Most data professionals work with multiple datasets scattered across teams, systems, and formats. But without a clear modeling strategy, the result is often chaos: mismatched schemas, fragile pipelines, and a constant fight to make sense of the noise. This essential guide offers a better way by introducing a practical framework for designing high-quality data models that work across platforms while supporting the growing demands of AI, analytics, and real-time systems. Author Jun Shan bridges the gap between disconnected modeling approaches and the need for a unified, system-agnostic methodology. Whether you're building a new data platform or rethinking legacy infrastructure, Universal Data Modeling gives you the clarity, patterns, and tools to model data that's consistent, resilient, and ready to scale. Connect conceptual, logical, and physical modeling phases with confidence Apply best-fit techniques across relational, semistructured, and NoSQL formats Improve data quality, clarity, and maintainability across your organization Support modern design paradigms like data mesh and data products Translate domain knowledge into models that empower teams Build flexible, scalable models that stand the test of technology change

Bring your data to life with the ultimate beginner's guide to Power BI, now featuring Microsoft Fabric, Copilot, and full-color visuals to make learning data modeling, storytelling, and dashboards easier and faster than ever Key Features Build data literacy and gain confidence using Power BI through real-world, beginner-friendly examples Learn to shape, clean, and model data using Power BI Desktop and Power Query, with zero experience required Build vibrant, accurate reports and dashboards with real-world modeling examples Book Description Updated with the latest innovations in Power BI, including integration with Microsoft Fabric for seamless data unification and Copilot for AI-powered guidance. This comprehensive guide empowers you to build compelling reports and dashboards from the ground up. Whether you're new to Power BI or stepping into a data role, this book provides a friendly, approachable introduction to business intelligence and data storytelling You'll start with the Power BI Desktop interface and its core functionality, then move into shaping and cleaning your data using the Power Query Editor. From designing intuitive data models to writing your first DAX formulas, you’ll develop practical skills that apply directly to real-world scenarios. he book emphasizes how to use visualizations and narrative techniques to turn numbers into meaningful insights The chapters focus on hands-on, real-world examples—like analyzing sales trends, tracking KPIs, and cleaning messy data. You'll learn to build and refresh reports, scale your Power BI setup, and enhance your solutions using Microsoft Fabric and Copilot. Fabric unifies analytics across your organization, while Copilot speeds up your workflow with AI-driven insights and report suggestions By the end of the book, you’ll have the confidence and experience to turn raw data into insightful, impactful dashboards What you will learn Understand why data literacy matters in decision-making and careers Connect to data using import, DirectQuery, and live connection modes Clean and transform data using Power Query Editor and dataflows Design reports with visuals that support clear data storytelling Apply row-level security to enforce access and data protection Manage and monitor Power BI cloud for scalability and teamwork Use AI tools like Copilot to speed up prep and generate insights Learn Microsoft Fabric basics to enable unified data experiences Who this book is for This book is ideal for anyone looking to build a solid foundation in Power BI, regardless of prior experience. Whether you're just starting out or stepping into a new role that involves data, you'll find clear, approachable guidance throughout. The step-by-step tutorials and real-world examples make it easy to follow along—even if it’s your first time working with business intelligence tools

