The complete series will cover the entire life cycle of defining and designing to developing and delivering digital solutions. It will also support the BCS International Diploma in Solution Development and includes extensive references for further study.

Ensuring data usability is paramount to unlocking a company’s full potential and driving informed decision-making. Part of author Saurav Bhattacharya’s trilogy that covers the essential pillars of digital ecosystems—security, reliability, and usability—this book offers a comprehensive exploration of the fundamental concepts, principles, and practices essential for enhancing data accessibility and effectiveness. You’ll study the core aspects of data design, standardization, and interoperability, gaining the knowledge needed to create and maintain high-quality data environments. By examining the tools and technologies that improve data usability, along with best practices for data visualization and user-centric strategies, this book serves as an invaluable resource for professionals seeking to leverage data more effectively. The book also addresses crucial governance issues, ensuring data quality, integrity, and security are maintained. Through a detailed analysis of data governance frameworks and privacy concerns, you’ll see how to manage data responsibly. Additionally, the book includes compelling case studies that highlight successful data usability implementations, future trends, and the challenges faced in achieving optimal data usability. By fostering a culture of data literacy and usability, this book will help you and your organization navigate the evolving data landscape and harness the power of data for innovation and growth. What You Will Learn Understand the fundamental concepts and importance of data usability, including effective data design, enhancing data accessibility, and ensuring data standardization and interoperability. Review the latest tools and technologies that enhance data usability, best practices for data visualization, and strategies for implementing user-centric data approaches. Ensure data quality and integrity, while navigating data privacy and security concerns. Implement robust data governance frameworks to manage data responsibly and effectively. Who This Book Is For Cybersecurity and IT professionals

Your complete Guide to preparing for the AWS® Certified Data Engineer: Associate exam The AWS® Certified Data Engineer Study Guide is your one-stop resource for complete coverage of the challenging DEA-C01 Associate exam. This Sybex Study Guide covers 100% of the DEA-C01 objectives. Prepare for the exam faster and smarter with Sybex thanks to accurate content including, an assessment test that validates and measures exam readiness, real-world examples and scenarios, practical exercises, and challenging chapter review questions. Reinforce and retain what you’ve learned with the Sybex online learning environment and test bank, accessible across multiple devices. Get ready for the AWS Certified Data Engineer exam – quickly and efficiently – with Sybex. Coverage of 100% of all exam objectives in this Study Guide means you’ll be ready for: Data Ingestion and Transformation Data Store Management Data Operations and Support Data Security and Governance ABOUT THE AWS DATA ENGINEER – ASSOCIATE CERTIFICATION The AWS Data Engineer – Associate certification validates skills and knowledge in core data-related Amazon Web Services. It recognizes your ability to implement data pipelines and to monitor, troubleshoot, and optimize cost and performance issues in accordance with best practices Interactive learning environment Take your exam prep to the next level with Sybex’s superior interactive online study tools. To access our learning environment, simply visit www.wiley.com/go/sybextestprep, register your book to receive your unique PIN, and instantly gain one year of FREE access after activation to: • Interactive test bank with 5 practice exams to help you identify areas where further review is needed. Get more than 90% of the answers correct, and you’re ready to take the certification exam. • 100 electronic flashcards to reinforce learning and last-minute prep before the exam • Comprehensive glossary in PDF format gives you instant access to the key terms so you are fully prepared

This guide to UltraEdit covers the text editor's powerful and flexible functions that go far beyond the functionality of a normal text editor for a breadth of use cases, including text/code editing, web development, system administration, development/programming, remote file editing, data filtering and sorting, and file compare. Even though UltraEdit celebrated its 30th anniversary in 2024, very few manuals exist. This book provides a well-founded introduction and exhaustively discusses all UltraEdit’s powerful functions. At the same time, the book is intended to be a solid reference and a bundled compendium for the more than four million UltraEdit customers worldwide. What You Will Learn Know the basic functions and many power functions Understand the focus of UltraEdit in the areas of programming/development, web development, database management, and system administration, as well as technical writing, editing, and publishing Get up to speed on functions and capabilities, user interface and program navigation, customization and settings, and windows arrangement and file management Know the core functions for editing and inserting data Expand your knowledge with the many view variations, formatting options, and powerful search and replace features an editor can include Perfect your workflow with many other power functions such as multi-caret editing, column mode, and FTP integration Who This Book Is For Users who are familiar with text editors but are frustrated with their limits, or who want to benefit from UltraEdit's long-established power functions

