Название: ScyllaDB in Action (Final Release)
Автор: Bo Ingram
Издательство: Manning Publications
Год: 2025
Страниц: 394
Язык: английский
Формат: pdf (true)
Размер: 10.9 MB

Build, maintain, and run databases that are easy to scale and quick to query—all with ScyllaDB. ScyllaDB in Action is your guide to everything you need to know about ScyllaDB, from your very first queries to running it in a production environment. It starts you with the basics of creating, reading, and deleting data and expands your knowledge from there. You'll soon have mastered everything you need to build, maintain, and run an effective and efficient database. This book teaches you ScyllaDB the best way—through hands-on examples. Dive into the node-based architecture of ScyllaDB to understand how its distributed systems work, how you can troubleshoot problems, and how you can constantly improve performance. ScyllaDB is a versatile NoSQL database that can move large volumes of data fast. Very, very, very fast. This drop-in replacement for Cassandra takes full advantage of modern multi-core hardware and scales to handle large real-time data workloads with incredibly low latency. It features built-in monitoring and management tools, and its efficient use of computing resources can save a lot of money on high-volume applications. ScyllaDB in Action is written for anyone looking to learn ScyllaDB or work with it. To get the best out of it, you should have some basic familiarity with SQL. You’ve probably written a SELECT statement before, and that knowledge will assist you throughout the book as you learn about Scylla. If you’re a database expert, that’s okay too! You’ll get to break some habits and pick up some new ones to effectively use ScyllaDB. You should also have some experience with a programming language—preferably Python, as you’ll use it to build the sample application to learn about the database driver and its client-side features.

Название: Mastering Microsoft Access 2024: A Comprehensive Guide to Designing, Managing, and Optimizing Your Databases with Step-by-Step Tutorials and Expert Tips - From Novice to Database
Автор: Thaddeus Locke
Издательство: Independently published
Год: 2024
Страниц: 718
Язык: английский
Формат: epub
Размер: 28.0 MB

Welcome to the ultimate guide to mastering Microsoft Access 2024! In today's data-driven world, organizing and analyzing information is paramount, and Microsoft Access remains one of the most powerful tools for managing databases efficiently. Whether you're a seasoned professional seeking to enhance your skills or a newcomer eager to harness the potential of Access, this book is your comprehensive companion on the journey to becoming an Access expert. In the Chapter 1, you will learn about the various vocabularies that are being used in Microsoft Access databases. In this section, you will learn about various databases, tables, records fields, and values and you will also learn about other relational databases. Objects in the Access Database which include tables, queries, display forms that include data entry, reports macros and VBA will also be discussed in detail in this chapter. Lately, you will learn about the various step design methods that should be embarked upon when making plans for database objects.

Название: Business Intelligence, Analytics, Data Science, and AI: A Managerial Perspective, 5th Edition
Автор: Ramesh Sharda, Dursun Delen, Efraim Turban
Издательство: Pearson Education, Inc.
Год: 2024
Страниц: 727
Язык: английский
Формат: pdf (true)
Размер: 39.2 MB

Business Intelligence, Analytics, Data Science, and AI is your guide to the business-related impact of Artificial Intelligence (AI), Data Science and analytics, designed to prepare you for a managerial role. The text's vignettes and cases feature modern companies and non-profit organizations and illustrate capabilities, costs and justifications of BI across various business units. With coverage of many data science/AI applications, you'll explore tools, then learn from various organizations' experiences employing such applications. Ample hands-on practice is provided, can be completed with a range of software, and will help you use analytics as a future manager. The 5th Edition integrates the fully updated content of Analytics, Data Science, and Artificial Intelligence, 11/e and Business Intelligence, Analytics, and Data Science, 4/e into one textbook, strengthened by 4 new chapters that will equip you for today's analytics and AI tech, such as ChatGPT. Examples explore analytics in sports, gaming, agriculture and “data for good.” Hadoop is an open-source framework for processing, storing, and analyzing massive amounts of distributed, unstructured data. A related new style of database called NoSQL (Not Only SQL) has emerged to, like Hadoop, process large volumes of multistructured data. Evolving out of the traditional artificial neural networks (ANN), Deep Learning is changing the very foundation of how Machine Learning works. Thanks to large collections of data and improved computational resources, Deep Learning is making a profound impact on how computers can discover complex patterns using the self-extracted features from the data (as opposed to a data scientist providing the feature vector to the learning algorithm).

