Big data
Joshua N. Milligan
Learning Tableau strengthens your command on Tableau fundamentals and builds on advanced topics.The book starts by taking you through foundational principles of Tableau. We then demonstrate various types of connections and how to work with metadata. We teach you to use a wide variety of visualizations to analyze and communicate the data, and introduce you to calculations and parameters. We then take an in-depth look at level of detail (LOD) expressions and use them to solve complex data challenges. Up next, we show table calculations, how to extend and alter default visualizations, build an interactive dashboard, and master the art of telling stories with data.This Tableau book will introduce you to visual statistical analytics capabilities, create different types of visualizations and dynamic dashboards for rich user experiences. We then move on to maps and geospatial visualization, and the new Data Model capabilities introduced in Tableau 2020.2. You will further use Tableau Prep’s ability to clean and structure data and share the stories contained in your data.By the end of this book, you will be proficient in implementing the powerful features of Tableau 2020 for decision-making.
Joshua N. Milligan
Learning Tableau strengthens your command on Tableau fundamentals and builds on advanced topics.The book starts by taking you through foundational principles of Tableau. We then demonstrate various types of connections and how to work with metadata. We teach you to use a wide variety of visualizations to analyze and communicate the data, and introduce you to calculations and parameters. We then take an in-depth look at level of detail (LOD) expressions and use them to solve complex data challenges. Up next, we show table calculations, how to extend and alter default visualizations, build an interactive dashboard, and master the art of telling stories with data.This Tableau book will introduce you to visual statistical analytics capabilities, create different types of visualizations and dynamic dashboards for rich user experiences. We then move on to maps and geospatial visualization, and the new Data Model capabilities introduced in Tableau 2020.2. You will further use Tableau Prep’s ability to clean and structure data and share the stories contained in your data.By the end of this book, you will be proficient in implementing the powerful features of Tableau 2020 for decision-making.
Joshua N. Milligan
Tableau 2025 marks a new era in data visualization and analysis, bringing together advanced AI integrations and dynamic user experiences. This sixth edition, written by Tableau Visionary and Zen Master Joshua Miligan, is an end-to-end guide to mastering the latest innovations in Tableau that transform raw data into actionable insights.This edition introduces groundbreaking features like Tableau AI (including Tableau Pulse and Tableau Agent), enhancing your analytical capabilities with AI-driven data exploration and automated insights. With detailed walkthroughs, you’ll learn to build dynamic dashboards that respond to your data in real time and work with sophisticated AI functionalities that predict trends and model scenarios.Whether you're a seasoned data professional or new to Tableau, this book provides the tools you need to leverage Tableau’s full potential. From integrating diverse data sources using the enhanced data model to employing advanced geospatial functions for detailed mapping, every chapter is packed with expert knowledge and practical applications designed to put powerful analytics at your fingertips.*Email sign-up and proof of purchase required
Jos Dirksen
If you know JavaScript and want to start creating 3D graphics that run in any browser, this book is a great choice for you. You don't need to know anything about math or WebGL; all that you need is general knowledge of JavaScript and HTML.
Akhil Arora, Shrey Mehrotra
Today enterprises generate huge volumes of data. In order to provide effective services and to make smarter and more intelligent decisions from these huge volumes of data, enterprises use big-data analytics. In recent years, Hadoop has been used for massive data storage and efficient distributed processing of data. The Yet Another Resource Negotiator (YARN) framework solves the design problems related to resource management faced by the Hadoop 1.x framework by providing a more scalable, efficient, flexible, and highly available resource management framework for distributed data processing.This book starts with an overview of the YARN features and explains how YARN provides a business solution for growing big data needs. You will learn to provision and manage single, as well as multi-node, Hadoop-YARN clusters in the easiest way. You will walk through the YARN administration, life cycle management, application execution, REST APIs, schedulers, security framework and so on. You will gain insights about the YARN components and features such as ResourceManager, NodeManager, ApplicationMaster, Container, Timeline Server, High Availability, Resource Localisation and so on.The book explains Hadoop-YARN commands and the configurations of components and explores topics such as High Availability, Resource Localization and Log aggregation. You will then be ready to develop your own ApplicationMaster and execute it over a Hadoop-YARN cluster.Towards the end of the book, you will learn about the security architecture and integration of YARN with big data technologies like Spark and Storm. This book promises conceptual as well as practical knowledge of resource management using YARN.