Design powerful financial reports in Power BI by building models, measures, and dashboards tailored for real-world accounting and analytics Key Features Build a complete financial data model from ledgers, journals, and budgets Master DAX for income statements, KPIs, and performance analysis Learn Power BI Paginated and AI tools for printable and predictive reporting Purchase of the print or Kindle book includes a free PDF eBook Book Description Power BI for Financial Reporting is the definitive guide to designing high-performance, flexible, and insightful financial reports using Power BI. This book empowers finance and BI professionals to create everything from trial balances to enterprise-wide performance dashboards with ease and precision. The book starts by helping you define your reporting goals and data sources, mapping these needs to Power BI’s capabilities. You’ll then build a core financial data model—covering ledger transactions, charts of accounts, and multi-company support. As you proceed, you’ll integrate complex DAX measures, handle foreign exchange and journal entries, and extend your model with budgeting and inventory data. Each chapter builds toward a comprehensive suite of reports, complete with visual best practices and tested metrics. You’ll learn to streamline datasets using Power Query, test for data integrity, and generate printable reports via Power BI Paginated. The final chapters dive into using AI, predictive analytics, and Microsoft Fabric to future-proof your reporting. Whether you're consolidating data across systems or evolving your reports for changing business needs, this hands-on guide ensures you’re prepared to meet the demands of modern finance. What you will learn Build core financial models from ledgers and accounts Create Trial Balance and Income Statements using DAX Optimize Power BI with Power Query and data transformation Add budgets, targets, and KPIs to performance dashboards Integrate inventory data for nuanced stock reporting Produce printable reports using Power BI Paginated Apply AI for report generation and predictive analytics Test, tune, and evolve reports for secure, scalable use Who this book is for This book is for finance professionals, accountants, financial analysts, and BI developers who want to leverage Power BI to improve, automate, and future-proof their financial reporting. Whether consolidating data from ERPs, building reports across entities, or exploring advanced Power BI features, this book equips readers with practical skills and strategic insight.

In the evolving landscape of SAP development, performance is no longer just a nice-to-have—it's a necessity. With the power of SAP HANA and the enhancements introduced in ABAP 7.5, developers are now equipped to rethink how applications are built, executed, and optimized. This book is your guide to that transformation. We begin by understanding the core shift: moving data-intensive operations directly into the HANA database. When implemented correctly, this "code pushdown" philosophy dramatically reduces data transfer and processing overhead. AMDP (ABAP Managed Database Procedures), our in-database processing engine, enables us to write complex logic directly in SQLScript, harnessing HANA’s parallel processing capabilities. We focus on crafting efficient AMDP procedures by adopting set-based operations and minimizing unnecessary data movement. Next, we explore Core Data Services (CDS) Views, our go-to data modeling tool. CDS Views are not just simple database views; they act as semantic layers that define how our applications interact with data. We learn to create optimized CDS Views by leveraging associations, annotations, and table functions, enabling us to build reusable, high-performance data models. These views simplify complex queries, improve data consistency, and enhance application flexibility. We then turn to Native SQL, our direct line to the HANA database. While AMDP and CDS Views provide powerful abstractions, Native SQL offers ultimate control for specialized tasks. We embed Native SQL within AMDP procedures to access database-specific features and fine-tune performance for critical operations. Along the way, we apply best practices for writing efficient queries, with a strong focus on indexing, join strategies, and precise data filtering. Throughout this journey, we emphasize the importance of rigorous testing and proactive monitoring. Just like a race car undergoes extensive testing before hitting the track, our ABAP applications require careful validation to ensure accuracy and optimal performance. We explore techniques for unit testing AMDP procedures, validating CDS Views, and monitoring query performance. We also look at strategies for detecting and addressing potential bottlenecks before they affect end users. SAP ABAP 7.5 Optimization for HANA is not just about writing faster code—it’s about fundamentally rethinking how we develop applications. By embracing code pushdown, leveraging AMDP, CDS Views, and Native SQL, and implementing robust testing and monitoring strategies, we build ABAP applications that are not only faster, but also more scalable, maintainable, and adaptable to the ever-evolving demands of modern business. You Will: Learn how to implement the "code pushdown" philosophy, moving data-intensive operations directly into the HANA database to reduce data transfer and processing overhead Understand to create optimized CDS Views, leveraging associations, annotations, and table functions to build reusable, high-performance data models that simplify complex queries and improve data consistency. Explore how to write complex logic directly in SQLScript using AMDP, harnessing HANA's parallel processing capabilities, and using Native SQL for specialized tasks, accessing database-specific features to optimize performance. This Book is For: ABAP Developers, SAP Consultants and Architects and IT Managers and Technical Leads