CockroachDB is the distributed SQL database that handles the demands of today's data-driven applications. The second edition of this popular hands-on guide shows software developers, architects, and DevOps/SRE teams how to use CockroachDB for applications that scale elastically and provide seamless delivery for end users while remaining indestructible. Data professionals will learn how to migrate existing applications to CockroachDB's performant, cloud-native data architecture. You'll also quickly discover the benefits of strong data correctness and consistency guarantees, plus optimizations for delivering ultra-low latencies to globally distributed end users. Uncover the power of distributed SQL Learn how to start, manage, and optimize projects in CockroachDB Explore best practices for data modeling, schema design, and distributed infrastructure Discover strategies for migrating data into CockroachDB See how to read, write, and run ACID transactions across distributed systems Maximize resiliency in multiregion clusters Secure, monitor, and fine-tune your CockroachDB deployment for peak performance

Today's data engineering teams are overwhelmed—juggling fire drills and endless requests while relying on manual, repetitive processes for building data pipelines. This much-needed tech guide from author Josh Hall introduces a practical approach to streamlining pipeline development, empowering teams to work smarter, not harder. Using Coalesce, a modern development platform, you'll learn to standardize workflows, apply reusable design patterns, and build faster, more efficient pipelines—all without piling on tech debt. Ideal for data engineers, architects, and analysts of all experience levels, the book offers clear explanations of Coalesce's core functionality including configuring environments, defining nodes, and connecting to data warehouses. Packed with workflows and useful takeaways, it's your guide to delivering high-quality, actionable data while reducing pipeline development time. Set up Coalesce and integrate with a data warehouse Use reusable nodes and design patterns for faster development Accelerate pipeline delivery with reduced manual effort Leverage Coalesce Marketplace for advanced functionality

A friendly illustrated guide to designing and implementing your first database. Grokking Relational Database Design makes the principles of designing relational databases approachable and engaging. Everything in this book is reinforced by hands-on exercises and examples. In Grokking Relational Database Design, you’ll learn how to: Query and create databases using Structured Query Language (SQL) Design databases from scratch Implement and optimize database designs Take advantage of generative AI when designing databases A well-constructed database is easy to understand, query, manage, and scale when your app needs to grow. In Grokking Relational Database Design you’ll learn the basics of relational database design including how to name fields and tables, which data to store where, how to eliminate repetition, good practices for data collection and hygiene, and much more. You won’t need a computer science degree or in-depth knowledge of programming—the book’s practical examples and down-to-earth definitions are beginner-friendly. About the Technology Almost every business uses a relational database system. Whether you’re a software developer, an analyst creating reports and dashboards, or a business user just trying to pull the latest numbers, it pays to understand how a relational database operates. This friendly, easy-to-follow book guides you from square one through the basics of relational database design. About the Book Grokking Relational Database Design introduces the core skills you need to assemble and query tables using SQL. The clear explanations, intuitive illustrations, and hands-on projects make database theory come to life, even if you can’t tell a primary key from an inner join. As you go, you’ll design, implement, and optimize a database for an e-commerce application and explore how generative AI simplifies the mundane tasks of database designs. What's Inside Define entities and their relationships Minimize anomalies and redundancy Use SQL to implement your designs Security, scalability, and performance About the Reader For self-taught programmers, software engineers, data scientists, and business data users. No previous experience with relational databases assumed. About the Authors Dr. Qiang Hao and Dr. Michail Tsikerdekis are both professors of Computer Science at Western Washington University. Quotes If anyone is looking to improve their database design skills, they can’t go wrong with this book. - Ben Brumm, DatabaseStar Goes beyond SQL syntax and explores the core principles. An invaluable resource! - William Jamir Silva, Adjust Relational database design is best done right the first time. This book is a great help to achieve that! - Maxim Volgin, KLM Provides necessary notions to design and build databases that can stand the data challenges we face. - Orlando Méndez, Experian

