualize This also provides you with opportunities to apply what you learn to your own data. This completely updated, full-color second edition: Presents a unique approach to visualizing and telling stories with data, from data visualization expert Nathan Yau Offers step-by-step tutorials and practical design tips for creating statistical graphics, geographical maps, and information design Details tools that can be used to visualize data graphics for reports, presentations, and stories, for the web or for print, with major updates for the latest R packages, Python libraries, JavaScript libraries, illustration software, and point-and-click applications Contains numerous examples and descriptions of patterns and outliers and explains how to show them Information designers, analysts, journalists, statisticians, data scientists—as well as anyone studying for careers in these fields—will gain a valuable background in the concepts and techniques of data visualization, thanks to this legendary book.

This project-oriented book presents a hands-on approach to identifying migration and performance issues with experience drawn from real-world examples. As you work through the book, you will develop skills, knowledge, and deep understanding of Snowflake tuning options and capabilities while preparing for later incorporation of additional Snowflake features as they become available. Your Snowflake platform will cost less to run and will improve your customer experience. Written by a seasoned Snowflake practitioner, this book is full of practical, hands-on guidance and advice specifically designed to further accelerate your Snowflake journey. Tuning the Snowflake Data Cloud provides you a pathway to success by equipping you with the skills, knowledge, and expertise needed to elevate your Snowflake experience. The book shows you how to leverage what you already know, adds what you don’t, and helps you apply it toward delivering for your Snowflake accounts. Read this book to embark on a voyage of advancement and equip your organization to deliver consistent Snowflake performance. What You Will Learn Recognize and understand the root cause of performance bottlenecks Know how to resolve performance issues Develop a deep understanding of Snowflake performance tuning options Reduce expensive mistakes, remediate poorly performing code Manage Snowflake costs

Discover the power of Looker for Business Intelligence and data visualization in this comprehensive cookbook. This book serves as your guide to mastering Looker's tools and features, enabling you to transform data into actionable insights. What this Book will help me do Understand Looker's key components, including LookML and dashboards. Explore advanced Looker capabilities, including data modeling and interactivity. Create dynamic dashboards to monitor and present critical metrics effectively. Integrate Looker with additional tools and systems to extend its capabilities. Leverage Looker's tools for fostering data-driven decision-making within your team. Author(s) Khrystyna Grynko is a seasoned data professional with extensive experience in Business Intelligence and analytics. She brings practical insights into how to effectively utilize Looker for real-world applications. Khrystyna is known for her clear, instructional writing style that makes complex topics approachable. Who is it for? This book is an essential resource for business analysts, data analysts, or BI developers looking to expand their expertise in Looker. Suitable for readers with a basic understanding of business intelligence concepts. Ideal for professionals who aim to leverage Looker for creating insightful and interactive data applications to inform business strategy.

