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Traditional data architecture patterns are severely limited. To use these patterns, you have to ETL data into each tool--a cost-prohibitive process for making warehouse features available to all of your data. The lack of flexibility with these patterns requires you to lock into a set of priority tools and formats, which creates data silos and data drift. This practical book shows you a better way. Apache Iceberg provides the capabilities, performance, scalability, and savings that fulfill the promise of an open data lakehouse. By following the lessons in this book, you'll be able to achieve interactive, batch, machine learning, and streaming analytics with this high-performance open source format. Authors Tomer Shiran, Jason Hughes, and Alex Merced from Dremio show you how to get started with Iceberg. With this book, you'll learn: The architecture of Apache Iceberg tables What happens under the hood when you perform operations on Iceberg tables How to further optimize Iceberg tables for maximum performance How to use Iceberg with popular data engines such as Apache Spark, Apache Flink, and Dremio Discover why Apache Iceberg is a foundational technology for implementing an open data lakehouse.

Gain the valuable skills and techniques you need to accelerate the delivery of machine learning solutions. With this practical guide, data scientists, ML engineers, and their leaders will learn how to bridge the gap between data science and Lean product delivery in a practical and simple way. David Tan, Ada Leung, and Dave Colls show you how to apply time-tested software engineering skills and Lean product delivery practices to reduce toil and waste, shorten feedback loops, and improve your team's flow when building ML systems and products. Based on the authors' experience across multiple real-world data and ML projects, the proven techniques in this book will help your team avoid common traps in the ML world, so you can iterate and scale more quickly and reliably. You'll learn how to overcome friction and experience flow when delivering ML solutions. You'll also learn how to: Write automated tests for ML systems, containerize development environments, and refactor problematic codebases Apply MLOps and CI/CD practices to accelerate experimentation cycles and improve reliability of ML solutions Apply Lean delivery and product practices to improve your odds of building the right product for your users Identify suitable team structures and intra- and inter-team collaboration techniques to enable fast flow, reduce cognitive load, and scale ML within your organization

If programming is magic then web scraping is surely a form of wizardry. By writing a simple automated program, you can query web servers, request data, and parse it to extract the information you need. The expanded edition of this practical book not only introduces you web scraping, but also serves as a comprehensive guide to scraping almost every type of data from the modern web.Part I focuses on web scraping mechanics: using Python to request information from a web server, performing basic handling of the servers response, and interacting with sites in an automated fashion. Part II explores a variety of more specific tools and applications to fit any web scraping scenario youre likely to encounter.Parse complicated HTML pagesDevelop crawlers with the Scrapy frameworkLearn methods to store data you scrapeRead and extract data from documentsClean and normalize badly formatted dataRead and write natural languagesCrawl through forms and loginsScrape JavaScript and crawl through APIsUse and write image-to-text softwareAvoid scraping traps and bot blockersUse scrapers to test your website

How can you make sense of the complex IoT landscape? With dozens of components ranging from devices to metadata about the devices, it's easy to get lost among the possibilities. But it's not impossible if you have the right guide to help you navigate all the complexities. This practical book shows developers, architects, and IT managers how to build IoT solutions on Azure. Author Blaize Stewart presents a comprehensive view of the IoT landscape. You'll learn about devices, device management at scale, and the tools Azure provides for building globally distributed systems. You'll also explore ways to organize data by choosing the appropriate dataflow and data storage technologies. The final chapters examine data consumption and solutions for delivering data to consumers with Azure. Get the architectural guidance you need to create holistic solutions with devices, data, and everything in between. This book helps you: Meet the demands of an IoT solution with Azure-provided functionality Use Azure to create complete scalable and secure IoT systems Understand how to articulate IoT architecture and solutions Guide conversations around common problems that IoT applications solve Select the appropriate technologies in the Azure space to build IoT applications