The "SnowPro Core Certification Study Guide" provides a comprehensive resource for mastering Snowflake data cloud concepts and passing the SnowPro Core exam. Through detailed explanations and practical exercises, you will gain the knowledge and skills necessary to successfully implement and manage Snowflake's powerful features and integrate data solutions effectively. What this Book will help me do Efficiently load and manage data in Snowflake for modern data processing. Optimize queries and configure Snowflake's performance features for data analytics. Securely implement access control and user roles to ensure data privacy. Apply Snowflake's sharing features to collaborate within and between organizations. Prepare effectively for the SnowPro Core exam with mock tests and review tools. Author(s) Jatin Verma is a renowned expert in Snowflake technologies and a certified SnowPro Core professional. With years of hands-on experience working with data solutions, Jatin excels at breaking down complex concepts into digestible lessons. His approachable writing style and dedication to education make this book a trusted resource for both aspiring and current professionals. Who is it for? This book is perfect for data engineers, analysts, database administrators, and business intelligence professionals who are looking to gain expertise in Snowflake and achieve SnowPro Core certification. It is particularly suited for those with foundational knowledge of databases, data warehouses, and SQL, seeking to advance their skills in Snowflake and become certified professionals. By leveraging this guide, readers can solidify their Snowflake knowledge and confidently approach the SnowPro Core certification exam.

Data engineers proficient in Databricks are currently in high demand. As organizations gather more data than ever before, skilled data engineers on platforms like Databricks become critical to business success. The Databricks Data Engineer Associate certification is proof that you have a complete understanding of the Databricks platform and its capabilities, as well as the essential skills to effectively execute various data engineering tasks on the platform. In this comprehensive study guide, you will build a strong foundation in all topics covered on the certification exam, including the Databricks Lakehouse and its tools and benefits. You'll also learn to develop ETL pipelines in both batch and streaming modes. Moreover, you'll discover how to orchestrate data workflows and design dashboards while maintaining data governance. Finally, you'll dive into the finer points of exactly what's on the exam and learn to prepare for it with mock tests. Author Derar Alhussein teaches you not only the fundamental concepts but also provides hands-on exercises to reinforce your understanding. From setting up your Databricks workspace to deploying production pipelines, each chapter is carefully crafted to equip you with the skills needed to master the Databricks Platform. By the end of this book, you'll know everything you need to ace the Databricks Data Engineer Associate certification exam with flying colors, and start your career as a certified data engineer from Databricks! You'll learn how to: Use the Databricks Platform and Delta Lake effectively Perform advanced ETL tasks using Apache Spark SQL Design multi-hop architecture to process data incrementally Build production pipelines using Delta Live Tables and Databricks Jobs Implement data governance using Databricks SQL and Unity Catalog Derar Alhussein is a senior data engineer with a master's degree in data mining. He has over a decade of hands-on experience in software and data projects, including large-scale projects on Databricks. He currently holds eight certifications from Databricks, showcasing his proficiency in the field. Derar is also an experienced instructor, with a proven track record of success in training thousands of data engineers, helping them to develop their skills and obtain professional certifications.

Explore Generative AI and understand its key concepts, architecture, and tangible business use cases. This book will help you develop the skills needed to use SAP AI Core service features available in the SAP Business Technology Platform. You’ll examine large language model (LLM) concepts and gain the practical knowledge to unleash the best use of Gen AI. As you progress, you’ll learn how to get started with your own LLM models and work with Generative AI use cases. Additionally, you’ll see how to take advantage Amazon Bedrock stack using AWS SDK for ABAP. To fully leverage your knowledge, Generative AI with SAP and Amazon Bedrock offers practical step-by-step instructions for how to establish a cloud SAP BTP account model and create your first GenAIartifacts. This work is an important prerequisite for those who want to take full advantage of generative AI with SAP. What You Will Learn Master the concepts and terminology of artificial intelligence and GenAI Understand opportunities and impacts for different industries with GenAI Become familiar with SAP AI Core, Amazon Bedrock, AWS SDK for ABAP and develop your firsts GenAI projects Accelerate your development skills Gain more productivity and time implementing GenAI use cases Who this Book Is For Anyone who wants to learn about Generative AI for Enterprise and SAP practitioners who want to take advantage of AI within the SAP ecosystem to support their systems and workflows.