Everything you need to implement stream processing on Apache KafkaⓇ using Kafka Streams and the kqsIDB event streaming database. Kafka Streams in Action, Second Edition guides you through setting up and maintaining your streaming processing with Kafka. Inside, you’ll find comprehensive coverage of not only Kafka Streams, but the entire toolbox you’ll need for effective streaming—from the components of the Kafka ecosystem, to Producer and Consumer clients, Connect, and Schema Registry. In Kafka Streams in Action, Second Edition you’ll learn how to: Design streaming applications in Kafka Streams with the KStream and the Processor API Integrate external systems with Kafka Connect Enforce data compatibility with Schema Registry Build applications that respond immediately to events in either Kafka Streams or ksqlDB Craft materialized views over streams with ksqlDB This totally revised new edition of Kafka Streams in Action has been expanded to cover more of the Kafka platform used for building event-based applications. You’ll also find full coverage of ksqlDB, an event streaming database that makes it a snap to create applications that respond immediately to events, such as real-time push and pull updates. About the Technology Enterprise applications need to handle thousands—even millions—of data events every day. With an intuitive API and flawless reliability, the lightweight Kafka Streams library has earned a spot at the center of these systems. Kafka Streams provides exactly the power and simplicity you need to manage real-time event processing or microservices messaging. About the Book Kafka Streams in Action, Second Edition teaches you how to create event streaming applications on the amazing Apache Kafka platform. This thoroughly revised new edition now covers a wider range of streaming architectures and includes data integration with Kafka Connect. As you go, you’ll explore real-world examples that introduce components and brokers, schema management, and the other essentials. Along the way, you’ll pick up practical techniques for blending Kafka with Spring, low-level control of processors and state stores, storing event data with ksqlDB, and testing streaming applications. What's Inside Design efficient streaming applications Integrate external systems with Kafka Connect Enforce data compatibility with Schema Registry About the Reader For Java developers. No knowledge of Kafka or streaming applications required. About the Author Bill Bejeck is a Confluent engineer and a Kafka Streams contributor with over 15 years of software development experience. Bill is also a committer on the Apache KafkaⓇ project. Quotes Comprehensive streaming data applications are only a few years away from becoming the reality, and this book is the guide the industry has been waiting for to move beyond the hype. - Adi Polak, Director, Developer Experience Engineering, Confluent Covers all the key aspects of building applications with Kafka Streams. Whether you are getting started with stream processing or have already built Kafka Streams applications, it is an essential resource. - Mickael Maison, Principal Software Engineer, Red Hat Serves as both a learning and a resource guide, offering a perfect blend of ‘how-to’ and ‘why-to.’ Even if you have been using Kafka Streams for many years, I highly recommend this book. - Neil Buesing, CTO & Co-founder, Kinetic Edge

Concepts of Database Management System is designed to meet the syllabi requirements of undergraduate students of computer applications and computer science. It describes the concepts in an easy-to-understand language with sufficient number of examples. The overview of emerging trends in databases is thoroughly explained. A brief introduction to PL/SQL, MS-Access and Oracle is discussed to help students get a flavor of different types of database management systems.

This IBM® Redbooks® publication describes the new member of the IBM Z® family, IBM z14™. IBM z14 is the trusted enterprise platform for pervasive encryption, integrating data, transactions, and insights into the data. A data-centric infrastructure must always be available with a 99.999% or better availability, have flawless data integrity, and be secured from misuse. It also must be an integrated infrastructure that can support new applications. Finally, it must have integrated capabilities that can provide new mobile capabilities with real-time analytics that are delivered by a secure cloud infrastructure. IBM z14 servers are designed with improved scalability, performance, security, resiliency, availability, and virtualization. The superscalar design allows z14 servers to deliver a record level of capacity over the prior IBM Z platforms. In its maximum configuration, z14 is powered by up to 170 client characterizable microprocessors (cores) running at 5.2 GHz. This configuration can run more than 146,000 million instructions per second (MIPS) and up to 32 TB of client memory. The IBM z14 Model M05 is estimated to provide up to 35% more total system capacity than the IBM z13® Model NE1. This Redbooks publication provides information about IBM z14 and its functions, features, and associated software support. More information is offered in areas that are relevant to technical planning. It is intended for systems engineers, consultants, planners, and anyone who wants to understand the IBM Z servers functions and plan for their usage. It is intended as an introduction to mainframes. Readers are expected to be generally familiar with existing IBM Z technology and terminology.

