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Podcasts
The Professional Scrum Master Guide. The unofficial guide to Scrum with real-world projects
This book demonstrates the real-world applications of Scrum in a variety of scenarios, all with practical examples. You’ll understand why the structure of your Scrum team matters, and how to create and manage sprint and product backlogs. Each chapter concludes with relevance to the exam, reinforcing what you’ve learned as you work through the book and making sure you have an edge when it comes to earning your certificate.The statements made and opinions expressed herein belong exclusively to Packt Publishing Ltd and are not shared by or represent the viewpoint of Scrum.org. This training does not constitute an endorsement of any product, service or point of view. Scrum.org makes no representations, warranties or assurances of any kind, express or implied, as to the completeness, accuracy, reliability, suitability, availability or currency of the content contained in this presentation or any material related to this presentation. In no event shall Scrum.org, its agents, officers, employees, licensees or affiliates be liable for any damages whatsoever (including, without limitation, damages for loss of profits, business information, or loss of information) arising out of the information or statements contained in the training. Any reliance you place on such content is strictly at your own risk.
Scala Test-Driven Development. Write clean scala code that works
Test-driven development (TDD) produces high-quality applications in less time than is possible with traditional methods. Due to the systematic nature of TDD, the application is tested in individual units as well as cumulatively, right from the design stage, to ensure optimum performance and reduced debugging costs. This step-by-step guide shows you how to use the principles of TDD and built-in Scala testing modules to write clean and fully tested Scala code and give your workflow the change it needs to let you create better applications than ever before. After an introduction to TDD, you will learn the basics of ScalaTest, one of the most flexible and most popular testing tools around for Scala, by building your first fully test-driven application. Building on from that you will learn about the ScalaTest API and how to refactor code to produce high-quality applications. We’ll teach you the concepts of BDD (Behavior-driven development) and you’ll see how to add functional tests to the existing suite of tests. You’ll be introduced to the concepts of Mocks and Stubs and will learn to increase test coverage using properties. With a concluding chapter on miscellaneous tools, this book will enable you to write better quality code that is easily maintainable and watch your apps change for the better.
Julia is a well-constructed programming language which was designed for fast execution speed by using just-in-time LLVM compilation techniques, thus eliminating the classic problem of performing analysis in one language and translating it for performance in a second.This book is a primer on Julia’s approach to a wide variety of topics such as scientific computing, statistics, machine learning, simulation, graphics, and distributed computing.Starting off with a refresher on installing and running Julia on different platforms, you’ll quickly get to grips with the core concepts and delve into a discussion on how to use Julia with various code editors and interactive development environments (IDEs).As you progress, you’ll see how data works through simple statistics and analytics and discover Julia's speed, its real strength, which makes it particularly useful in highly intensive computing tasks. You’ll also and observe how Julia can cooperate with external processes to enhance graphics and data visualization. Finally, you will explore metaprogramming and learn how it adds great power to the language and establish networking and distributed computing with Julia.By the end of this book, you’ll be confident in using Julia as part of your existing skill set.
Data scientists, when presented with a myriad of data, can often lose sight of how to present geospatial analyses in a meaningful way so that it makes sense to everyone. Using Python to visualize data helps stakeholders in less technical roles to understand the problem and seek solutions. The goal of this book is to help data scientists and GIS professionals learn and implement geospatial data science workflows using Python.Throughout this book, you’ll uncover numerous geospatial Python libraries with which you can develop end-to-end spatial data science workflows. You’ll learn how to read, process, and manipulate spatial data effectively. With data in hand, you’ll move on to crafting spatial data visualizations to better understand and tell the story of your data through static and dynamic mapping applications. As you progress through the book, you’ll find yourself developing geospatial AI and ML models focused on clustering, regression, and optimization. The use cases can be leveraged as building blocks for more advanced work in a variety of industries.By the end of the book, you’ll be able to tackle random data, find meaningful correlations, and make geospatial data models.
Service-oriented Architecture (SOA) is an architectural style created to address the challenges posed by today’s highly distributed, fast-paced computing. This goal is achieved by constructing business-focused software systems from loosely coupled, interoperable building blocks called Services. Organizations often fail to successfully implement SOA due to a lack of effective governance. Oracle SOA Governance is a comprehensive, service-orientated architecture governance solution that is designed to make the transition to SOA easier.Oracle SOA Governance 11g Implementation illustrates how to successfully implement SOA governance in your organization. To achieve this, we describe how goals and objectives need to be clearly laid out and used to align governance processes with governance tools, governance tools with people, and people with the different roles and responsibilities that are required to implement effective governance.Oracle SOA Governance 11g Implementation begins with a short but concise overview of SOA governance. We then go to explore real world examples, based on previous experiences and working solutions, in order to learn the concepts of Oracle SOA Governance Suite.We will also learn how to implement an OER-centric SDLC process to address your organizations design-time governance requirements. Next, we will explore OSR, and discover how to use it to expose service implementations to consumers based on UDDI concepts. We will explore the features available within Web Service Manager (WSM), Oracle Enterprise Manager (OEM), and Business Transaction Manager (BTM). Finally, we discover how OER can be extended to govern Oracle Application Integration Architecture (AIA) implementations.Discover and learn how to use Oracle SOA Governance Suite to address your specific design-time and runtime governance challenges.
Olivier Mertens, Breght Van Baelen
With data’s growing importance in businesses, the need for cloud data and AI architects has never been higher. The Azure Data and AI Architect Handbook is designed to assist any data professional or academic looking to advance their cloud data platform designing skills. This book will help you understand all the individual components of an end-to-end data architecture and how to piece them together into a scalable and robust solution.You’ll begin by getting to grips with core data architecture design concepts and Azure Data & AI services, before exploring cloud landing zones and best practices for building up an enterprise-scale data platform from scratch. Next, you’ll take a deep dive into various data domains such as data engineering, business intelligence, data science, and data governance. As you advance, you’ll cover topics ranging from learning different methods of ingesting data into the cloud to designing the right data warehousing solution, managing large-scale data transformations, extracting valuable insights, and learning how to leverage cloud computing to drive advanced analytical workloads. Finally, you’ll discover how to add data governance, compliance, and security to solutions.By the end of this book, you’ll have gained the expertise needed to become a well-rounded Azure Data & AI architect.