Begin your journey toward efficient data manipulation with this robust technical guide and enhance your aggregation skills while building efficient pipelines for a variety of tasks Key Features Build effective aggregation pipelines for increased productivity and performance Solve common data manipulation and analysis problems with the help of practical examples Learn essential strategies to aggregate time series data in financial datasets and IoT Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionOfficially endorsed by MongoDB, Inc., Practical MongoDB Aggregations helps you unlock the full potential of the MongoDB aggregation framework, including the latest features of MongoDB 7.0. This book provides practical, easy-to-digest principles and approaches for increasing your effectiveness in developing aggregation pipelines, supported by examples for building pipelines to solve complex data manipulation and analytical tasks. This book is customized for developers, architects, data analysts, data engineers, and data scientists with some familiarity with the aggregation framework. It begins by explaining the framework's architecture and then shows you how to build pipelines optimized for productivity and scale. Given the critical role arrays play in MongoDB's document model, the book delves into best practices for optimally manipulating arrays. The latter part of the book equips you with examples to solve common data processing challenges so you can apply the lessons you've learned to practical situations. By the end of this MongoDB book, you’ll have learned how to utilize the MongoDB aggregation framework to streamline your data analysis and manipulation processes effectively.What you will learn Develop dynamic aggregation pipelines tailored to changing business requirements Master essential techniques to optimize aggregation pipelines for rapid data processing Achieve optimal efficiency for applying aggregations to vast datasets with effective sharding strategies Eliminate the performance penalties of processing data externally by filtering, grouping, and calculating aggregated values directly within the database Use pipelines to help you secure your data access and distribution Who this book is for This book is for intermediate-level developers, architects, analysts, engineers, and data scientists who are interested in learning about aggregation capabilities in MongoDB. Working knowledge of MongoDB is needed to get the most out of this book.

Gain MongoDB expertise and discover advanced queries and Atlas insights with this ultimate guide to version 7.0 Key Features Enhance your proficiency in advanced queries, aggregation, and optimized indexing to achieve peak MongoDB performance Monitor, back up, and integrate applications effortlessly with MongoDB Atlas Implement security thorough RBAC, auditing, and encryption to ensure comprehensive data protection and privacy Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionMastering MongoDB 7.0 explores the latest version of MongoDB, an exceptional NoSQL database solution that aligns with the needs of modern web applications. This book starts with an informative overview of MongoDB’s architecture and developer tools, guiding you through the process of connecting to databases seamlessly. This MongoDB book explores advanced queries in detail, including aggregation pipelines and multi-document ACID transactions. It delves into the capabilities of the MongoDB Atlas developer data platform and the latest features, such as Atlas Vector Search, and their role in AI applications, enabling developers to build applications with the scalability and performance that today’s organizations need. It also covers the creation of resilient search functionality using MongoDB Atlas Search. Mastering MongoDB 7.0’s deep coverage of advanced techniques encompasses everything from role-based access control (RBAC) to user management, auditing practices, and encryption across data, network, and storage layers. By the end of this book, you’ll have developed the skills necessary to create efficient, secure, and high-performing applications using MongoDB. You’ll have the confidence to undertake complex queries, integrate robust applications, and ensure data security to overcome modern data challenges.What you will learn Execute advanced MongoDB queries for intricate data insights Harness the power of aggregation pipelines to transform data Ensure data integrity with multi-document ACID transactions Optimize query performance using strategic indexing techniques Navigate MongoDB Atlas seamlessly for monitoring and backups Enable robust search functionality with Atlas Search Master RBAC, user management, and data encryption for security Implement auditing practices for transparency and accountability Who this book is for This book is for developers with an intermediate skill level who aim to become MongoDB experts. Working knowledge of MongoDB is recommended to gain the most from this guide. Ideal for database administrators, app developers, and software engineers, this book will assist you in developing advanced skills to conquer intricate data tasks.