This IBM® Redbooks® publication describes the new member of the IBM Z® family, IBM z14™ Model ZR1 (Machine Type 3907). It includes information about the Z environment and how it helps integrate data and transactions more securely, and can infuse insight for faster and more accurate business decisions. The z14 ZR1 is a state-of-the-art data and transaction system that delivers advanced capabilities, which are vital to any digital transformation. The z14 ZR1 is designed for enhanced modularity, in an industry standard footprint. A data-centric infrastructure must always be available with a 99.999% or better availability, have flawless data integrity, and be secured from misuse. It also must be an integrated infrastructure that can support new applications. Finally, it must have integrated capabilities that can provide new mobile capabilities with real-time analytics that are delivered by a secure cloud infrastructure. IBM z14 ZR1 servers are designed with improved scalability, performance, security, resiliency, availability, and virtualization. The superscalar design allows z14 ZR1 servers to deliver a record level of capacity over the previous IBM Z platforms. In its maximum configuration, z14 ZR1 is powered by up to 30 client characterizable microprocessors (cores) running at 4.5 GHz. This configuration can run more than 29,000 million instructions per second and up to 8 TB of client memory. The IBM z14 Model ZR1 is estimated to provide up to 54% more total system capacity than the IBM z13s® Model N20. This Redbooks publication provides information about IBM z14 ZR1 and its functions, features, and associated software support. More information is offered in areas that are relevant to technical planning. It is intended for systems engineers, consultants, planners, and anyone who wants to understand the IBM Z servers functions and plan for their usage. It is intended as an introduction to mainframes. Readers are expected to be generally familiar with IBM Z technology and terminology.

This IBM® Redbooks® publication describes the features and functions the latest member of the IBM Z® platform, the IBM z15™ (machine type 8561). It includes information about the IBM z15 processor design, I/O innovations, security features, and supported operating systems. The z15 is a state-of-the-art data and transaction system that delivers advanced capabilities, which are vital to any digital transformation. The z15 is designed for enhanced modularity, which is in an industry standard footprint. This system excels at the following tasks: Making use of multicloud integration services Securing data with pervasive encryption Accelerating digital transformation with agile service delivery Transforming a transactional platform into a data powerhouse Getting more out of the platform with IT Operational Analytics Accelerating digital transformation with agile service delivery Revolutionizing business processes Blending open source and Z technologies This book explains how this system uses new innovations and traditional Z strengths to satisfy growing demand for cloud, analytics, and open source technologies. With the z15 as the base, applications can run in a trusted, reliable, and secure environment that improves operations and lessens business risk.

This IBM® Redbooks® publication describes the features and functions the latest member of the IBM Z® platform, the IBM z15™ Model T02 (machine type 8562). It includes information about the IBM z15 processor design, I/O innovations, security features, and supported operating systems. The z15 is a state-of-the-art data and transaction system that delivers advanced capabilities, which are vital to any digital transformation. The z15 is designed for enhanced modularity, which is in an industry standard footprint. This system excels at the following tasks: Making use of multicloud integration services Securing data with pervasive encryption Accelerating digital transformation with agile service delivery Transforming a transactional platform into a data powerhouse Getting more out of the platform with IT Operational Analytics Accelerating digital transformation with agile service delivery Revolutionizing business processes Blending open source and Z technologies This book explains how this system uses new innovations and traditional Z strengths to satisfy growing demand for cloud, analytics, and open source technologies. With the z15 as the base, applications can run in a trusted, reliable, and secure environment that improves operations and lessens business risk.

This thoroughly updated and expanded second edition covers traditional nonparametric methods and rank-based analyses. Two new chapters covering multivariate analyses and big data have been added. Core classical nonparametrics chapters on one- and two-sample problems have been expanded

The problem of forecasting future values of economic and physical processes, the problem of restoring lost information, cleaning signals or other data observations from noise, is magnified in an information-laden word. Methods of stochastic processes estimation depend on two main factors. The first factor is construction of a model of the process being investigated. The second factor is the available information about the structure of the process under consideration. In this book, we propose results of the investigation of the problem of mean square optimal estimation (extrapolation, interpolation, and filtering) of linear functionals depending on unobserved values of stochastic sequences and processes with periodically stationary and long memory multiplicative seasonal increments. Formulas for calculating the mean square errors and the spectral characteristics of the optimal estimates of the functionals are derived in the case of spectral certainty, where spectral structure of the considered sequences and processes are exactly known. In the case where spectral densities of the sequences and processes are not known exactly while some sets of admissible spectral densities are given, we apply the minimax-robust method of estimation.