Название: Working with Network dаta: A Data Science Perspective
Автор: James Bagrow, Yong‐Yeol Ahn
Издательство: Cambridge University Press
Год: 2024
Страниц: 554
Язык: английский
Формат: pdf
Размер: 15.1 MB

Drawing examples from real-world networks, this essential book traces the methods behind network analysis and explains how network data is first gathered, then processed and interpreted. The text will equip you with a toolbox of diverse methods and data modelling approaches, allowing you to quickly start making your own calculations on a huge variety of networked systems. This book sets you up to succeed, addressing the questions of what you need to know and what to do with it, when beginning to work with network data. The hands-on approach adopted throughout means that beginners quickly become capable practitioners, guided by a wealth of interesting examples that demonstrate key concepts. Exercises using real-world data extend and deepen your understanding, and develop effective working patterns in network calculations and analysis. There are great textbooks on network science. We complement these with a focus on the practical side of network science—working with network data. The purpose of this book is to provide a more practical guide for data scientists to use network science. Machine Learning, also called statistical learning, is the science and technology of building predictive models that generalize from data. Machine Learning has not only disrupted many industries, it’s revolutionizing how science is done. Because of its ubiquity, network data are also heavily leveraged by Machine Learning. Thus, scientists working with network data (and all forms of data) can benefit from the tools and techniques of Machine Learning. There are several types of Machine Learning methods: supervised learning and unsupervised learning are the primary categories and then there are self-supervised learning, reinforcement learning, and more. Suitable for both graduate students and researchers across a range of disciplines, this novel text provides a fast-track to network data expertise.

Название: Apache Hudi: The Definitive Guide: Building Robust, Open, and High-Performing Data Lakehouses (Early Release)
Автор: Shiyan Xu, Prashant Wason, Bhavani Sudha Saktheeswaran, Rebecca Bilbro
Издательство: O’Reilly Media, Inc.
Год: 2024-09-24
Язык: английский
Формат: pdf, epub, mobi
Размер: 10.1 MB

Overcome challenges in building transactional guarantees on rapidly changing data by using Apache Hudi. With this practical guide, data engineers, data architects, and software architects will discover how to seamlessly build an interoperable lakehouse from disparate data sources and deliver faster insights using their query engine of choice. Authors Shiyan Xu, Prashant Wason, Sudha Saktheeswaran, and Rebecca Bilbro provide practical examples and insights to help you unlock the full potential of data lakehouses for different levels of analytics, from batch to interactive to streaming. You'll also learn how to evaluate storage choices and leverage built-in automated table optimizations to build, maintain, and operate production data applications. The data platform layer can then become a limiting factor for innovation, straining to provide data fresh enough for analytics, and slowing down use cases of Machine Learning and AI. Herein lies a key advantage of using Hudi to empower analytics for this next generation of data-intensive applications. Hudi is designed to provide native support for near real-time analytics as well as time travel, and this is most evident in the different ways in which data can be read from Hudi.

Название: Streaming Databases: Unifying Batch and Stream Processing (Final Release)
Автор: Hubert Dulay, Ralph M. Debusmann
Издательство: O’Reilly Media, Inc.
Год: 2024
Страниц: 260
Язык: английский
Формат: True PDF, True EPUB (Retail Copy)
Размер: 15.4 MB

Real-time applications are becoming the norm today. But building a model that works properly requires real-time data from the source, in-flight stream processing, and low latency serving of its analytics. With this practical book, data engineers, data architects, and data analysts will learn how to use streaming databases to build real-time solutions. Authors Hubert Dulay and Ralph M. Debusmann take you through streaming database fundamentals, including how these databases reduce infrastructure for real-time solutions. You'll learn the difference between streaming databases, stream processing, and real-time online analytical processing (OLAP) databases. And you'll discover when to use push queries versus pull queries, and how to serve synchronous and asynchronous data emanating from streaming databases. So what is a streaming database? Database systems have many different flavors, from traditional relational databases to XML, graph, object, vector, and NoSQL databases. Many of these are well known and have been established for many decades. Streaming, or stream processing, is much less established, although it has seen a steep adoption rate in the industry over the past decade or so, led by the rise of Apache Kafka as the de facto streaming platform. Whether you’re a seasoned database engineer or a novice developer, this book guides you to unlocking the full potential of streaming databases and embracing the future of data processing.