Join the millions of people already using Microsoft Access and become a database power-user in no time! In the newly revised edition of Microsoft Access For Dummies, professional database developer and Access extraordinaire Laurie Ulrich-Fuller walks you through the ins-and-outs of one of the world's most popular database platforms. This is the perfect beginner's guide to Microsoft Access, showing you how to create databases, extract data, create reports, and more. The author demonstrates a ton of tips, tricks, and best practices you can use immediately to create, maintain, and improve your databases. You'll also find: Updates outlining edge browser controls in forms Step-by-step guides explaining how to import, export, and edit data Easy-to-follow query-writing tutorials to help you find the exact data you're looking for when you need it Whether you're a database novice or a data science whiz, Microsoft Access For Dummies has the info you need to supercharge your database skills. It's the perfect, how-to guide to get you up-to-speed on everything you need to know to get started with Microsoft's world-famous database app.

Learn what's private online (not much)—and what to do about it! Version 5.1, updated January 30, 2025 Nearly everything you do say or do online can be recorded and scrutinized by advertisers, data brokers, and a long list of other people and organizations---often without your knowledge or consent. When your personal data falls into the wrong hands, you risk theft, embarrassment, and worse. But you can take steps to greatly improve your online privacy without sacrificing all your convenience. Nowadays, online privacy is extremely hard to come by. Corporations, governments, and scammers alike go out of their way to gather up massive amounts of your personal data. The situation feels bleak, but you have more control than you may realize. In this book, Joe Kissell helps you to develop a sensible, customized online privacy strategy . No matter what devices or operating systems you use, you’ll find practical advice that ordinary people need to handle common privacy needs. The massively revised fifth edition of Take Control of Your Online Privacy is packed with information that helps you get a handle on current topics in online privacy , including data breaches, hardware bugs, quantum computing, two-factor authentication, how ads can track you, and much more. You’ll receive savvy advice about topics such as these:

Why worry? Find out who wants your private data, why they want it, and what that means to you. Determine your personal risk level , learn which privacy factors are most important to you, what you can and can't control, and what extra steps you can take if you're at a high risk of being personally targeted. Hear some good news (five steps you could take that would massively increase your online privacy)…and some bad news (why some of those steps may be difficult or infeasible). Remove personal information from Google and data brokers, though the process comes with limitations and gotchas. Discover Apple-Specific Privacy Features for users of Macs, iPhones, and iPads. Manage your internet connection: Secure your Wi-Fi network and keep your data from leaking out. Find advice on why and when to use a VPN or a network-connected privacy appliance, plus why you should be skeptical of VPN reviews. Browse and search the web: Avoid bogus websites, control your cookies and history, block ads, browse and search anonymously, and find out who is tracking you. Send and receive email: Find out how your email could be intercepted, learn techniques for encrypting email when necessary, get tips for sending email anonymously, and know when email is not the best way to communicate. Watch your social media: Understand the risks of sharing personal information online (especially on Facebook!), tweak your settings, and consider common-sense precautions. Talk and chat online: Consider to what extent any phone call, text message, or online chat is private, and find tips for enhancing privacy when using these channels. Protect your smart devices: Address privacy issues with "Internet of Things" devices like smart TVs, smart speakers, and home automation gear. Think mobile: Ponder topics like supercookies, location reporting, photo storage, spear phishing, and more as you decide how to handle privacy for a mobile phone or tablet. Help your children: As a parent, you may want to take extra steps to protect your children's privacy. Find a few key tips to keep in mind.

Prepare for success on the IAPP CIPP/US exam and further your career in privacy with this effective study guide - now includes a downloadable supplement to get you up to date on the current CIPP exam for 2024-2025! Information privacy has become a critical and central concern for small and large businesses across the United States. At the same time, the demand for talented professionals able to navigate the increasingly complex web of legislation and regulation regarding privacy continues to increase. Written from the ground up to prepare you for the United States version of the Certified Information Privacy Professional (CIPP) exam, Sybex's IAPP CIPP/US Certified Information Privacy Professional Study Guide also readies you for success in the rapidly growing privacy field. You'll efficiently and effectively prepare for the exam with online practice tests and flashcards as well as a digital glossary. The concise and easy-to-follow instruction contained in the IAPP/CIPP Study Guide covers every aspect of the CIPP/US exam, including the legal environment, regulatory enforcement, information management, private sector data collection, law enforcement and national security, workplace privacy and state privacy law, and international privacy regulation. Provides the information you need to gain a unique and sought-after certification that allows you to fully understand the privacy framework in the US Fully updated to prepare you to advise organizations on the current legal limits of public and private sector data collection and use Includes 1 year free access to the Sybex online learning center, with chapter review questions, full-length practice exams, hundreds of electronic flashcards, and a glossary of key terms, all supported by Wiley's support agents who are available 24x7 via email or live chat to assist with access and login questions Perfect for anyone considering a career in privacy or preparing to tackle the challenging IAPP CIPP exam as the next step to advance an existing privacy role, the IAPP CIPP/US Certified Information Privacy Professional Study Guide offers you an invaluable head start for success on the exam and in your career as an in-demand privacy professional.