The surging predictive analytics market is expected to grow from $10.5 billion today to $28 billion by 2026. With the rise in automation across industries, the increase in data-driven decision-making, and the proliferation of IoT devices, predictive analytics has become an operational necessity in today's forward-thinking companies. If you're a data professional, you need to be aligned with your company's business activities more than ever before. This practical book provides the background, tools, and best practices necessary to help you design, implement, and operationalize predictive analytics on-premises or in the cloud. Explore ways that predictive analytics can provide direct input back to your business Understand mathematical tools commonly used in predictive analytics Learn the development frameworks used in predictive analytics applications Appreciate the role of predictive analytics in the machine learning process Examine industry implementations of predictive analytics Build, train, and retrain predictive models using Python and TensorFlow

Dive into the Databricks Data Intelligence Platform and learn how to harness its full potential for creating, deploying, and maintaining machine learning solutions. This book covers everything from setting up your workspace to integrating state-of-the-art tools such as AutoML and VectorSearch, imparting practical skills through detailed examples and code. What this Book will help me do Set up and manage a Databricks workspace tailored for effective data science workflows. Implement monitoring to ensure data quality and detect drift efficiently. Build, fine-tune, and deploy machine learning models seamlessly using Databricks tools. Operationalize AI projects including feature engineering, data pipelines, and workflows on the Databricks Lakehouse architecture. Leverage integrations with popular tools like OpenAI's ChatGPT to expand your AI project capabilities. Author(s) This book is authored by Stephanie Rivera, Anastasia Prokaieva, Amanda Baker, and Hayley Horn, seasoned experts in data science and machine learning from Databricks. Their collective years of expertise in big data and AI technologies ensure a rich and insightful perspective. Through their work, they strive to make complex concepts accessible and actionable. Who is it for? This book serves as an ideal guide for machine learning engineers, data scientists, and technically inclined managers. It's well-suited for those transitioning to the Databricks environment or seeking to deepen their Databricks-based machine learning implementation skills. Whether you're an ambitious beginner or an experienced professional, this book provides clear pathways to success.

This book is designed to meet the requirements of students and is intended for beginners to help them understand the concepts from the first principles. Spread across 16 chapters, it discusses the theoretical aspects that have been refined and updated to reflect the current developments in the subjects. It expounds on theoretical concepts that have immense practical applications, giving adequate proofs to establish significant theorems.

Book Contents –

Chapter 1: Probability Chapter 2: Random Variables (Discrete and Continuous) Chapter 3: Mathematical Expectation Chapter 4: Standard Discrete Distributions Chapter 5: Standard Continuous Distributions Chapter 6: Sampling Theory and Distribution Chapter 7: Testing of Hypothesis (Large Samples) Chapter 8: Test of Hypothesis (Small Samples) Chapter 9: Estimation Chapter 10: Curve Fitting Chapter 11: Correlation Chapter 12: Regression Chapter 13: Queuing Theory Chapter 14: Design of Experiments Chapter 15: Random Process Chapter 16: Advanced Random Process Appendix A, Appendix B, Appendix C, Appendix D Index

MATLAB provides an interactive programming interface for numerical computation and data visualization making it the default framework used for analysis, design and research in many domains of science and industry. Programming in MATLAB is intended as an aid to engineers and scientists with no prior programming expertise. The book focuses on the systematic development of practical programming skills through MATLAB language constructs, backed by several well-designed examples and exercises. Designed to be as much a MATLAB reference tool for researchers in varied fields as it is a guide for undergraduate readers, the book builds on the concepts sequentially as it progresses through the chapters. Each chapter is complete, independent of the book's remaining contents. Thus, for teaching purposes, one can suitably the relevant portions.

About The Authors –

Ramnarayan Patel did his Ph.D. in the area of power systems from Indian Institute of Technology Delhi, in 2003. He received his M.Tech. from IIT Delhi and a graduate degree in electrical engineering from SGSITS, Indore. His manifold fields of interest include power system stability, optimization in electric power systems, application of artificial intelligence techniques, design of intelligent controllers and renewable energy systems. He has over 14 years of hands-on experience working with MATLAB and Simulink, as an instructor, researcher and trainer.