If you were handed two different but related sets of data, what tools would you use to find the matches? What if all you had was SQL SELECT access to a database? In this practical book, author Jim Lehmer provides best practices, techniques, and tricks to help you import, clean, match, score, and think about heterogeneous data using SQL. DBAs, programmers, business analysts, and data scientists will learn how to identify and remove duplicates, parse strings, extract data from XML and JSON, generate SQL using SQL, regularize data and prepare datasets, and apply data quality and ETL approaches for finding the similarities and differences between various expressions of the same data. Full of real-world techniques, the examples in the book contain working code. You'll learn how to: Identity and remove duplicates in two different datasets using SQL Regularize data and achieve data quality using SQL Extract data from XML and JSON Generate SQL using SQL to increase your productivity Prepare datasets for import, merging, and better analysis using SQL Report results using SQL Apply data quality and ETL approaches to finding similarities and differences between various expressions of the same data

This practical guide provides a collection of techniques and best practices that are generally overlooked in most data engineering and data science pedagogy. A common misconception is that great data scientists are experts in the "big themes" of the discipline--machine learning and programming. But most of the time, these tools can only take us so far. In practice, the smaller tools and skills really separate a great data scientist from a not-so-great one. Taken as a whole, the lessons in this book make the difference between an average data scientist candidate and a qualified data scientist working in the field. Author Daniel Vaughan has collected, extended, and used these skills to create value and train data scientists from different companies and industries. With this book, you will: Understand how data science creates value Deliver compelling narratives to sell your data science project Build a business case using unit economics principles Create new features for a ML model using storytelling Learn how to decompose KPIs Perform growth decompositions to find root causes for changes in a metric Daniel Vaughan is head of data at Clip, the leading paytech company in Mexico. He's the author of Analytical Skills for AI and Data Science (O'Reilly).

Explore the theory and practice of designing and writing serverless applications using examples from the Knative project. With this practical guide, mid-level to senior application developers and team managers will learn when and why to target serverless platforms when developing microservices or applications. Along the way, you'll also discover warning signs that suggest why serverless might cause you more trouble than joy. Drawing on author Evan Anderson's 15 years of experience developing and maintaining applications in the cloud--and more than six years of experience with serverless platforms at scale--this book acts as your guide into the high-velocity world of serverless application development. You'll come to appreciate why Knative is the most widely adopted open source serverless platform available. With this book, you will: Learn what serverless is, how it works, and why teams are adopting it Understand the benefits of Knative for cloud native development teams Learn how to build a serverless application on Knative Explore the challenges serverless introduces for debugging and the tools that can help improve it Learn why event-driven architecture and serverless compute are complementary but distinct Understand when a serverless approach might not be the right system design

"The adoption of serverless is on the rise, but until now, little guidance has been available for development teams that want to apply this technology on AWS. This definitive guide is packed with architectural, security, and data best practices and patterns for architects and engineers who want to build reliable enterprise-scale serverless solutions. Sheen Brisals, an AWS Serverless Hero, and Luke Hedger, an AWS Community Builder, outline the serverless adoption requirements for an enterprise, examine the development tools your team needs, and explain in depth the nuances of testing event-driven and distributed serverless services. You'll gain practical guidance for keeping up with change and learn how to build serverless solutions with sustainability in mind. Examine the serverless technology ecosystem and AWS services needed to develop serverless applications; learn the approach and preparation required for a successful serverless adoption in an enterprise; learn serverless architectures and implementation patterns; design, develop, and test distributed serverless microservices on AWS cloud; apply security best practices while building serverless solutions; identify and adapt the implementation patterns for your particular use case; incorporate the necessary measures for observable serverless applications; implement sustainable serverless applications in the cloud "--