Mastering PostgreSQL 17 is your guide to becoming a skilled PostgreSQL database administrator. Learn the latest in PostgreSQL 17, including deployment strategies, optimization approaches, and techniques for secure and high-performing database environments. This book equips you with best practices and actionable steps to elevate your PostgreSQL expertise to a professional level. What this Book will help me do Deploy and manage PostgreSQL 17 databases effectively in production environments. Utilize advanced optimization techniques to ensure queries run efficiently. Implement robust security measures, including encryption and access control. Learn and master database recovery strategies, backups, and replication. Troubleshoot real-world PostgreSQL database issues and performance bottlenecks. Author(s) Hans-Jürgen Schönig is a PostgreSQL expert with over 25 years of hands-on experience as a user and consultant. As the CEO of CYBERTEC PostgreSQL International GmbH, he has contributed extensively to the PostgreSQL community, helping clients worldwide. Hans brings a practical, solutions-focused approach to database administration drawn from supporting countless mission-critical environments. Who is it for? System and database administrators aiming to enhance their PostgreSQL expertise will find this book invaluable. It's also targeted at developers familiar with basic database concepts, seeking to deepen their understanding of PostgreSQL optimization and advanced features. Prior experience with SQL and database management is recommended. Ideal for IT professionals managing production database systems.

Explore Snowflake’s core concepts and unique features that differentiates it from industry competitors, such as, Azure Synapse and Google BigQuery. This book provides recipes for architecting and developing modern data pipelines on the Snowflake data platform by employing progressive techniques, agile practices, and repeatable strategies. You’ll walk through step-by-step instructions on ready-to-use recipes covering a wide range of the latest development topics. Then build scalable development pipelines and solve specific scenarios common to all modern data platforms, such as, data masking, object tagging, data monetization, and security best practices. Throughout the book you’ll work with code samples for Amazon Web Services, Microsoft Azure, and Google Cloud Platform. There’s also a chapter devoted to solving machine learning problems with Snowflake. Authors Dillon Dayton and John Eipe are both Snowflake SnowPro Core certified, specializing in data and digital services, and understand the challenges of finding the right solution to complex problems. The recipes in this book are based on real world use cases and examples designed to help you provide quality, performant, and secured data to solve business initiatives. What You’ll Learn Handle structured and un- structured data in Snowflake. Apply best practices and different options for data transformation. Understand data application development. Implement data sharing, data governance and security. Who This book Is For Data engineers, scientists and analysts moving into Snowflake, looking to build data apps. This book expects basic knowledge in Cloud (AWS or Azure or GCP), SQL and Python