Get command of your organizational Big Data using the power of data science and analytics Key Features A perfect companion to boost your Big Data storing, processing, analyzing skills to help you take informed business decisions Work with the best tools such as Apache Hadoop, R, Python, and Spark for NoSQL platforms to perform massive online analyses Get expert tips on statistical inference, machine learning, mathematical modeling, and data visualization for Big Data Book Description Big Data analytics relates to the strategies used by organizations to collect, organize and analyze large amounts of data to uncover valuable business insights that otherwise cannot be analyzed through traditional systems. Crafting an enterprise-scale cost-efficient Big Data and machine learning solution to uncover insights and value from your organization's data is a challenge. Today, with hundreds of new Big Data systems, machine learning packages and BI Tools, selecting the right combination of technologies is an even greater challenge. This book will help you do that. With the help of this guide, you will be able to bridge the gap between the theoretical world of technology with the practical ground reality of building corporate Big Data and data science platforms. You will get hands-on exposure to Hadoop and Spark, build machine learning dashboards using R and R Shiny, create web-based apps using NoSQL databases such as MongoDB and even learn how to write R code for neural networks. By the end of the book, you will have a very clear and concrete understanding of what Big Data analytics means, how it drives revenues for organizations, and how you can develop your own Big Data analytics solution using different tools and methods articulated in this book. What you will learn - Get a 360-degree view into the world of Big Data, data science and machine learning - Broad range of technical and business Big Data analytics topics that caters to the interests of the technical experts as well as corporate IT executives - Get hands-on experience with industry-standard Big Data and machine learning tools such as Hadoop, Spark, MongoDB, KDB+ and R - Create production-grade machine learning BI Dashboards using R and R Shiny with step-by-step instructions - Learn how to combine open-source Big Data, machine learning and BI Tools to create low-cost business analytics applications - Understand corporate strategies for successful Big Data and data science projects - Go beyond general-purpose analytics to develop cutting-edge Big Data applications using emerging technologies Who this book is for The book is intended for existing and aspiring Big Data professionals who wish to become the go-to person in their organization when it comes to Big Data architecture, analytics, and governance. While no prior knowledge of Big Data or related technologies is assumed, it will be helpful to have some programming experience.

Enhance your web development skills, from setting up your environment and advanced integrations to building robust, high-traffic web applications with practical, scalable solutions Key Features Explore FastAPI in depth, from basic setup to advanced features such as custom middleware and WebSockets Discover practical strategies to optimize app performance and handle high traffic Implement SQL and NoSQL integration techniques for versatile data management in FastAPI applications Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionFastAPI is a cutting-edge Python framework that is revolutionizing the way web apps and APIs are built. Known for its speed, simplicity, and scalability, FastAPI empowers developers to create high-performing applications with ease. This book will help you leverage FastAPI’s immense potential to handle high-traffic scenarios and integrate seamlessly with modern Python tools. The book begins by familiarizing you with the basics of setting up and configuring your FastAPI environment before moving to the intricacies of building RESTful APIs, managing data with SQL and NoSQL databases, and handling authentication and authorization. Next, you'll focus on advanced topics such as custom middleware, WebSocket communication, and integration with various Python libraries. Each chapter is meticulously crafted with practical recipes, progressing from foundational concepts to advanced features and best practices. The concluding chapters show you how to optimize performance, implement rate limiting, and execute background tasks, empowering you to become a proficient FastAPI developer. By the end of this book, you'll have gained the skills you need to migrate existing apps to FastAPI, and be equipped to tackle any challenge in the modern web development landscape, ensuring your apps are not only functional, but also efficient, secure, and scalable.What you will learn Explore advanced FastAPI functionalities such as dependency injection, custom middleware, and WebSockets Discover various types of data storage for powerful app functionality with SQL and NoSQL Implement testing and debugging practices for clean, robust code Integrate authentication and authorization mechanisms to secure web apps Acquire skills to seamlessly migrate existing applications to FastAPI Write unit and integration tests, ensuring reliability and security for your apps Deploy your FastAPI apps to production environments for real-world use Who this book is for This book is for Python developers looking to enhance their skills to build scalable, high-performance web apps using FastAPI. Professionals seeking practical guidance to create APIs and web apps that can handle significant traffic and scale as needed will also find this book helpful by learning from both foundational insights and advanced techniques. The book is also designed for anyone familiar with RESTful APIs, HTTP protocols, and database systems, as well as developers looking to migrate existing applications to FastAPI or explore its advanced features.

