Data Management Strategy at Microsoft. Best practices from a tech giant's decade-long data transformation journey

Aleksejs Plotnikovs

Microsoft pioneered data innovation and investment ahead of many in the industry, setting a remarkable standard for data maturity. Written by a data leader with over 15 years of experience following Microsoft’s data journey, this book delves into every crucial aspect of this journey, including change management, aligning with business needs, enhancing data value, and cultivating a data-driven culture.This book emphasizes that success in a data-driven enterprise goes beyond relying solely on modern technology and highlights the importance of prioritizing genuine business needs to propel necessary modernizations through change management practices. You’ll see how data-driven innovation does not solely reside within central IT engineering teams but also among the data's business owners who rely on data daily for their operational needs. This guide empower these professionals with clean, easily discoverable, and business-ready data, marking a significant breakthrough in how data is perceived and utilized throughout an enterprise. You’ll also discover advanced techniques to nurture the value of data as unique intellectual property, and differentiate your organization with the power of data.Its storytelling approach and summary of essential insights at the end of each chapter make this book invaluable for business and data leaders to advocate for crucial data investments.

Learning Probabilistic Graphical Models in R. Familiarize yourself with probabilistic graphical models through real-world problems and illustrative code examples in R

David Bellot, Dan Toomey

Probabilistic graphical models (PGM, also known as graphical models) are a marriage between probability theory and graph theory. Generally, PGMs use a graph-based representation. Two branches of graphical representations of distributions are commonly used, namely Bayesian networks and Markov networks. R has many packages to implement graphical models.We’ll start by showing you how to transform a classical statistical model into a modern PGM and then look at how to do exact inference in graphical models. Proceeding, we’ll introduce you to many modern R packages that will help you to perform inference on the models. We will then run a Bayesian linear regression and you’ll see the advantage of going probabilistic when you want to do prediction. Next, you’ll master using R packages and implementing its techniques. Finally, you’ll be presented with machine learning applications that have a direct impact in many fields. Here, we’ll cover clustering and the discovery of hidden information in big data, as well as two important methods, PCA and ICA, to reduce the size of big problems.

Sonar Code Quality Testing Essentials. Achieve higher levels of Software Quality with Sonar with this book and

Charalampos S Arapidis, Charalampos S. Arapidis

Sonar is an open source platform used by development teams to manage source code quality. Sonar has been developed with this main objective in mind: make code quality management accessible to everyone with minimal effort. As such, Sonar provides code analyzers, reporting tools, manual reviews, defect-hunting modules, and TimeMachine as core functionalities. It also comes with a plugin mechanism enabling the community to extend the functionality, making Sonar the one-stop-shop for source code quality by addressing not only the developer's requirements, but also the manager's needs.The Sonar Code Quality Testing Essentials book will help you understand the different factors that define code quality and how to improve your own or your team's code using Sonar.You will learn to use Sonar effectively and explore the quality of your source code in the following axes:Coding StandardsDocumentation and CommentsPotential Bugs and DefectsUnit Testing CoverageDesign and ComplexityThrough practical examples, you will customize Sonar components and widgets to identify areas where your source code is lacking. The book goes down to proposing good practices and common solutions that you can put to use to improve such code.You will start with installing and setting up a Sonar server and performing your first project analysis. Then you will go through the process of creating a custom and balanced quality profile exploring all Sonar components through practical examples. After reading the book, you will be able to analyze any project using Sonar and know how to read and evaluate quality metrics.Hunting potential bugs and eliminating complexity are the hottest topics regarding code quality. The book will guide you through the process of finding such problematic areas, leveraging and customizing the most appropriate components. Knowing the best tool for each task is essential. While you improve code and design through the book, you will notice that metrics go high and alerts turn green. You will use the Time Machine and the Timeline to examine how your changes affected the quality.Sonar Code Quality Testing Essentials will enable you to perform custom quality analysis on any Java project and quickly gain insight on even large code bases, as well as provide possible solutions to code defects and complexity matters.

Linux Networking Cookbook. Over 40 recipes to help you set up and configure Linux networks

Gregory Boyce

Linux can be configured as a networked workstation, a DNS server, a mail server, a firewall, a gateway router, and many other things. These are all part of administration tasks, hence network administration is one of the main tasks of Linux system administration. By knowing how to configure system network interfaces in a reliable and optimal manner, Linux administrators can deploy and configure several network services including file, web, mail, and servers while working in large enterprise environments.Starting with a simple Linux router that passes traffic between two private networks, you will see how to enable NAT on the router in order to allow Internet access from the network, and will also enable DHCP on the network to ease configuration of client systems. You will then move on to configuring your own DNS server on your local network using bind9 and tying it into your DHCP server to allow automatic configuration of local hostnames. You will then future enable your network by setting up IPv6 via tunnel providers.Moving on, we’ll configure Samba to centralize authentication for your network services; we will also configure Linux client to leverage it for authentication, and set up a RADIUS server that uses the directory server for authentication.Toward the end, you will have a network with a number of services running on it, and will implement monitoring in order to detect problems as they occur.