Название: New Frontiers in Textual Data Analysis
Автор: Giuseppe Giordano, Michelangelo Misuraca
Издательство: Springer
Год: 2024
Страниц: 385
Язык: английский
Формат: pdf (true), epub
Размер: 39.4 MB

This volume presents a selection of articles which explore methodological and applicative aspects of textual data analysis. Divided into four parts, it begins by focusing on statistical methods, and then moves on to problems in quantitative language processing. After discussing the challenging task of text mining in relation to emotional and sentiment analyses, the book concludes with a collection of studies in the social sciences and public health which apply textual data analysis methods. The book, comprising thirty contributions, is divided into four parts: (1). Statistical methods for Textual Data Analysis, (2). Advances in language processing, (3). Emotion and Sentiment Analyses, and (4). Textual Data Analysis in action. Machine learning has become a crucial technology in various industries and has many applications ranging from computer vision and natural language processing to predictive policing and healthcare. Artificial Intelligence (AI) models can be grouped into several families based on their underlying architecture, functionality, and applications. The most important ones are the following: 1. Deep Learning models: They have been the driving force behind many breakthroughs in AI in the recent year. Their architecture, made of multiple neuronal layers, is designed to model complex relationships and nonlinear interactions between input and output variables. 2. Generative models: They can generate new data much of a muchness to the fed training data. They are used in most of applications generating new images, music, or text.

Название: Linux-Code fur Einsteiger - September 2024
Издательство: Papercut Limited
Год / месяц: September 2024
Страниц: 72
Формат: PDF
Размер: 55,4 MB
Язык: немецкий

Эта книга содержит подробное введение в основные функции и возможности Linux, включая установку дистрибутива Linux на компьютер, использование командной строки, управление пользователями и файлами, создание сетевых соединений и настройку различных служб. Вы также узнаете, как писать и использовать сценарии Bash. Как введение в программирование для Linux, эта книга будет полезна как профессионалам, так и любителям, предоставляя всю информацию, необходимую для того, чтобы войти в мир программирования для Linux и создавать отличные приложения. В этой книге вы найдете всю информацию, необходимую для того, чтобы войти в мир программирования под Linux и создавать отличные приложения.

Название: MySQL 8 Cookbook: Ready solutions to achieve highest levels of enterprise database scalability, security, reliability, and uptime
Автор: Kyran Velos
Издательство: GitforGits
Год: 2024
Страниц: 335
Язык: английский
Формат: pdf, epub, mobi
Размер: 10.1 MB

For database developers, administrators, engineers, and backend developers, MySQL 8 Cookbook provides solution-focused recipes. This book takes a practical approach to solving real-world problems by showing readers how to increase database security, enhance performance, and fix common MySQL issues through the use of numerous examples. You will learn how to install, configure, and tune MySQL for optimal performance in Linux environments. Important topics like backup strategies, security measures, query optimization, high availability, and replication are covered in each chapter. You will learn to partition and index datasets in a way that improves query performance, and the book provides step-by-step solutions to help them manage big datasets. With the help of this book, you can convert MySQL into a schema-less database that can manage unstructured data with ease, and it even handles modern data types like JSON. You can build fault-tolerant and scalable database systems including the implementation of multi-source replication, master-slave replication, and master-master replication. Problems like table corruption, excessive CPU and memory usage, deadlocks, and replication lag are addressed in the troubleshooting sections. Also shown are methods for automating and monitoring database security using Linux tools, cron jobs, and MySQL's performance schema. Whether you're managing enterprise databases or developing backend applications, this book will teach you to improve your database management skills and ensure peak performance for systems that are critical to business.

Название: Data Analytics and Artificial Intelligence for Predictive Maintenance in Smart Manufacturing
Автор: Amit Kumar Tyagi, Shrikant Tiwari, Gulshan Soni
Издательство: CRC Press
Год: 2025
Страниц: 419
Язык: английский
Формат: pdf (true), epub
Размер: 26.1 MB

Data analytics and Artificial Intelligence (AI) or data mining techniques have emerged as essential tools for this decade which invite a new revolution in the way manufacturers manage their operations. This has resulted in a transformation in predictive maintenance (PdM), an indispensable strategy that uses the power of data and AI to optimize maintenance practices and, in doing so, redefine the manufacturing landscape/process. Hence, this book provides detail of various topics such as where it uses data analytics and Artificial Intelligence techniques in predictive maintenance in the manufacturing industry. This book will start with fundamental concepts, the transformative impact, and reasons why this convergence of technology and industry is not just a trend but a revolution. As we move on this journey through the realms of data, algorithms, sensors, and real-time decision-making, this book explain essential implications of these emerging (data analytics/data mining techniques) technologies on the future of manufacturing. It starts from data collection and preprocessing to the deployment of required Machine Learning models in the respective area. Machine Learning, a subset of Artificial Intelligence (AI), has become a fundamental aspect of contemporary computing. Its capacity to enable systems to learn from data and independently make informed choices has sparked revolutionary advancements across various sectors. In recent years, the field has witnessed unprecedented growth, driven by advancements in computational power, data availability, and algorithmic sophistication. The essence of Machine Learning lies in its departure from traditional rule-based programming paradigms.