Trillions of lines of code help us in our lives, companies, and organizations. But just a single software cybersecurity vulnerability can stop entire companies from doing business and cause billions of dollars in revenue loss and business recovery. Securing the creation and deployment of software, also known as software supply chain security, goes well beyond the software development process. This practical book gives you a comprehensive look at security risks and identifies the practical controls you need to incorporate into your end-to-end software supply chain. Author Cassie Crossley demonstrates how and why everyone involved in the supply chain needs to participate if your organization is to improve the security posture of its software, firmware, and hardware. With this book, you'll learn how to: Pinpoint the cybersecurity risks in each part of your organization's software supply chain Find the cybersecurity frameworks and resources that can improve security Identify the roles that participate in the supply chain--including IT, development, operations, manufacturing, and procurement Design initiatives and controls for each part of the supply chain using existing frameworks and references Evaluate third-party risk in your supply chain

Microservices can be a very effective approach for delivering value to your organization and to your customers. If you get them right, microservices help you to move fast, making changes to small parts of your system hundreds of times a day. But get them wrong and microservices just make everything more complicated. In this book, technical strategist Sarah Wells provides practical, in-depth advice for moving to microservices. Having built her first microservices architecture in 2013 for the Financial Times, Sarah discusses the approaches you need to take from the start, and explains the potential traps most likely to trip you up. You'll also learn how to maintain the architecture as your systems mature while minimizing the time you spend on support and maintenance. With this book, you will: Learn the impact of microservices on software development patterns and practices Identify the organizational changes you need to make to successfully build and operate this architecture Determine the steps you must take before you move to microservices Understand the traps to avoid when you create a microservices architecture--and learn how to recover if you fall into one

Kubernetes is becoming the de-facto standard for container orchestration and distributed applications management across a microservices framework. With this practical cookbook, youll learn hands-on recipes for automating the deployment, scaling, and operations of application containers across clusters of hosts.The book's easy-lookup problem-solution-discussion format helps you find the detailed answers you needquickly. Kubernetes lets you deploy your applications quickly and predictably, so you can efficiently respond to customer demand. This cookbook, ideal for developers and system administers alike, provides the essential knowledge you need to get there.Youll find recipes for:Kubernetes installationKubernetes API, API groupsApplication primitivesMonitoringTroubleshooting

Implementing and designing systems that make suggestions to users are among the most popular and essential machine learning applications available. Whether you want customers to find the most appealing items at your online store, videos to enrich and entertain them, or news they need to know, recommendation systems (RecSys) provide the way. In this practical book, authors Bryan Bischof and Hector Yee illustrate the core concepts and examples to help you create a RecSys for any industry or scale. You'll learn the math, ideas, and implementation details you need to succeed. This book includes the RecSys platform components, relevant MLOps tools in your stack, plus code examples and helpful suggestions in PySpark, SparkSQL, FastAPI, Weights & Biases, and Kafka. You'll learn: The data essential for building a RecSys How to frame your data and business as a RecSys problem Ways to evaluate models appropriate for your system Methods to implement, train, test, and deploy the model you choose Metrics you need to track to ensure your system is working as planned How to improve your system as you learn more about your users, products, and business case

All cloud architects need to know how to build data platforms that enable businesses to make data-driven decisions and deliver enterprise-wide intelligence in a fast and efficient way. This handbook shows you how to design, build, and modernize cloud native data and machine learning platforms using AWS, Azure, Google Cloud, and multicloud tools like Snowflake and Databricks. Authors Marco Tranquillin, Valliappa Lakshmanan, and Firat Tekiner cover the entire data lifecycle from ingestion to activation in a cloud environment using real-world enterprise architectures. You'll learn how to transform, secure, and modernize familiar solutions like data warehouses and data lakes, and you'll be able to leverage recent AI/ML patterns to get accurate and quicker insights to drive competitive advantage. You'll learn how to: Design a modern and secure cloud native or hybrid data analytics and machine learning platform Accelerate data-led innovation by consolidating enterprise data in a governed, scalable, and resilient data platform Democratize access to enterprise data and govern how business teams extract insights and build AI/ML capabilities Enable your business to make decisions in real time using streaming pipelines Build an MLOps platform to move to a predictive and prescriptive analytics approach

What sets Laravel apart from other PHP web frameworks? Speed and simplicity, for starters. This rapid application development framework and its vast ecosystem of tools let you quickly build new sites and applications with clean, readable code. Fully updated to cover Laravel 5.8, the latest release, the second edition of this practical guide provides the definitive introduction to one of todays most popular web frameworks.Matt Stauffera leading teacher and developer in the Laravel communitydelivers a high-level overview and concrete examples to help experienced PHP web developers get started with Laravel right away. By the time you reach the last page, you should feel comfortable writing an entire application in Laravel from scratch.