Dr Patel has served as faculty in the electrical engineering department at IIT Roorkee and at the Birla Institute of Technology and Science, Pilani. Currently, he is Professorin the Department of Electrical and Electronics Engineering, Shri Shankaracharya Technical Campus (SSGI), Bhilai, and has many publications to his credit in various international journals of repute. He has presented his research at various international conferences and organized many workshops and conferences within the country. He is a recipient of the prestigious ‘Career Award for Young Teachers’ from All India Council for Technical Education (AICTE), New Delhi. Dr Patel has successfully handled many research projects funded by AICTE, New Delhi, and Department of Science and Technology, Government of India, New Delhi.

Ankush Mittal received his B.Tech. in computer science and engineering from Indian Institute of Technology Delhi in 1996, and later, his Master’s degree in 1998 from the same institute. He received his Ph.D. degree in electrical and computer engineering from the National University of Singapore in 2001 and was a faculty member in the Department of Computer Science, National University of Singapore, for two years. He has also served as Associate Professor at IIT Roorkee. Currently, he is Director (Research) at Graphic Era University, Dehradun.

Dr Mittal has contributed more than 250 research papers in journals and conferences of high repute with significant impact in academic circles. A dedicated teacher and active researcher, he is a recipient of the IIT Roorkee Outstanding Teacher Award and the IBM Faculty Award. He has taught more than 20 courses and worked on MATLAB extensively since his Ph.D.

Book Contents –

1. Introduction to MATLAB® Desktop
2. Matrix Operations and Applications
3. MATLAB® Graphics and Plotting
4. Control Structures, Loops, and File Handling
5. Scripts and Functions
6. Numerical Methods, Calculus, and Statistics
7. Using Memory Efficiently
8. Using the MATLAB® Debugger and Profiler
9. Efficient Coding Using Vectorization Technique
10. Precision and Errors
11. Advanced Concepts in MATLAB®
12. Modeling with Simulink®
13. Digital Image Processing Index

Express Learning is a series of books designed as quick reference guides to important undergraduate computer courses. The organized and accessible format of these books allows students to learn important concepts in an easy-to-understand, question-and-answer format. These portable learning tools have been designed as one-stop references for students to understand and master the subjects by themselves.

Features –

• Designed as a student-friendly self-learning guide. The book is written in a clear, concise, and lucid manner. • Easy-to-understand question-and-answer format. • Includes previously asked as well as new questions organized in chapters. • All types of questions including MCQs, short and long questions are covered. • Solutions to numerical questions asked at examinations are provided. • All ideas and concepts are presented with clear examples. • Text is well structured and well supported with suitable diagrams. • Inter-chapter dependencies are kept to a minimum

Book Contents –

1: Database System 2: Conceptual Modelling 3: Relational Model 4: Relational Algebra and Calculus 5: Structured Query Language 6: Relational Database Design 7: Data Storage and Indexing 8: Query Processing and Optimization 9: Introduction to Transaction Processing 10: Concurrency Control Techniques 11: Database Recovery System 12: Database Security 13: Database System Architecture 14: Data Warehousing, OLAP, and Data Mining 15: Information Retrieval 16: Miscellaneous Questions

Express Learning is a series of books designed as quick reference guides to important undergraduate courses. The organized and accessible format of these books allows students to learn important concepts in an easy-to-understand, question-and-answer format. These portable learning tools have been designed as one-stop references for students to understand and master the subjects by themselves.