Are you ready to turn your data into powerful insights and make smarter business decisions? Microsoft Power BI Step by Step is your hands-on guide to mastering one of todays most in-demand business intelligence tools. Written by certified Power BI experts Nuric Ugarte and José Rafael Escalanteleaders in the Power BI community, with years of real-world consulting and teaching experiencethis book takes you from your very first steps in Power BI all the way to advanced data modeling, DAX calculations, and sharing interactive reports with your team. Whether youre a business analyst, data professional, Excel power user, or IT decision-maker, youll find clear, step-by-step instructions and practical exercises that make learning Power BI approachable and effective. Youll learn how to connect to a wide range of data sources, clean and transform your data, create stunning visualizations, and collaborate securely in the Power BI Service. Plus, youll discover how to use the latest features, including Copilot, to streamline your workflow and get answers faster. If you want to build your data skills, impress your organization, and unlock the full potential of Power BI, this is the book you need to get thereone step at a time.

Grow your software engineering discipline, incorporating and mastering design, development, testing, and deployment best practices examples in a realistic Python project structure. Key Features Understand what makes Software Engineering a discipline, distinct from basic programming Gain practical insight into updating, refactoring, and scaling an existing Python system Implement robust testing, CI/CD pipelines, and cloud-ready architecture decisions Book Description Software engineering is more than coding; it’s the strategic design and continuous improvement of systems that serve real-world needs. This newly updated second edition of Hands-On Software Engineering with Python expands on its foundational approach to help you grow into a senior or staff-level engineering role. Fully revised for today’s Python ecosystem, this edition includes updated tooling, practices, and architectural patterns. You’ll explore key changes across five minor Python versions, examine new features like dataclasses and type hinting, and evaluate modern tools such as Poetry, pytest, and GitHub Actions. A new chapter introduces high-performance computing in Python, and the entire development process is enhanced with cloud-readiness in mind. You’ll follow a complete redesign and refactor of a multi-tier system from the first edition, gaining insight into how software evolves—and what it takes to do that responsibly. From system modeling and SDLC phases to data persistence, testing, and CI/CD automation, each chapter builds your engineering mindset while updating your hands-on skills. By the end of this book, you'll have mastered modern Python software engineering practices and be equipped to revise and future-proof complex systems with confidence. What you will learn Distinguish software engineering from general programming Break down and apply each phase of the SDLC to Python systems Create system models to plan architecture before writing code Apply Agile, Scrum, and other modern development methodologies Use dataclasses, pydantic, and schemas for robust data modeling Set up CI/CD pipelines with GitHub Actions and cloud build tools Write and structure unit, integration, and end-to-end tests Evaluate and integrate tools like Poetry, pytest, and Docker Who this book is for This book is for Python developers with a basic grasp of software development who want to grow into senior or staff-level engineering roles. It’s ideal for professionals looking to deepen their understanding of software architecture, system modeling, testing strategies, and cloud-aware development. Familiarity with core Python programming is required, as the book focuses on applying engineering principles to maintain, extend, and modernize real-world systems.

Seasoned Experts Alberto Ferrari and Marco Russo Help You Master DAX for Superior Business Intelligence Solutions The Definitive Guide to DAX is an authoritative resource for mastering the DAX language, which is pivotal for creating measures for semantic models in Microsoft Power BI, Fabric, Analysis Services, and Excel. With years of experience since the inception of Power Pivot, the authors offer a comprehensive reference that navigates through the unique and complex concepts of DAX, making it an essential tool for BI professionals. This third edition updates you with the latest features and provides a framework for writing efficient DAX code, enhancing your ability to customize calculations in data models. You will gain the skills necessary to understand and apply advanced DAX concepts, structure code in user-defined functions, and leverage new calendars for time intelligence calculations. By reading this book, you will: Understand the foundational concepts of DAX and its unique language structure Master the use of evaluation contexts to enhance data analysis Utilize CALCULATE and CALCULATETABLE functions effectively Implement variables to simplify complex DAX expressions Leverage classic and new calendar based time intelligence functions Work with iterators to perform advanced calculations Apply visual calculations to improve report interactivity Create and manage calculation groups for dynamic reporting Handle complex hierarchies and relationships in data models Author DAX queries for testing and troubleshooting About This Book For BI professionals and Excel power users eager to deepen their understanding of DAX and enhance their data modeling capabilities with advanced techniques For data analysts and IT specialists seeking to optimize their use of Microsoft Power BI, Fabric, Analysis Services, and Excel for more efficient and insightful data analysis

