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Podcasts
The second edition of Data Engineering with Google Cloud builds upon the success of the first edition by offering enhanced clarity and depth to data professionals navigating the intricate landscape of data engineering.Beyond its foundational lessons, this new edition delves into the essential realm of data governance within Google Cloud, providing you with invaluable insights into managing and optimizing data resources effectively. Written by a Data Strategic Cloud Engineer at Google, this book helps you stay ahead of the curve by guiding you through the latest technological advancements in the Google Cloud ecosystem. You’ll cover essential aspects, from exploring Cloud Composer 2 to the evolution of Airflow 2.5. Additionally, you’ll explore how to work with cutting-edge tools like Dataform, DLP, Dataplex, Dataproc Serverless, and Datastream to perform data governance on datasets.By the end of this book, you'll be equipped to navigate the ever-evolving world of data engineering on Google Cloud, from foundational principles to cutting-edge practices.
Vulnerability researchers are in increasingly high demand as the number of security incidents related to crime continues to rise with the adoption and use of technology. To begin your journey of becoming a security researcher, you need more than just the technical skills to find vulnerabilities; you’ll need to learn how to adopt research strategies and navigate the complex and frustrating process of sharing your findings. This book provides an easy-to-follow approach that will help you understand the process of discovering, disclosing, and publishing your first zero-day vulnerability through a collection of examples and an in-depth review of the process.You’ll begin by learning the fundamentals of vulnerabilities, exploits, and what makes something a zero-day vulnerability. Then, you'll take a deep dive into the details of planning winning research strategies, navigating the complexities of vulnerability disclosure, and publishing your research with sometimes-less-than-receptive vendors.By the end of the book, you'll be well versed in how researchers discover, disclose, and publish vulnerabilities, navigate complex vendor relationships, receive credit for their work, and ultimately protect users from exploitation. With this knowledge, you’ll be prepared to conduct your own research and publish vulnerabilities.
R is a highly flexible and powerful tool for analyzing and visualizing data. Most of the applications built using various libraries with R are desktop-based. But what if you want to go on the web? Here comes Shiny to your rescue!Shiny allows you to create interactive web applications using the excellent analytical and graphical capabilities of R. This book will guide you through basic data management and analysis with R through your first Shiny application, and then show you how to integrate Shiny applications with your own web pages. Finally, you will learn how to finely control the inputs and outputs of your application, along with using other packages to build state-of-the-art applications, including dashboards.
Splunk 9 improves on the existing Splunk tool to include important features such as federated search, observability, performance improvements, and dashboarding. This book helps you to make the best use of the impressive and new features to prepare a Splunk installation that can be employed in the data analysis process.Starting with an introduction to the different Splunk components, such as indexers, search heads, and forwarders, this Splunk book takes you through the step-by-step installation and configuration instructions for basic Splunk components using Amazon Web Services (AWS) instances. You’ll import the BOTS v1 dataset into a search head and begin exploring data using the Splunk Search Processing Language (SPL), covering various types of Splunk commands, lookups, and macros. After that, you’ll create tables, charts, and dashboards using Splunk’s new Dashboard Studio, and then advance to work with clustering, container management, data models, federated search, bucket merging, and more.By the end of the book, you’ll not only have learned everything about the latest features of Splunk 9 but also have a solid understanding of the performance tuning techniques in the latest version.
Learning Go Programming. Click here to enter text
The Go programming language has firmly established itself as a favorite for building complex and scalable system applications. Go offers a direct and practical approach to programming that let programmers write correct and predictable code using concurrency idioms and a full-featured standard library.This is a step-by-step, practical guide full of real world examples to help you get started with Go in no time at all. We start off by understanding the fundamentals of Go, followed by a detailed description of the Go data types, program structures and Maps. After this, you learn how to use Go concurrency idioms to avoid pitfalls and create programs that are exact in expected behavior. Next, you will be familiarized with the tools and libraries that are available in Go for writing and exercising tests, benchmarking, and code coverage. Finally, you will be able to utilize some of the most important features of GO such as, Network Programming and OS integration to build efficient applications. All the concepts are explained in a crisp and concise manner and by the end of this book; you would be able to create highly efficient programs that you can deploy over cloud.
Embark on a transformative journey with this course designed to equip you with robust Python and SQL skills. Starting with an introduction to Python, you'll delve into fundamental building blocks, control flow, functions, and object-oriented programming. As you progress, you'll master data structures, file I/O, exception handling, and the Python Standard Library, ensuring a solid foundation in Python.The course then transitions to SQL, beginning with an introduction and covering basics, and proceeding to advanced querying techniques. You'll learn about database administration and how Python integrates seamlessly with SQL, enhancing your data manipulation capabilities. By combining Python with SQLAlchemy, you'll perform advanced database operations and execute complex data analysis tasks, preparing you for real-world challenges.By the end of this course, you will have developed the expertise to utilize Python and SQL for scientific computing, data analysis, and database management. This comprehensive learning path ensures you can tackle diverse projects, from basic scripting to sophisticated data operations, making you a valuable asset in the tech industry. You'll also gain hands-on experience with real-world datasets, enhancing your problem-solving skills and boosting your confidence.
Data science and machine learning are some of the top buzzwords in the technical world today. From retail stores to Fortune 500 companies, everyone is working hard to making machine learning give them data-driven insights to grow their business. With powerful data manipulation features, machine learning packages, and an active developer community, R empowers users to build sophisticated machine learning systems to solve real-world data problems.This book takes you on a data-driven journey that starts with the very basics of R and machine learning and gradually builds upon the concepts to work on projects that tackle real-world problems.You’ll begin by getting an understanding of the core concepts and definitions required to appreciate machine learning algorithms and concepts. Building upon the basics, you will then work on three different projects to apply the concepts of machine learning, following current trends and cover major algorithms as well as popular R packages in detail. These projects have been neatly divided into six different chapters covering the worlds of e-commerce, finance, and social-media, which are at the very core of this data-driven revolution. Each of the projects will help you to understand, explore, visualize, and derive insights depending upon the domain and algorithms.Through this book, you will learn to apply the concepts of machine learning to deal with data-related problems and solve them using the powerful yet simple language, R.