Verleger: Packt Publishing
Cassandra 3.x High Availability. Click here to enter text. - Second Edition
Robbie Strickland
Apache Cassandra is a massively scalable, peer-to-peer database designed for 100 percent uptime, with deployments in the tens of thousands of nodes, all supporting petabytes of data. This book offers a practical insight into building highly available, real-world applications using Apache Cassandra.The book starts with the fundamentals, helping you to understand how Apache Cassandra’s architecture allows it to achieve 100 percent uptime when other systems struggle to do so. You’ll get an excellent understanding of data distribution, replication, and Cassandra’s highly tunable consistency model. Then we take an in-depth look at Cassandra's robust support for multiple data centers, and you’ll see how to scale out a cluster. Next, the book explores the domain of application design, with chapters discussing the native driver and data modeling. Lastly, you’ll find out how to steer clear of common anti-patterns and take advantage of Cassandra’s ability to fail gracefully.
Rajanarayanan Thottuvaikkatumana
If you are new to Cassandra but well-versed in RDBMS modeling and design, then it is natural to model data in the same way in Cassandra, resulting in poorly performing applications and losing the real purpose of Cassandra. If you want to learn to make the most of Cassandra, this book is for you.This book starts with strategies to integrate Cassandra with other legacy data stores and progresses to the ways in which a migration from RDBMS to Cassandra can be accomplished. The journey continues with ideas to migrate data from cache solutions to Cassandra. With this, the stage is set and the book moves on to some of the most commonly seen problems in applications when dealing with consistency, availability, and partition tolerance guarantees. Cassandra is exceptionally good at dealing with temporal data and patterns such as the time-series pattern and log pattern, which are covered next. Many NoSQL data stores fail miserably when a huge amount of data is read for analytical purposes, but Cassandra is different in this regard. Keeping analytical needs in mind, you’ll walk through different and interesting design patterns.No theoretical discussions are complete without a good set of use cases to which the knowledge gained can be applied, so the book concludes with a set of use cases you can apply the patterns you’ve learned.
Aleksander Molak, Ajit Jaokar
Causal methods present unique challenges compared to traditional machine learning and statistics. Learning causality can be challenging, but it offers distinct advantages that elude a purely statistical mindset. Causal Inference and Discovery in Python helps you unlock the potential of causality.You’ll start with basic motivations behind causal thinking and a comprehensive introduction to Pearlian causal concepts, such as structural causal models, interventions, counterfactuals, and more. Each concept is accompanied by a theoretical explanation and a set of practical exercises with Python code. Next, you’ll dive into the world of causal effect estimation, consistently progressing towards modern machine learning methods. Step-by-step, you’ll discover Python causal ecosystem and harness the power of cutting-edge algorithms. You’ll further explore the mechanics of how “causes leave traces” and compare the main families of causal discovery algorithms. The final chapter gives you a broad outlook into the future of causal AI where we examine challenges and opportunities and provide you with a comprehensive list of resources to learn more.By the end of this book, you will be able to build your own models for causal inference and discovery using statistical and machine learning techniques as well as perform basic project assessment.
Subhajit Das
Determining causality in data is difficult due to confounding factors. Written by an applied scientist specializing in causal inference with over a decade of experience, Causal Inference in R provides the tools and methods you need to accurately establish causal relationships, improving data-driven decision-making.This book helps you get to grips with foundational concepts, offering a clear understanding of causal models and their relevance in data analysis. You’ll progress through chapters that blend theory with hands-on examples, illustrating how to apply advanced statistical methods to real-world scenarios. You’ll discover techniques for establishing causality, from classic approaches to contemporary methods, such as propensity score matching and instrumental variables. Each chapter is enriched with detailed case studies and R code snippets, enabling you to implement concepts immediately. Beyond technical skills, this book also emphasizes critical thinking in data analysis to empower you to make informed, data-driven decisions. The chapters enable you to harness the power of causal inference in R to uncover deeper insights from data.By the end of this book, you’ll be able to confidently establish causal relationships and make data-driven decisions with precision.
Esta Lessing
Certified Business Analysis Professional (CBAP®) is a certification from the International Institute of Business Analysis (IIBA®) for professionals with extensive experience in business analysis. The CCBA® and CBAP® validates your proficiency in various aspects of business analysis and your ability to tackle challenging projects, work effectively with stakeholders, and identify and deliver business value. You’ll start by learning about the benefits of CCBA® and CBAP® certifications for your career progression before focussing on the six core knowledge areas explained thoroughly in each chapter. These include topics such as business analysis planning and monitoring, elicitation and collaboration, requirements life cycle management, strategy analysis, requirements analysis, and design definition as well as solution evaluation. The book includes the essential underlying competencies and techniques to ensure a complete understanding of the BABOK® v3 guide content. Each chapter delves into the essential concepts and business analysis task considerations utilizing practical examples. Finally, you’ll assess your knowledge through mock exam questions based on real-world case studies.By the end of this book, you’ll have gained the business analysis skills needed to prepare for the certification exams and to advance in your career.
Bekim Dauti
CCENT is the entry-level certification for those looking to venture into the networking world. This guide will help you stay up-to date with your networking skills. This book starts with the basics and will take you through everything essential to pass the certification exam. It extensively covers IPv4 and IPv6 addressing, IP data networks, switching and routing, network security, and much more—all in some detail. This guide will provide real-world examples with a bunch of hands-on labs to give you immense expertise in important networking tasks, with a practical approach. Each chapter consists of practice questions to help you take up a challenge from what you have procured. This book ends with mock tests with several examples to help you confidently pass the certification. This Certification Guide consists of everything you need to know in order to pass the ICND 1 100-105 Exam, thus obtaining a CCENT certification. However, practicing with real switches and routers or a switch or router simulator will help you succeed.
Andrew Chu
Cybersecurity roles have grown exponentially in the IT industry and an increasing number of organizations have set up security operations centers (SOCs) to monitor and respond to security threats. The 210-255 SECOPS exam is the second of two exams required for the Cisco CCNA Cyber Ops certification. By providing you with fundamental knowledge of SOC events, this certification validates your skills in managing cybersecurity processes such as analyzing threats and malicious activities, conducting security investigations, and using incident playbooks.You'll start by understanding threat analysis and computer forensics, which will help you build the foundation for learning intrusion analysis and incident response principles. The book will then guide you through vocabulary and techniques for analyzing data from the network and previous events. In later chapters, you'll discover how to identify, analyze, correlate, and respond to incidents, including how to communicate technical and inaccessible (non-technical) examples. You'll be able to build on your knowledge as you learn through examples and practice questions, and finally test your knowledge with two mock exams that allow you to put what you’ve learned to the test.By the end of this book, you'll have the skills to confidently pass the SECOPS 210-255 exam and achieve CCNA Cyber Ops certification.