A practical introduction to data engineering on the powerful Snowflake cloud data platform. Data engineers create the pipelines that ingest raw data, transform it, and funnel it to the analysts and professionals who need it. The Snowflake cloud data platform provides a suite of productivity-focused tools and features that simplify building and maintaining data pipelines. In Snowflake Data Engineering, Snowflake Data Superhero Maja Ferle shows you how to get started. In Snowflake Data Engineering you will learn how to: Ingest data into Snowflake from both cloud and local file systems Transform data using functions, stored procedures, and SQL Orchestrate data pipelines with streams and tasks, and monitor their execution Use Snowpark to run Python code in your pipelines Deploy Snowflake objects and code using continuous integration principles Optimize performance and costs when ingesting data into Snowflake Snowflake Data Engineering reveals how Snowflake makes it easy to work with unstructured data, set up continuous ingestion with Snowpipe, and keep your data safe and secure with best-in-class data governance features. Along the way, you’ll practice the most important data engineering tasks as you work through relevant hands-on examples. Throughout, author Maja Ferle shares design tips drawn from her years of experience to ensure your pipeline follows the best practices of software engineering, security, and data governance. About the Technology Pipelines that ingest and transform raw data are the lifeblood of business analytics, and data engineers rely on Snowflake to help them deliver those pipelines efficiently. Snowflake is a full-service cloud-based platform that handles everything from near-infinite storage, fast elastic compute services, inbuilt AI/ML capabilities like vector search, text-to-SQL, code generation, and more. This book gives you what you need to create effective data pipelines on the Snowflake platform. About the Book Snowflake Data Engineering guides you skill-by-skill through accomplishing on-the-job data engineering tasks using Snowflake. You’ll start by building your first simple pipeline and then expand it by adding increasingly powerful features, including data governance and security, adding CI/CD into your pipelines, and even augmenting data with generative AI. You’ll be amazed how far you can go in just a few short chapters! What's Inside Ingest data from the cloud, APIs, or Snowflake Marketplace Orchestrate data pipelines with streams and tasks Optimize performance and cost About the Reader For software developers and data analysts. Readers should know the basics of SQL and the Cloud. About the Author Maja Ferle is a Snowflake Subject Matter Expert and a Snowflake Data Superhero who holds the SnowPro Advanced Data Engineer and the SnowPro Advanced Data Analyst certifications. Quotes An incredible guide for going from zero to production with Snowflake. - Doyle Turner, Microsoft A must-have if you’re looking to excel in the field of data engineering. - Isabella Renzetti, Data Analytics Consultant & Trainer Masterful! Unlocks the true potential of Snowflake for modern data engineers. - Shankar Narayanan, Microsoft Valuable insights will enhance your data engineering skills and lead to cost-effective solutions. A must read! - Frédéric L’Anglais, Maxa Comprehensive, up-to-date and packed with real-life code examples. - Albert Nogués, Danone

This book provides a comprehensive approach to manage PostgreSQL cluster databases on Amazon Web Services and Azure Web Services on the cloud, as well as in Docker and container environments on a Red Hat operating system. Furthermore, detailed references for managing PostgreSQL on both Windows and Mac are provided. This book condenses all the fundamental and essential concepts you need to manage a PostgreSQL cluster into a one-stop guide that is perfect for newcomers to Postgres database administration. Each chapter of the book provides historical context and documents version changes of the PostgreSQL cluster, elucidates practical "how-to" methods, and includes illustrations and key word definitions, practices for application, a summary of key learnings, and questions to reinforce understanding. The book also outlines a clear study objective with a weekly learning schedule and hundreds of practice exercises, along with questions and answers. With its comprehensive and practical approach, this book will help you gain the confidence to manage all aspects of a PostgreSQL cluster in critical production environments so you can better support your organization's database infrastructure on the cloud and in containers. What You Will Learn Install and configure Postgres clusters on the cloud and in containers, monitor database logs, start and stop databases, troubleshoot, tune performance, backup and recover, and integrate with Amazon S3 and Azure Data Blob Manage Postgres databases on Amazon Web Services and Azure Web Services on the cloud, as well as in Docker and container environments on a Red Hat operating system Access sample references to scripting solutions and database management tools for working with Postgres, Redshift (based on Postgres 8.2), and Docker Create Amazon Machine Images (AMI) and Azure Images for managing a fleet of Postgres clusters on the cloud Reinforce knowledge with a weekly learning schedule and hundreds of practice exercises, along with questions and answers Progress from simple concepts, such as how to choose the correct instance type, to creating complex machine images Gain access to an Amazon AMI with a DBA admin tool, allowing you to learn Postgres, Redshift, and Docker in a cloud environment Refer to a comprehensive summary of documentations of Postgres, Amazon Web services, Azure Web services, and Red Hat Linux for managing all aspects of Postgres cluster management on the cloud Who This Book Is For Newcomers to PostgreSQL database administration and cross-platform support DBAs looking to master PostgreSQL on the cloud.