Liczby w HR. Matematyczne ramy najbardziej ludzkiej części biznesu
Anna Morawiec-Bartosik
Czy pracę działu HR da się zmierzyć? Współczesny biznes liczbami stoi. Wykresy, tabele, przetwarzanie danych, analizowanie wyników z przeszłości, prognozowanie sprzedaży, zakupów i produkcji... Większość działów w dużych przedsiębiorstwach wspiera się tym, co policzalne. Większość, ale raczej nie dział human resources. Dlaczego? Czyżby HR-owcy nie wierzyli w liczby i stawiali na intuicję? Może. A może po prostu brakuje im rzetelnych narzędzi, dzięki którym można przeanalizować dane, jakie są dostępne dla osób wyspecjalizowanych w zarządzaniu zasobami ludzkimi firmy? Do niedawna działy HR uchodziły powszechnie za najbardziej niemierzalne w przedsiębiorstwach. Ostatnio jednak ten trend się zmienia. Takie pojęcia jak data-based HR czy data-driven HR z roku na rok zyskują na popularności. Zarządzający firmami, a także sami pracownicy human resources chcą mierzyć efektywność coraz większej liczby procesów personalnych, by na podstawie uzyskanych wyników móc planować przyszłe działania. Tylko co mierzyć? Jakimi metodami to robić? Odpowiedzi na te i inne pytania związane z analityką zasobów ludzkich znajdziesz w tej książce. Ta książka pomoże Ci zbudować lub wzmocnić rolę analityki HR w Twojej firmie, pomoże także w rozwijaniu umiejętności i perspektywy analityków HR oraz przekona zarząd i biznes, że warto zainwestować czas i fundusze w rozwijanie tej części biznesu. Wskaże jasne cele analityki personalnej, przeprowadzi Cię krok po kroku przez najważniejsze aspekty liczb w HR, które będziesz mógł wykorzystać w swojej firmie. Przede wszystkim książka pomoże Ci w znalezieniu wspólnego języka z biznesem, finansami i zarządem ― a językiem tym są właśnie dane.
Prashant Kumar Mishra, Mukesh Kumar
Azure Synapse Analytics, which Microsoft describes as the next evolution of Azure SQL Data Warehouse, is a limitless analytics service that brings enterprise data warehousing and big data analytics together. With this book, you'll learn how to discover insights from your data effectively using this platform.The book starts with an overview of Azure Synapse Analytics, its architecture, and how it can be used to improve business intelligence and machine learning capabilities. Next, you'll go on to choose and set up the correct environment for your business problem. You'll also learn a variety of ways to ingest data from various sources and orchestrate the data using transformation techniques offered by Azure Synapse. Later, you'll explore how to handle both relational and non-relational data using the SQL language. As you progress, you'll perform real-time streaming and execute data analysis operations on your data using various languages, before going on to apply ML techniques to derive accurate and granular insights from data. Finally, you'll discover how to protect sensitive data in real time by using security and privacy features.By the end of this Azure book, you'll be able to build end-to-end analytics solutions while focusing on data prep, data management, data warehousing, and AI tasks.
Linear Regression With Python. A Tutorial Introduction to the Mathematics of Regression Analysis
James V Stone
This book offers a detailed yet approachable introduction to linear regression, blending mathematical theory with Python-based practical applications. Beginning with fundamentals, it explains the best-fitting line, regression and causation, and statistical measures like variance, correlation, and the coefficient of determination. Clear examples and Python code ensure readers can connect theory to implementation.As the journey continues, readers explore statistical significance through concepts like t-tests, z-tests, and p-values, understanding how to assess slopes, intercepts, and overall model fit. Advanced chapters cover multivariate regression, introducing matrix formulations, the best-fitting plane, and methods to handle multiple variables. Topics such as Bayesian regression, nonlinear models, and weighted regression are explored in depth, with step-by-step coding guides for hands-on practice.The final sections tie together these techniques with maximum likelihood estimation and practical summaries. Appendices provide resources such as matrix tutorials, key equations, and mathematical symbols. Designed for both beginners and professionals, this book ensures a structured learning experience. Basic mathematical knowledge or foundation is recommended.
LLM Prompt Engineering for Developers. The Art and Science of Unlocking LLMs' True Potential
Aymen El Amri
LLM Prompt Engineering For Developers begins by laying the groundwork with essential principles of natural language processing (NLP), setting the stage for more complex topics. It methodically guides readers through the initial steps of understanding how large language models work, providing a solid foundation that prepares them for the more intricate aspects of prompt engineering.As you proceed, the book transitions into advanced strategies and techniques that reveal how to effectively interact with and utilize these powerful models. From crafting precise prompts that enhance model responses to exploring innovative methods like few-shot and zero-shot learning, this resource is designed to unlock the full potential of language model technology.This book not only teaches the technical skills needed to excel in the field but also addresses the broader implications of AI technology. It encourages thoughtful consideration of ethical issues and the impact of AI on society. By the end of this book, readers will master the technical aspects of prompt engineering & appreciate the importance of responsible AI development, making them well-rounded professionals ready to focus on the advancement of this cutting-edge technology.