Principles of Data Fabric. Become a data-driven organization by implementing Data Fabric solutions efficiently

Sonia Mezzetta

Data can be found everywhere, from cloud environments and relational and non-relational databases to data lakes, data warehouses, and data lakehouses. Data management practices can be standardized across the cloud, on-premises, and edge devices with Data Fabric, a powerful architecture that creates a unified view of data. This book will enable you to design a Data Fabric solution by addressing all the key aspects that need to be considered.The book begins by introducing you to Data Fabric architecture, why you need them, and how they relate to other strategic data management frameworks. You’ll then quickly progress to grasping the principles of DataOps, an operational model for Data Fabric architecture. The next set of chapters will show you how to combine Data Fabric with DataOps and Data Mesh and how they work together by making the most out of it. After that, you’ll discover how to design Data Integration, Data Governance, and Self-Service analytics architecture. The book ends with technical architecture to implement distributed data management and regulatory compliance, followed by industry best practices and principles.By the end of this data book, you will have a clear understanding of what Data Fabric is and what the architecture looks like, along with the level of effort that goes into designing a Data Fabric solution.

Azure for Developers. Implement rich Azure PaaS ecosystems using containers, serverless services, and storage solutions - Second Edition

Kamil Mrzygłód

Microsoft Azure is currently one of the fastest growing public cloud service providers thanks to its sophisticated set of services for building fault-tolerant and scalable cloud-based applications.This second edition of Azure for Developers will take you on a journey through the various PaaS services available in Azure, including Azure App Service, Azure Functions, and Azure SQL Databases, showing you how to build a complete and reliable system with ease. Throughout the book, you’ll discover ways to enhance your skills when building cloud-based solutions leveraging different SQL/NoSQL databases, serverless and messaging components, containerized solutions, and even search engines such as Azure Cognitive Search. That’s not all!! The book also covers more advanced scenarios such as scalability best practices, serving static content with Azure CDN, and distributing loads with Azure Traffic Manager, Azure Application Gateway, and Azure Front Door.By the end of this Azure book, you’ll be able to build modern applications on the Azure cloud using the most popular and promising technologies to make your solutions reliable, stable, and efficient.

Financial Modeling Using Quantum Computing. Design and manage quantum machine learning solutions for financial analysis and decision making

Anshul Saxena, Javier Mancilla, Iraitz Montalban, Christophe Pere

Quantum computing has the potential to revolutionize the computing paradigm. By integrating quantum algorithms with artificial intelligence and machine learning, we can harness the power of qubits to deliver comprehensive and optimized solutions for intricate financial problems.This book offers step-by-step guidance on using various quantum algorithm frameworks within a Python environment, enabling you to tackle business challenges in finance. With the use of contrasting solutions from well-known Python libraries with quantum algorithms, you’ll discover the advantages of the quantum approach. Focusing on clarity, the authors expertly present complex quantum algorithms in a straightforward, yet comprehensive way. Throughout the book, you'll become adept at working with simple programs illustrating quantum computing principles. Gradually, you'll progress to more sophisticated programs and algorithms that harness the full power of quantum computing.By the end of this book, you’ll be able to design, implement and run your own quantum computing programs to turbocharge your financial modelling.

GNU Octave Beginner's Guide. Become a proficient Octave user by learning this high-level scientific numerical tool from the ground up

Jesper Schmidt Hansen

Today, scientific computing and data analysis play an integral part in most scientific disciplines ranging from mathematics and biology to imaging processing and finance. With GNU Octave you have a highly flexible tool that can solve a vast number of such different problems as complex statistical analysis and dynamical system studies.The GNU Octave Beginner's Guide gives you an introduction that enables you to solve and analyze complicated numerical problems. The book is based on numerous concrete examples and at the end of each chapter you will find exercises to test your knowledge. It's easy to learn GNU Octave, with the GNU Octave Beginner's Guide to hand.Using real-world examples the GNU Octave Beginner's Guide will take you through the most important aspects of GNU Octave. This practical guide takes you from the basics where you are introduced to the interpreter to a more advanced level where you will learn how to build your own specialized and highly optimized GNU Octave toolbox package. The book starts by introducing you to work variables like vectors and matrices, demonstrating how to perform simple arithmetic operations on these objects before explaining how to use some of the simple functionality that comes with GNU Octave, including plotting. It then goes on to show you how to write new functionality into GNU Octave and how to make a toolbox package to solve your specific problem. Finally, it demonstrates how to optimize your code and link GNU Octave with C and C++ code enabling you to solve even the most computationally demanding tasks. After reading GNU Octave Beginner's Guide you will be able to use and tailor GNU Octave to solve most numerical problems and perform complicated data analysis with ease.