Build effective data models and reports in Power BI for financial planning, budgeting, and valuations with practical templates, logic, and step-by-step guidance. Free with your book: DRM-free PDF version + access to Packt's next-gen Reader Key Features Engineer optimal star schema data models for financial planning and analysis Implement common financial logic, calendars, and variance calculations Create dynamic, formatted reports for income statements, balance sheets, and cash flow Purchase of the print or Kindle book includes a free PDF eBook Book Description Martin Kratky brings his global experience of over 20 years as co-founder of Managility and creator of Acterys to empower CFOs and accountants with Power BI for Finance through this hands-on guide to streamlining and enhancing financial processes. Starting with the foundation of every effective BI solution, a well-designed data model, the book shows you how to structure star schemas and integrate common financial data sources like ERP and accounting systems. You’ll then learn to implement key financial logic using DAX and M, covering calendars, KPIs, and variance calculations. The book offers practical advice on creating clear and compliant financial reports, such as income statements, balance sheets, and cash flows with visual design and formatting best practices. With dedicated chapters on advanced workflows, you’ll learn how to handle multi-currency setups, perform group consolidations, and implement planning models like rolling forecasts, annual budgets, and sales and operations planning (S&OP). As you advance, you’ll gain insights from real-world case studies covering company valuations, Excel integration, and the use of write-back methods with Dynamics Business Performance Planning and Acterys. The concluding chapters highlight how AI and Copilot enhance financial analytics. Email sign-up and proof of purchase required What you will learn Apply multi-currency handling and group consolidation techniques in Power BI Model discounted cash flow and company valuation scenarios Design and manage write-back workflows with Dynamics BPP and Acterys Integrate Excel and Power BI using live connections and cube formulas Utilize AI, Copilot, and LLMs to enhance automation and insight generation Create complete finance-focused dashboards for sales and operations planning Who this book is for This book is for finance professionals including CFOs, FP&A managers, controllers, and certified accountants who want to enhance reporting, planning, and forecasting using Power BI. Basic familiarity with Power BI and financial concepts is recommended to get the most out of this hands-on guide.

Get up to speed on a new unified approach to building machine learning (ML) systems with a feature store. Using this practical book, data scientists and ML engineers will learn in detail how to develop and operate batch, real-time, and agentic ML systems. Author Jim Dowling introduces fundamental principles and practices for developing, testing, and operating ML and AI systems at scale. You'll see how any AI system can be decomposed into independent feature, training, and inference pipelines connected by a shared data layer. Through example ML systems, you'll tackle the hardest part of ML systems--the data, learning how to transform data into features and embeddings, and how to design a data model for AI. Develop batch ML systems at any scale Develop real-time ML systems by shifting left or shifting right feature computation Develop agentic ML systems that use LLMs, tools, and retrieval-augmented generation Understand and apply MLOps principles when developing and operating ML systems