Recent breakthroughs in AI have not only increased demand for AI products, they've also lowered the barriers to entry for those who want to build AI products. The model-as-a-service approach has transformed AI from an esoteric discipline into a powerful development tool that anyone can use. Everyone, including those with minimal or no prior AI experience, can now leverage AI models to build applications. In this book, author Chip Huyen discusses AI engineering: the process of building applications with readily available foundation models. The book starts with an overview of AI engineering, explaining how it differs from traditional ML engineering and discussing the new AI stack. The more AI is used, the more opportunities there are for catastrophic failures, and therefore, the more important evaluation becomes. This book discusses different approaches to evaluating open-ended models, including the rapidly growing AI-as-a-judge approach. AI application developers will discover how to navigate the AI landscape, including models, datasets, evaluation benchmarks, and the seemingly infinite number of use cases and application patterns. You'll learn a framework for developing an AI application, starting with simple techniques and progressing toward more sophisticated methods, and discover how to efficiently deploy these applications. Understand what AI engineering is and how it differs from traditional machine learning engineering Learn the process for developing an AI application, the challenges at each step, and approaches to address them Explore various model adaptation techniques, including prompt engineering, RAG, fine-tuning, agents, and dataset engineering, and understand how and why they work Examine the bottlenecks for latency and cost when serving foundation models and learn how to overcome them Choose the right model, dataset, evaluation benchmarks, and metrics for your needs Chip Huyen works to accelerate data analytics on GPUs at Voltron Data. Previously, she was with Snorkel AI and NVIDIA, founded an AI infrastructure startup, and taught Machine Learning Systems Design at Stanford. She's the author of the book Designing Machine Learning Systems, an Amazon bestseller in AI. AI Engineering builds upon and is complementary to Designing Machine Learning Systems (O'Reilly).

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Your MySQL instances are probably broken. Many developers face slow-running queries, issues related to database architecture, replication, or database security—and that’s only the beginning. This book will deliver answers to your most pressing MySQL database questions related to performance, availability, or security by uncovering what causes databases to break in the first place. At its core, this book provides you with the knowledge necessary for you to break your database instances so you can better optimize it for performance and secure it from data breaches. In other words, you’ll discover the sorts of actions, minor and major, that degrade databases so you can fix and ultimately preempt them. MySQL sometimes acts according to its own rules, and this book will help you keep it working on your terms. At the same time, you will learn to optimize your backup and recovery procedures, determine when and which data to index to achieve maximum performance, and choose the best MySQL configurations, among other essential skills. Most MySQL books focus exclusively on optimization, but this book argues that it’s just as important to pay attention to the ways databases break. Indeed, after reading this book, you will be able to safely break your database instances to expose and overcome the nuanced issues that affect performance, availability, and security. What You Will Learn Know the basics of MySQL and the storage engines innoDB and MyISAM Spot the ways you are harming your database’s performance, availability and security without even realizing it Fix minor bugs and issues that have surprisingly serious impact Optimize schema, data types, queries, indexes, and partitions to head off issues Understand key MySQL security strategies Who This Book Is For Database administrators, web developers, systems administrators, and security professionals with an intermediary knowledge of database management systems and building applications in MySQL

This comprehensive guide, featuring hand-picked examples of daily use cases, will walk you through the end-to-end predictive model-building cycle using the latest techniques and industry tricks. In Chapters 1, 2, and 3, we will begin by setting up the environment and covering the basics of PySpark, focusing on data manipulation. Chapter 4 delves into the art of variable selection, demonstrating various techniques available in PySpark. In Chapters 5, 6, and 7, we explore machine learning algorithms, their implementations, and fine-tuning techniques. Chapters 8 and 9 will guide you through machine learning pipelines and various methods to operationalize and serve models using Docker/API. Chapter 10 will demonstrate how to unlock the power of predictive models to create a meaningful impact on your business. Chapter 11 introduces some of the most widely used and powerful modeling frameworks to unlock real value from data. In this new edition, you will learn predictive modeling frameworks that can quantify customer lifetime values and estimate the return on your predictive modeling investments. This edition also includes methods to measure engagement and identify actionable populations for effective churn treatments. Additionally, a dedicated chapter on experimentation design has been added, covering steps to efficiently design, conduct, test, and measure the results of your models. All code examples have been updated to reflect the latest stable version of Spark. You will: Gain an overview of end-to-end predictive model building Understand multiple variable selection techniques and their implementations Learn how to operationalize models Perform data science experiments and learn useful tips