"Cyber risk management is one of the most urgent issues facing enterprises today. This book presents a detailed framework for designing, developing, and implementing a cyber risk management program that addresses your company's specific needs. Ideal for corporate directors, senior executives, security risk practitioners, and auditors at many levels, this guide offers both the strategic insight and tactical guidance you're looking for."--Publisher's description.

"Join the technological revolution that's taking the financial world by storm. Mastering Bitcoin is your guide through the seemingly complex world of Bitcoin, providing the knowledge you need to participate in the internet of money. Whether you're building the next killer app, investing in a startup, or simply curious about the technology, this revised and expanded third edition provides essential detail to get you started. Bitcoin, the first successful decentralized digital currency, has already spawned a multibillion-dollar global economy open to anyone with the knowledge and passion to participate. Mastering Bitcoin provides the knowledge. You supply the passion" --

"This practical book shows you how to ensure that the data your organization relies on is trustworthy ... [and] explain[s] how you can use automated data quality monitoring to cover all your tables efficiently, proactively alert on issues, and resolve problems immediately"--

As tech products become more prevalent today, the demand for machine learning professionals continues to grow. But the responsibilities and skill sets required of ML professionals still vary drastically from company to company, making the interview process difficult to predict. In this guide, data science leader Susan Shu Chang shows you how to tackle the ML hiring process. Having served as principal data scientist in several companies, Chang has considerable experience as both ML interviewer and interviewee. She'll take you through the highly selective recruitment process by sharing hard-won lessons she learned along the way. You'll quickly understand how to successfully navigate your way through typical ML interviews. This guide shows you how to: Explore various machine learning roles, including ML engineer, applied scientist, data scientist, and other positions Assess your interests and skills before deciding which ML role(s) to pursue Evaluate your current skills and close any gaps that may prevent you from succeeding in the interview process Acquire the skill set necessary for each machine learning role Ace ML interview topics, including coding assessments, statistics and machine learning theory, and behavioral questions Prepare for interviews in statistics and machine learning theory by studying common interview questions

Looking for quick answers for using C# 12? This tightly focused and practical guide tells you exactly what you need to know without long intros or bloated samples. Succinct and easy to browse, this pocket reference is an ideal quick source of information. If you know Java, C++, or an earlier C# version, this guide will help you get rapidly up to speed. All programs and code snippets are available as interactive samples in LINQPad. You can edit these samples and instantly see the results without needing to set up projects in Visual Studio.

With the shift from data warehouses to data lakes, data now lands in repositories before it's been transformed, enabling engineers to model raw data into clean, well-defined datasets. dbt (data build tool) helps you take data further. This practical book shows data analysts, data engineers, BI developers, and data scientists how to create a true self-service transformation platform through the use of dynamic SQL. Authors Rui Machado from Monstarlab and Hélder Russa from Jumia show you how to quickly deliver new data products by focusing more on value delivery and less on architectural and engineering aspects. If you know your business well and have the technical skills to model raw data into clean, well-defined datasets, you'll learn how to design and deliver data models without any technical influence. With this book, you'll learn: What dbt is and how a dbt project is structured How dbt fits into the data engineering and analytics worlds How to collaborate on building data models The main tools and architectures for building useful, functional data models How to fit dbt into data warehousing and laking architecture How to build tests for data transformations

"Software engineers and architects who work with large, complex code bases need to scale and maintain them effectively. With this cookbook, author Maximiliano Contieri takes you beyond the concept of clean code by showing you how to identify improvement opportunities and assess their impact on production code. When it comes to reliability and system evolution, these techniques provide benefits that pay off over time. Using real-world examples in JavaScript, PHP, Python, Java, and many other programming languages, this cookbook provides proven recipes to help you scale and maintain large systems. Every section covers fundamental concepts including readability, coupling, testability, security, and extensibility, as well as code smells and the corresponding recipes to address them"--Page 4 of cover.