Dive into 'Microsoft Power Platform Solution Architect's Handbook' to master the art of designing and delivering enterprise-grade solutions using Microsoft's cutting-edge Power Platform. Through a mix of practical examples and hands-on tutorials, this book equips you to harness tools like AI, Copilot, and DevOps for building innovative, scalable applications tailored to enterprise needs. What this Book will help me do Acquire the knowledge to effectively utilize AI tools such as Power Platform Copilot and ChatGPT to enhance application intelligence. Understand and apply enterprise-grade solution architecture principles for scalable and secure application development. Gain expertise in integrating heterogenous systems with Power Platform Pipes and third-party APIs. Develop proficiency in creating and maintaining reusable Dataverse data models. Learn to establish and manage a Center of Excellence to govern and scale Power Platform solutions. Author(s) Hugo Herrera is an experienced solution architect specializing in the Microsoft Power Platform with a deep focus on integrating AI and cloud-native strategies. With years of hands-on experience in enterprise software development and architectural design, Hugo brings real-world insights into his writing, emphasizing practical application of advanced concepts. His approach is clear, structured, and aimed at empowering readers to excel. Who is it for? This book is tailored for IT professionals like solution architects, enterprise architects, and technical consultants who are looking to elevate their capabilities in Power Platform development. It is also suitable for individuals with an intermediate understanding of Power Platform seeking to spearhead enterprise-level digital transformation projects. Ideal readers are those ready to deepen their integration, data modeling, and AI usage skills within the Microsoft ecosystem, particularly for enterprise applications.

There are already excellent books on software programming for data processing and data transformation for instance: Wes McKinney’s. This book, reflecting on my own industrial and teaching experience, tries to overcome the big learning curve newcomers to the field have to travel before they are ready to tackle real data science and AI challenges. In this regard this book is different to other books in that:

It assumes zero software programming knowledge. This instructional design is intentional given the book’s aim to open the practice of data science to anyone interested in data exploration and analysis irrespective of their previous background.

It follows an incremental approach to facilitate the assimilation of, sometimes, arcane software techniques to manipulate data.

It is practice oriented to ensure readers can apply what they learn in their daily practices.

Illustrates how to use generative AI to help you become a more productive data scientist and AI engineer.

By reading and working on the labs included in this book you will develop software programming skills required to successfully contribute to the data understanding and data preparation stages involved in any data related project. You will become proficient at manipulating and transforming datasets in industrial contexts and produce clean, reliable datasets that can drive accurate analysis and informed decision-making. Moreover you will be prepared to develop and deploy dashboards and visualizations supporting the insights and conclusions in the deployment stage.

Data modelling and evaluation are not covered in this book. We are working on a second installment of the book series illustrating the application of statistical and machine learning techniques to derive data insights.

Get started fast with MongoDB architecture, core operations, and AI-powered tools for building intelligent applications Free with your book: DRM-free PDF version + access to Packt's next-gen Reader Key Features Quickly grasp the MongoDB architecture and distributed design principles Learn practical data modeling, CRUD operations, and aggregation techniques Explore AI-enabled tools for building intelligent applications with MongoDB Purchase of the print or Kindle book includes a free PDF eBook Book Description Modern applications demand flexibility, speed, and intelligence, and MongoDB delivers all three. This mini guide wastes no time, offering a concise, practical introduction to handling data flexibly and efficiently with MongoDB. MongoDB Essentials helps developers, architects, database administrators, and decision makers get started quickly and confidently. The book introduces MongoDB’s core principles, from the document data model to its distributed architecture, including replica sets and sharding. It then helps you build hands-on skills such as installing MongoDB, designing effective data schemas, performing CRUD operations, and working with the aggregation pipeline. You’ll discover performance tips along the way and learn how AI-enhanced tools like Atlas Search and Atlas Vector Search power intelligent application development. With clear explanations and a practical approach, this book gives you the foundation and skills you need to start working with MongoDB right away. Email sign-up and proof of purchase required What you will learn Understand MongoDB's document model and architecture Set up local MongoDB deployments quickly Design schemas tailored to application access patterns Perform CRUD and aggregation operations efficiently Use tools to optimize query performance and scalability Explore AI-powered features such as Atlas Search and Atlas Vector Search Who this book is for This book is for anyone looking to explore MongoDB, including students, developers, system architects, managers, database administrators, and decision makers who want to familiarize themselves with what a modern database can offer. Whether you're building your first application or exploring what MongoDB can do for you, this book is the idea starting point for your MongoDB journey.