Data Engineering with AWS Cookbook serves as a comprehensive practical guide for building scalable and efficient data engineering solutions using AWS. With this book, you will master implementing data lakes, orchestrating data pipelines, and creating serving layers using AWS's robust services, such as Glue, EMR, Redshift, and Athena. With hands-on exercises and practical recipes, you will enhance your AWS-based data engineering projects. What this Book will help me do Gain the skills to design centralized data lake solutions and manage them securely at scale. Develop expertise in crafting data pipelines with AWS's ETL technologies like Glue and EMR. Learn to implement and automate governance, orchestration, and monitoring for data platforms. Build high-performance data serving layers using AWS analytics tools like Redshift and QuickSight. Effectively plan and execute data migrations to AWS from on-premises infrastructure. Author(s) Trâm Ngọc Phạm, Gonzalo Herreros González, Viquar Khan, and Huda Nofal bring together years of collective experience in data engineering and AWS cloud solutions. Each author's deep knowledge and passion for cloud technology have shaped this book into a valuable resource, geared towards practical learning and real-world application. Their approach ensures readers are not just learning but building tangible, impactful solutions. Who is it for? This book is geared towards data engineers and big data professionals engaged in or transitioning to cloud-based environments, specifically on AWS. Ideal readers are those looking to optimize workflows and master AWS tools to create scalable, efficient solutions. The content assumes a basic familiarity with AWS concepts like IAM roles and a command-line interface, ensuring all examples are accessible yet meaningful for those seeking advancement in AWS data engineering.

Discover how to transform your data architecture with the insights and techniques presented in Managing Data as a Product by Andrea Gioia. In this comprehensive guide, you'll explore how to design, implement, and maintain data-product-centered systems to meet modern demands, achieving scalable and sustainable data management tailored to your organization's needs. What this Book will help me do Understand the principles of data-product-centered architectures and their advantages. Learn to design, develop, and operate data products in production settings. Explore strategies to manage the lifecycle of data products efficiently. Gain insights into team topologies and data ownership for distributed systems. Discover data modeling techniques for AI-ready architectures. Author(s) Andrea Gioia is a renowned data architect and the creator of the Open Data Mesh Initiative. With over 20 years of experience, Andrea has successfully led complex data projects and is passionate about sharing his expertise. His writing is practical and driven by real-world challenges, aiming to equip engineers with actionable knowledge. Who is it for? This book is ideal for data engineers, software architects, and engineering leaders involved in shaping innovative data architectures. If you have foundational knowledge of data engineering and are eager to advance your expertise by adopting data-product principles, this book will suit your needs. It is for professionals aiming to modernize and optimize their approach to organizational data management.

Large language models (LLMs) are revolutionizing the world, promising to automate tasks and solve complex problems. A new generation of software applications are using these models as building blocks to unlock new potential in almost every domain, but reliably accessing these capabilities requires new skills. This book will teach you the art and science of prompt engineering-the key to unlocking the true potential of LLMs. Industry experts John Berryman and Albert Ziegler share how to communicate effectively with AI, transforming your ideas into a language model-friendly format. By learning both the philosophical foundation and practical techniques, you'll be equipped with the knowledge and confidence to build the next generation of LLM-powered applications. Understand LLM architecture and learn how to best interact with it Design a complete prompt-crafting strategy for an application Gather, triage, and present context elements to make an efficient prompt Master specific prompt-crafting techniques like few-shot learning, chain-of-thought prompting, and RAG

FileMaker Pro is a development platform from Claris International Inc., a subsidiary of Apple Inc. The software makes it easy for everyone to create powerful, multi-user, cross-platform, relational database applications. This book navigates the reader through the software in a clear and logical manner, with each chapter building on the previous one. After an initial review of the user environment and application basics, the book delves into a deep exploration of the integrated development environment, which seamlessly combines the full stack of schema, business logic, and interface layers into a unified visual programming experience. Everything beginners need to get started is covered, along with advanced material that seasoned professionals will appreciate. Written by a professional developer with decades of real-world experience, "Learn FileMaker Pro 2024" is a comprehensive learning and reference guide. Join millions of users and developers worldwide in achieving a new level of workflow efficiency with FileMaker. For This New Edition This third edition includes clearer lessons and more examples, making it easier than ever to start planning, building, and deploying a custom database solution. It covers dozens of new and modified features introduced in versions 19.1 to 19.6, as well as the more recent 2023 (v20) and 2024 (v21) releases. Whatever your level of experience, this book has something new for you! What You’ll Learn · Plan and create custom tables, fields, and relationships · Write calculations using built-in and custom functions · Build layouts with dynamic objects, themes, and custom menus · Automate tasks with scripts and link them to objects and interface events · Keep database files secure and healthy · Integrate with external systems using ODBC, cURL, and the FM API · Deploy solutions to share with desktop, iOS, and web clients · Learn about summary reports, dynamic object references, and transactions · Delve into artificial intelligence with CoreML, OpenAI, and Semantic Finds Who This Book Is For Hobbyist developers, professional consultants, IT staff