"Cloud native development gives you the power to rapidly build, secure, and scale software. But you still need to navigate many potential pitfalls along the way. Through practical examples, this book demonstrates how to use Google Cloud as a laboratory to enable rapid innovation, a factory to automate toil, a resilient, scalable, and secure citadel for running applications, and an observatory to observe them. Author Daniel Vaughan shows you how to take applications from prototype to production by combining Google Cloud services, a cloud native programming model, and best practices. By following an example project from start to finish, developers, architects, and engineering managers working with the Google Cloud Platform will learn how to build and run cloud native applications on Google Cloud with confidence." --

To help you on the path to becoming a Snowflake pro, this concise yet comprehensive guide reviews fundamentals and best practices for Snowflake's SQL and Scripting languages. Developers and data professionals will learn how to generate, modify, and query data in the Snowflake relational database management system as well as how to apply analytic functions for reporting. Author Alan Beaulieu also shows you how to create scripts, stored functions, and stored procedures to return data sets using Snowflake Scripting. This book is ideal whether you're new to databases and need to run queries or reports against a Snowflake database, or transitioning from databases such as Oracle, SQL Server, or MySQL to cloud-based platforms. With this book, you will: Generate and modify Snowflake data using INSERT, UPDATE, DELETE Query data in Snowflake using SELECT, including joining multiple tables, using subqueries, and grouping Apply analytic functions for performing subtotals, grand totals, row comparisons, and other reporting functionality Build scripts combining SQL statements with looping, if-then-else, and exception handling Learn how to build stored procedures and functions Use stored procedures to return data sets

Having a great idea or design is not enough to make your software project succeed. If you want stakeholders to buy into your design and teams to collaborate and contribute to the vision, you also need to communicate effectively. In this practical book, author Jacqui Read shows you how to successfully present your architecture and get stakeholders to jump on board. Misunderstanding and lack of buy-in leads to increasing costs, unmet requirements, and an architecture that is not what you intended. Through constructive examples and patterns, this book shows you how to create documentation and diagrams that actually get the message across to the different audiences you'll face. This book shows you how to: Design diagrams and documentation appropriate to your expected audience, intended message, and project stage Create documentation and diagrams that are accessible to those with varying roles, needs, or disabilities Master written, verbal, and nonverbal communication to succeed in technical settings Apply the communication patterns presented in this book in real-world projects and software designs Communicate and collaborate with distributed teams to successfully design and document software and technical projects

"Amazon Redshift powers analytic cloud data warehouses worldwide, from startups to some of the largest enterprise data warehouses available today. This practical guide thoroughly examines this managed service and demonstrates how you can use it to extract value from your data immediately, rather than go through the heavy lifting required to run a typical data warehouse."--Amazon.com.