The official guide to MongoDB architecture, tools, and cloud features, written by leading MongoDB subject matter experts to help you build secure, scalable, high-performance applications Key Features Design resilient, secure solutions with high performance and scalability Streamline development with modern tooling, indexing, and AI-powered workflows Deploy and optimize in the cloud using advanced MongoDB Atlas features Purchase of the print or Kindle book includes a free PDF eBook Book Description Delivering secure, scalable, and high-performance applications is never easy, especially when systems must handle growth, protect sensitive data, and perform reliably under pressure. The Official MongoDB Guide addresses these challenges with guidance from MongoDB’s top subject matter experts, so you learn proven best practices directly from those who know the technology inside out. This book takes you from core concepts and architecture through to advanced techniques for data modeling, indexing, and query optimization, supported by real-world patterns that improve performance and resilience. It offers practical coverage of developer tooling, IDE integrations, and AI-assisted workflows that will help you work faster and more effectively. Security-focused chapters walk you through authentication, authorization, encryption, and compliance, while chapters dedicated to MongoDB Atlas showcase its robust security features and demonstrate how to deploy, scale, and leverage platform-native capabilities such as Atlas Search and Atlas Vector Search. By the end of this book, you’ll be able to design, build, and manage MongoDB applications with the confidence that comes from learning directly from the experts shaping the technology. What you will learn Build secure, scalable, and high-performance applications Design efficient data models and indexes for real workloads Write powerful queries to sort, filter, and project data Protect applications with authentication and encryption Accelerate coding with AI-powered and IDE-based tools Launch, scale, and manage MongoDB Atlas with confidence Unlock advanced features like Atlas Search and Atlas Vector Search Apply proven techniques from MongoDB's own engineering leaders Who this book is for This book is for developers, database professionals, architects, and platform teams who want to get the most out of MongoDB. Whether you’re building web apps, APIs, mobile services, or backend systems, the concepts covered here will help you structure data, improve performance, and deliver value to your users. No prior experience with MongoDB is required, but familiarity with databases and programming will be helpful.

Data Modeling with Snowflake provides a clear and practical guide to mastering data modeling tailored to the Snowflake Data Cloud. By integrating foundational principles of database modeling with Snowflake's unique features and functionality, this book empowers you to create scalable, cost-effective, and high-performing data solutions. What this Book will help me do Apply universal data modeling concepts within the Snowflake platform effectively. Leverage Snowflake's features such as Time Travel and Zero-Copy Cloning for optimized data solutions. Understand and utilize advanced techniques like Data Vault and Data Mesh for scalable data architecture. Master handling semi-structured data in Snowflake using practical recipes and examples. Achieve cost efficiency and resource optimization by aligning modeling principles with Snowflake's architecture. Author(s) Serge Gershkovich is an accomplished data engineer and seasoned professional in data architecture and modeling. With a passion for simplifying complex concepts, Serge's work leverages his years of hands-on experience to guide readers in mastering both foundational and advanced data management practices. His clear and practical approach ensures accessibility for all levels. Who is it for? This book is ideal for data developers and engineers seeking practical modeling guidance within Snowflake. It's suitable for data analysts looking to broaden their database design expertise, and for database beginners aiming to get a head start in structuring data. Professionals new to Snowflake will also find its clear explanations of key features aligned with modeling techniques invaluable.

"Learning Tableau 2025" provides a comprehensive guide to mastering Tableau's latest features, including advanced AI capabilities like Tableau Pulse and Agent. This book, authored by Tableau expert Joshua N. Milligan, will equip you with the tools to transform complex data into actionable insights and interactive dashboards. What this Book will help me do Learn to use Tableau's advanced AI features, including Tableau Agent and Pulse, to streamline data analysis and automate insights. Develop skills to create and customize dynamic dashboards tailored to interactive data storytelling. Understand and utilize new geospatial functions within Tableau for advanced mapping and analytics. Master Tableau Prep's enhanced data preparation capabilities for efficient data modeling and structuring. Learn to effectively integrate and analyze data from multiple sources, enhancing your ability to extract meaningful insights. Author(s) Joshua N. Milligan, a Tableau Zen Master and Visionary, has years of experience in the field of data visualization and analytics. With a hands-on approach, Joshua combines his expertise and passion for Tableau to make complex topics accessible and engaging. His teaching method ensures that readers gain practical, actionable knowledge. Who is it for? This book is ideal for aspiring business intelligence developers, data analysts, data scientists, and professionals seeking to enhance their data visualization skills. It's suitable for both beginners looking to get started with Tableau and experienced users eager to explore its new features. A Tableau license or access to a 14-day trial is recommended.