Book Contents –

Chapter 1: Introduction to Data Warehouse Chapter 2: Building a Data Warehouse Chapter 3: Data Warehouse: Architecture Chapter 4: OLAP Technology Chapter 5: Introduction to Data Mining Chapter 6: Data Preprocessing Chapter 7: Mining Association Rules Chapter 8: Classification and Prediction Chapter 9: Cluster Analysis Chapter 10: Advanced Techniques of Data Mining and Its Applications Index

Many organizations today analyze and share large, sensitive datasets about individuals. Whether these datasets cover healthcare details, financial records, or exam scores, it's become more difficult for organizations to protect an individual's information through deidentification, anonymization, and other traditional statistical disclosure limitation techniques. This practical book explains how differential privacy (DP) can help. Authors Ethan Cowan, Michael Shoemate, and Mayana Pereira explain how these techniques enable data scientists, researchers, and programmers to run statistical analyses that hide the contribution of any single individual. You'll dive into basic DP concepts and understand how to use open source tools to create differentially private statistics, explore how to assess the utility/privacy trade-offs, and learn how to integrate differential privacy into workflows. With this book, you'll learn: How DP guarantees privacy when other data anonymization methods don't What preserving individual privacy in a dataset entails How to apply DP in several real-world scenarios and datasets Potential privacy attack methods, including what it means to perform a reidentification attack How to use the OpenDP library in privacy-preserving data releases How to interpret guarantees provided by specific DP data releases

Large language models (LLMs) and diffusion models such as ChatGPT and Stable Diffusion have unprecedented potential. Because they have been trained on all the public text and images on the internet, they can make useful contributions to a wide variety of tasks. And with the barrier to entry greatly reduced today, practically any developer can harness LLMs and diffusion models to tackle problems previously unsuitable for automation. With this book, you'll gain a solid foundation in generative AI, including how to apply these models in practice. When first integrating LLMs and diffusion models into their workflows, most developers struggle to coax reliable enough results from them to use in automated systems. Authors James Phoenix and Mike Taylor show you how a set of principles called prompt engineering can enable you to work effectively with AI. Learn how to empower AI to work for you. This book explains: The structure of the interaction chain of your program's AI model and the fine-grained steps in between How AI model requests arise from transforming the application problem into a document completion problem in the model training domain The influence of LLM and diffusion model architecture—and how to best interact with it How these principles apply in practice in the domains of natural language processing, text and image generation, and code

Radically improve the quality of your data visualizations by employing core principles of color, typography, chart types, data storytelling, and more. Everyday Data Visualization is a field guide for design techniques that will improve the charts, reports, and data dashboards you build every day. Everything you learn is tool-agnostic, with universal principles you can apply to any data stack. In Everyday Data Visualization you’ll learn important design principles for the most common data visualizations: Harness the power of perception to guide a user’s attention Bring data to life with color and typography Choose the best chart types for your data story Design for interactive visualizations Keep the user’s needs first throughout your projects This book gives you the tools you need to bring your data to life with clarity, precision, and flair. You’ll learn how human brains perceive and process information, wield modern accessibility standards, get the basics of color theory and typography, and more. About the Technology Even mundane presentations like charts, dashboards, and infographics can become engaging and inspiring data stories! This book shows you how to upgrade the visualizations you create every day by improving the layout, typography, color, and accessibility. You’ll discover timeless principles of design that help you highlight important features, compensate for missing information, and interact with live data flows. About the Book Everyday Data Visualization guides you through basic graphic design for the most common types of data visualization. You’ll learn how to enhance charts with color, encourage users to interact and explore data and create visualizations accessible to everyone. Along the way, you’ll practice each new skill as you take a dashboard project from research to publication. What's Inside Bring data to life with color and typography Choose the best chart types for your data story Design interactive visualizations About the Reader For readers experienced with data analysis tools. About the Author Desireé Abbott has over a decade of experience in product analytics, business intelligence, science, design, and software engineering. The technical editor on this book was Michael Petrey. Quotes A delightful blend of data viz principles, guidance, and design tips. The treasure trove of insights I wish I had years ago! - Alli Torban, Author of Chart Spark With vibrant enthusiasm and engaging conversational style, this book shines. - RJ Andrews, data storyteller Elegantly simplifies complex concepts, making them accessible even to beginners. An enlightening journey. - Renato Sinohara, Westwing Group SE Desiree’s approachable writing style makes it easy to dive straight into this book, and you’re in deep before you even know it. I guarantee you’ll learn plenty. - Neil Richards, 5xTableau Visionary, Author of Questions in Dataviz