This comprehensive guide shows you how to master the most importantchanges to Java since it was first released. Generics and the greatlyexpanded collection libraries have tremendously increased the power ofJava 5 and Java 6. But they have also confused many developers whohaven't known how to take advantage of these new features.Java Generics and Collections covers everything from the mostbasic uses of generics to the strangest corner cases. It teaches youeverything you need to know about the collections libraries, so you'llalways know which collection is appropriate for any given task, andhow to use it.Topics covered include:Fundamentals of generics: type parameters and generic methodsOther new features: boxing and unboxing, foreach loops, varargsSubtyping and wildcardsEvolution not revolution: generic libraries with legacy clients andgeneric clients with legacy librariesGenerics and reflectionDesign patterns for genericsSets, Queues, Lists, Maps, and their implementationsConcurrent programming and thread safety with collectionsPerformance implications of different collectionsGenerics and the new collection libraries they inspired take Java to anew level. If you want to take your software development practice toa new level, this book is essential reading.Philip Wadler is Professor of Theoretical Computer Science at theUniversity of Edinburgh, where his research focuses on the design ofprogramming languages. He is a co-designer of GJ, work thatbecame the basis for generics in Sun's Java 5.0.Maurice Naftalin is Technical Director at Morningside Light Ltd., a software consultancy in the United Kingdom. He has most recently served as an architect and mentor at NSB Retail Systems plc, and as the leader of the client development team of a major UK government social service system."e;A brilliant exposition of generics. By far the best book on thetopic, it provides a crystal clear tutorial that starts with thebasics and ends leaving the reader with a deep understanding of boththe use and design of generics."e;Gilad Bracha, Java Generics Lead, Sun Microsystems

Get a concise yet comprehensive overview of Airtable, one of the most versatile platforms to emerge from the no-code movement. Whether you're planning a new project, sharing data analysis within your organization, tracking a detailed initiative among stakeholders, or dealing with any other project that requires well-structured collaboration, this practical book shows you how Airtable is an accessible tool to tackle these challenges. Author Elliott Adams guides you through the process of structuring your data in a relational database, creating automations based on changes to data in Airtable, and building user-friendly interfaces for no-code applications. This showcases how Airtable is superior to the typical options of either non-developers using spreadsheets or making large investments in time-consuming application development. With this book, you will: Learn how Airtable can reduce the need for custom-built applications Use Airtable to replace internal tools such as spreadsheets Build applications utilizing relational data--without any knowledge of software programming Evaluate whether you can build a solution on Airtable rather than purchasing software Understand the limitations of the Airtable platform when compared with writing a software application from scratch

Many UX designers are surprised to learn that much of the job isn't about drawing things. It's about knowing what to draw and how to convince people to build it. Whether you're a one-person design team making products from scratch or a C-level product leader managing many products and strategies, UX for Business is your missing guide to real-world business design. You'll not only learn how to think about design as a professional but also discover how design can move the needle for your entire company. Author Joel Marsh helps you understand stakeholders, business models, the process of designing valuable solutions, dangerous choices that can ruin a product, and how to gain the attention your work deserves. You'll also explore the principles of designing common types of digital products and services, from portfolio sites to social networks to ecosystems. With this book, you'll learn: How to design the right things by understanding value, diagnostics, and probability How to conduct UX research and analysis without the luxury of time or money The most important aspects of common digital business models Methods for getting things done under less-than-ideal circumstances How to avoid common pitfalls caused by inexperience

Despite the increase of high-profile hacks, record-breaking data leaks, and ransomware attacks, many organizations dont have the budget to establish or outsource an information security (InfoSec) program, forcing them to learn on the job. For companies obliged to improvise, this pragmatic guide provides a security-101 handbook with steps, tools, processes, and ideas to help you drive maximum-security improvement at little or no cost.Each chapter in this book provides step-by-step instructions for dealing with a specific issue, including breaches and disasters, compliance, network infrastructure and password management, vulnerability scanning, and penetration testing, among others. Network engineers, system administrators, and security professionals will learn tools and techniques to help improve security in sensible, manageable chunks.Learn fundamentals of starting or redesigning an InfoSec programCreate a base set of policies, standards, and proceduresPlan and design incident response, disaster recovery, compliance, and physical securityBolster Microsoft and Unix systems, network infrastructure, and password managementUse segmentation practices and designs to compartmentalize your networkExplore automated process and tools for vulnerability managementSecurely develop code to reduce exploitable errorsUnderstand basic penetration testing concepts through purple teamingDelve into IDS, IPS, SOC, logging, and monitoring