Deliver flexible, scalable, and high-performance data storage that's perfect for AI and other modern applications with MongoDB 8.0 and MongoDB Atlas multi-cloud data platform. In MongoDB 8.0 in Action, Third Edition you'll find comprehensive coverage of the latest version of MongoDB 8.0 and the MongoDB Atlas multi-cloud data platform. Learn to utilize MongoDB’s flexible schema design for data modeling, scale applications effectively using advanced sharding features, integrate full-text and vector-based semantic search, and more. This totally revised new edition delivers engaging hands-on tutorials and examples that put MongoDB into action! In MongoDB 8.0 in Action, Third Edition you'll: Master new features in MongoDB 8.0 Create your first, free Atlas cluster using the Atlas CLI Design scalable NoSQL databases with effective data modeling techniques Master Vector Search for building GenAI-driven applications Utilize advanced search capabilities in MongoDB Atlas, including full-text search Build Event-Driven Applications with Atlas Stream Processing Deploy and manage MongoDB Atlas clusters both locally and in the cloud using the Atlas CLI Leverage the Atlas SQL interface for familiar SQL querying Use MongoDB Atlas Online Archive for efficient data management Establish robust security practices including encryption Master backup and restore strategies Optimize database performance and identify slow queries MongoDB 8.0 in Action, Third Edition offers a clear, easy-to-understand introduction to everything in MongoDB 8.0 and MongoDB Atlas—including new advanced features such as embedded config servers in sharded clusters, or moving an unsharded collection to a different shard. The book also covers Atlas stream processing, full text search, and vector search capabilities for generative AI applications. Each chapter is packed with tips, tricks, and practical examples you can quickly apply to your projects, whether you're brand new to MongoDB or looking to get up to speed with the latest version. About the Technology MongoDB is the database of choice for storing structured, semi-structured, and unstructured data like business documents and other text and image files. MongoDB 8.0 introduces a range of exciting new features—from sharding improvements that simplify the management of distributed data, to performance enhancements that stay resilient under heavy workloads. Plus, MongoDB Atlas brings vector search and full-text search features that support AI-powered applications. About the Book MongoDB 8.0 in Action, Third Edition you’ll learn how to take advantage of all the new features of MongoDB 8.0, including the powerful MongoDB Atlas multi-cloud data platform. You’ll start with the basics of setting up and managing a document database. Then, you’ll learn how to use MongoDB for AI-driven applications, implement advanced stream processing, and optimize performance with improved indexing and query handling. Hands-on projects like creating a RAG-based chatbot and building an aggregation pipeline mean you’ll really put MongoDB into action! What's Inside The new features in MongoDB 8.0 Get familiar with MongoDB’s Atlas cloud platform Utilizing sharding enhancements Using vector-based search technologies Full-text search capabilities for efficient text indexing and querying About the Reader For developers and DBAs of all levels. No prior experience with MongoDB required. About the Author Arek Borucki is a MongoDB Champion, certified MongoDB and MongoDB Atlas administrator with expertise in distributed systems, NoSQL databases, and Kubernetes. Quotes An excellent resource with real-world examples and best practices to design, optimize, and scale modern applications. - Advait Patel, Broadcom Essential MongoDB resource. Covers new features such as full-text search, vector search, AI, and RAG applications. - Juan Roy, Credit Suisse Reflects author’s practical experience and clear teaching style. It’s packed with real-world examples and up-to-date insights. - Rajesh Nair, MongoDB Champion & community leader This book will definitely make you a MongoDB star! - Vinicios Wentz, JP Morgan & Chase Co.