Boost your web developer potential and stay ahead in the fast-paced web development and AI race with the flexibility, adaptability, and robustness of the FARM stack Key Features Learn the basics of MongoDB to be able to model any type of data Explore the powerful Python web development ecosystem with Pydantic and FastAPI Future-proof your applications by integrating ChatGPT or other LLMs Purchase of the print or Kindle book includes a free PDF eBook Book Description Discover how to harness the power of the FARM stack—FastAPI, React, and MongoDB—to develop production-ready web applications of varying complexity. Written by a team of industry experts, including MongoDB champions and product leaders, this fast-paced, hands-on guide equips beginners with essential skills to build web applications efficiently. Introducing each element of the stack, the book demonstrates how to seamlessly integrate them to create a medium-sized web application. You'll set up MongoDB as a document store, construct a simple API with FastAPI, and build an application using React. The guide also covers enhancing application security through authentication and authorization with JSON Web Tokens. Beyond mastering the stack, you'll get to grips with integrating Large Language Models (like ChatGPT) for advanced functionality, such as automated email sending. Additionally, you'll learn how to make the most of Next.js 14, a robust full-stack framework offering improved developer experience. By the end of the book, you'll have created functional applications and gained the foundation to explore diverse and more specialized domains, expanding your development horizons. What you will learn Set up and manage MongoDB databases and collections, and model data Leverage the power of FastAPI to write complex APIs using pure Python Create frontends of varying complexity with the React library Build and deploy robust and secure backends using FastAPI and MongoDB Ship production-ready applications with Next.js 14, applying your React and backend knowledge Integrate Large Language Models, send emails, and do much more with the flexible FARM stack Who this book is for The book is for intermediate web developers with basic JavaScript and Python knowledge who want to enhance their developer skills, master a powerful and flexible stack, and write better applications faster.

A practical guide to obtaining, transforming, exploring, and analyzing data using Python, MongoDB, and Apache Spark About This Book Learn to use various data analysis tools and algorithms to classify, cluster, visualize, simulate, and forecast your data Apply Machine Learning algorithms to different kinds of data such as social networks, time series, and images A hands-on guide to understanding the nature of data and how to turn it into insight Who This Book Is For This book is for developers who want to implement data analysis and data-driven algorithms in a practical way. It is also suitable for those without a background in data analysis or data processing. Basic knowledge of Python programming, statistics, and linear algebra is assumed. What You Will Learn Acquire, format, and visualize your data Build an image-similarity search engine Generate meaningful visualizations anyone can understand Get started with analyzing social network graphs Find out how to implement sentiment text analysis Install data analysis tools such as Pandas, MongoDB, and Apache Spark Get to grips with Apache Spark Implement machine learning algorithms such as classification or forecasting In Detail Beyond buzzwords like Big Data or Data Science, there are a great opportunities to innovate in many businesses using data analysis to get data-driven products. Data analysis involves asking many questions about data in order to discover insights and generate value for a product or a service. This book explains the basic data algorithms without the theoretical jargon, and you'll get hands-on turning data into insights using machine learning techniques. We will perform data-driven innovation processing for several types of data such as text, Images, social network graphs, documents, and time series, showing you how to implement large data processing with MongoDB and Apache Spark. Style and approach This is a hands-on guide to data analysis and data processing. The concrete examples are explained with simple code and accessible data.

The "one-size-fits-all" thinking regarding traditional RDBMSs has been challenged in the last few years by the emergence of diversified NoSQL databases. More than 120 NoSQL databases are now available in the market, and the market leader by far is MongoDB. With so many companies opting for MongoDB as their NoSQL database of choice, there's a need for a practical how-to combined with expert advice for getting the most out of the software. Beginning with a short introduction to the basics of NoSQL databases, MongoDB experts Navin Sabharwal and Shankatala Gupta Edward introduce readers to MongoDB – the leading document based NoSQL database, acquainting them step by step with all aspects of MongoDB. They cover the data model, underlying architecture, how to code using Mongo Shell, and administration of the MongoDB platform, among other topics. The book also provides clear guidelines and practical examples for architecting and developing applications using the MongoDB platform and deploying them. Database developers, architects, and database administrators will find useful information covering all aspects of the MongoDB platform and how to put it to use practically. Practical Guide to MongoDB provides readers with: A solid understanding of NoSQL databases An understanding of how to get started with MongoDB Methodical coverage of the architecture, development, and administration of MongoDB A plethora of "How to’s" enabling you to use the technology most efficiently to solve the problems you face Practical MongoDB is for those just starting to learning to work with NoSQL databases in general and MongoDB in particular. Skills in these areas are in demand, making this book essential reading for those who want to work more productively or break into big data work. It will prove equally useful for entrepreneurs and others who like to work with new technologies.