This comprehensive guide book equips you with the knowledge and confidence needed to prep for the exam and thrive as a Power Platform Solution Architect. The book starts with a foundation for successful solution architecture, emphasizing essential skills such as requirements gathering, governance, and security. You will learn to navigate customer discovery, translate business needs into technical requirements, and design solutions that address both functional and non-functional needs. The second part of the book delves into the Microsoft Power Platform ecosystem, offering an in-depth look at its core components—Power Apps, Power Automate, Power BI, Microsoft Copilot, and Robotic Process Automation (RPA). Detailed insights into data modeling, security strategies, and AI integration will guide you in building scalable, secure solutions. Coverage of application life cycle management, which empowers solution architects to design, implement, and deploy Power Platform solutions effectively, is discussed next. You will then go through real-world scenarios, giving you a practical understanding of the challenges and considerations in managing Power Platform projects within a business context. The book concludes with strategies for continuous learning and resources for professional development, including practice questions to assess knowledge and readiness for the PL-600 exam. After reading the book, you will be ready to take the exam and become a successful Power Platform Solution Architect. What You Will Learn Understand the Solution Architect's role, responsibilities, and strategic approaches to successfully navigate projects Master the basics of Power Platform Solution Architecture Understand governance, security, and integration concepts in real-world scenarios Design and deploy effective business solutions using Power Platform components Gain the skills necessary to prep for the PL-600 certification exam Who This Book Is For Professionals pursuing Microsoft PL-600 Solution Architect certification and IT consultants and developers transitioning to solution architect roles

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

Complete eight data science projects that lock in important real-world skills—along with a practical process you can use to learn any new technique quickly and efficiently. Data analysts need to be problem solvers—and The Well-Grounded Data Analyst will teach you how to solve the most common problems you'll face in industry. You'll explore eight scenarios that your class or bootcamp won’t have covered, so you can accomplish what your boss is asking for. In The Well-Grounded Data Analyst you'll learn: High-value skills to tackle specific analytical problems Deconstructing problems for faster, practical solutions Data modeling, PDF data extraction, and categorical data manipulation Handling vague metrics, deciphering inherited projects, and defining customer records The Well-Grounded Data Analyst is for junior and early-career data analysts looking to supplement their foundational data skills with real-world problem solving. As you explore each project, you'll also master a proven process for quickly learning new skills developed by author and Half Stack Data Science podcast host David Asboth. You'll learn how to determine a minimum viable answer for your stakeholders, identify and obtain the data you need to deliver, and reliably present and iterate on your findings. The book can be read cover-to-cover or opened to the chapter most relevant to your current challenges. About the Technology Real world data analysis is messy. Success requires tackling challenges like unreliable data sources, ambiguous requests, and incompatible formats—often with limited guidance. This book goes beyond the clean, structured examples you see in classrooms and bootcamps, offering a step-by-step framework you can use to confidently solve any data analysis problem like a pro. About the Book The Well-Grounded Data Analyst introduces you to eight scenarios that every data analyst is bound to face. You’ll practice author David Asboth’s results-oriented approach as you model data by identifying customer records, navigate poorly-defined metrics, extract data from PDFs, and much more! It also teaches you how to take over incomplete projects and create rapid prototypes with real data. Along the way, you’ll build an impressive portfolio of projects you can showcase at your next interview. What's Inside Deconstructing problems Handling vague metrics Data modeling Categorical data manipulation About the Reader For early-career data scientists. About the Author David Asboth is a data generalist educator, and software architect. He co-hosts the Half Stack Data Science podcast. Quotes Well reasoned and well written, with approaches to solve many sorts of data analysis problems. - Naomi Ceder, Fellow of the Python Software Foundation An excellent resource for any aspiring data scientist! - Andrew R. Freed, IBM David’s clear and repeatable framework will give you confidence to tackle open-ended stakeholder requests and reach an answer much faster! - Shaun McGirr, DevOn Software Services A book version of shadowing a senior data analyst while they explain handling frequent data problems at work, including all the ugly gotchas. - Randy Au, Google

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.