Download or read book Getting Started with DuckDB written by Simon Aubury and published by Packt Publishing Ltd. This book was released on 2024-06-24 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: Analyze and transform data efficiently with DuckDB, a versatile, modern, in-process SQL database Key Features Use DuckDB to rapidly load, transform, and query data across a range of sources and formats Gain practical experience using SQL, Python, and R to effectively analyze data Learn how open source tools and cloud services in the broader data ecosystem complement DuckDB’s versatile capabilities Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionDuckDB is a fast in-process analytical database. Its ease of use, versatile feature set, and powerful analytical capabilities make DuckDB a valuable addition to the data practitioner’s toolkit. Getting Started with DuckDB offers a practical overview of DuckDB’s fundamentals and guidance for effectively using its powerful capabilities. Through extensive hands-on examples, you’ll learn how to use DuckDB to load, transform, and query a variety of data sources and formats, including CSV, JSON, and Parquet files, semi-structured data, remotely-hosted files, and external databases. You'll also find out how to leverage DuckDB's performance optimizations and friendly SQL enhancements. You'll explore how to use DuckDB’s extensions for specialized applications, such as geospatial analysis and text search over document collections. In addition to working through examples in SQL, Python, and R, you’ll also dive into using DuckDB for analyzing public datasets and discover the wider ecosystem of open-source tools and cloud services that supercharge DuckDB-powered workflows and applications. Whether you’re a seasoned data practitioner or new to working with analytical data, this book will rapidly get you up to speed with DuckDB’s versatile and powerful capabilities, enabling you to apply them in your analytical workflows and projects.What you will learn Understand the properties and applications of a columnar in-process database Use SQL to load, transform, and query a range of data formats Discover DuckDB's rich extensions and learn how to apply them Use nested data types to model semi-structured data and extract and model JSON data Integrate DuckDB into your Python and R analytical workflows Effectively leverage DuckDB's convenient SQL enhancements Explore the wider ecosystem and pathways for building DuckDB-powered data applications Who this book is for If you’re interested in expanding your analytical toolkit, this book is for you. It will be particularly valuable for data analysts wanting to rapidly explore and query complex data, data and software engineers looking for a lean and versatile data processing tool, along with data scientists needing a scalable data manipulation library that integrates seamlessly with Python and R. You will get the most from this book if you have some familiarity with SQL and foundational database concepts, as well as exposure to a programming language such as Python or R.

Download or read book DuckDB in Action written by Mark Needham and published by Simon and Schuster. This book was released on 2024-08-27 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dive into DuckDB and start processing gigabytes of data with ease—all with no data warehouse. You don’t need expensive hardware or to spin up a whole new cluster whenever you want to analyze a big data set. You just need DuckDB! This modern and fast embedded database runs on a laptop, and lets you easily process data from almost any source, including JSON, CSV, Parquet, SQLite and Postgres. In DuckDB in Action you’ll learn everything you need to know to get the most out of this awesome tool, keep your data secure on prem, and save you hundreds on your cloud bill. Open up DuckDB in Action and learn how to: Read and process data from CSV, JSON and Parquet sources both locally and remote Write analytical SQL queries, including aggregations, common table expressions, window functions, special types of joins, and pivot tables Use DuckDB from Python, both with SQL and its "Relational"-API, interacting with databases but also data frames Prepare, ingest and query large datasets Build cloud data pipelines Extend DuckDB with custom functionality DuckDB in Action introduces the DuckDB database and shows you how to use it to solve common data workflow problems. It’s full of quick wins—right from chapter one, you’ll be finding new ways that DuckDB can speed up your work as a data professional. Each new concept is paired with a hands-on project example, so you can easily see how DuckDB works in action. Purchase of the print book includes a free eBook in PDF and ePub formats from Manning Publications. About the book DuckDB in Action will show you how to quickly get your hands dirty with DuckDB. You won’t need to read through pages of documentation—you’ll learn as you work. Begin with DuckDB’s CLI embedded mode, then dive straight into modern SQL queries and utilizing DuckDB’s handy SQL extensions. From there, you’ll explore the different ways you can analyze data with DuckDB, including advanced aggregation and analysis, data without persistence, and DuckDB’s underlying architecture. Learn how to combine DuckDB with the Python ecosystem for even greater customization, and how to extend DuckDB with its own tools. You’ll take to DuckDB like a duck to water, rapidly solving almost any relational data task with zero friction. About the reader For data scientists, data engineers, and developers interested in analyzing structured data. You’ll need some knowledge of Python, CLI tools, and SQL to get the most out of this guide. About the author Mark Needham is a blogger, and video creator at @?LearnDataWithMark, where his series on DuckDB offers viewers hands-on insights into practical database applications. Michael Hunger works on the open source Neo4j graph database filling many roles, where leads the product innovation and developer product strategy. Michael Simons is a Java Champion, author, and Staff Software Engineer at Neo4j and has been working professionally as a developer for more than 20 years.

Download or read book In Memory Analytics with Apache Arrow written by Matthew Topol and published by Packt Publishing Ltd. This book was released on 2024-09-30 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt: Harness the power of Apache Arrow to optimize tabular data processing and develop robust, high-performance data systems with its standardized, language-independent columnar memory format Key Features Explore Apache Arrow's data types and integration with pandas, Polars, and Parquet Work with Arrow libraries such as Flight SQL, Acero compute engine, and Dataset APIs for tabular data Enhance and accelerate machine learning data pipelines using Apache Arrow and its subprojects Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionApache Arrow is an open source, columnar in-memory data format designed for efficient data processing and analytics. This book harnesses the author’s 15 years of experience to show you a standardized way to work with tabular data across various programming languages and environments, enabling high-performance data processing and exchange. This updated second edition gives you an overview of the Arrow format, highlighting its versatility and benefits through real-world use cases. It guides you through enhancing data science workflows, optimizing performance with Apache Parquet and Spark, and ensuring seamless data translation. You’ll explore data interchange and storage formats, and Arrow's relationships with Parquet, Protocol Buffers, FlatBuffers, JSON, and CSV. You’ll also discover Apache Arrow subprojects, including Flight, SQL, Database Connectivity, and nanoarrow. You’ll learn to streamline machine learning workflows, use Arrow Dataset APIs, and integrate with popular analytical data systems such as Snowflake, Dremio, and DuckDB. The latter chapters provide real-world examples and case studies of products powered by Apache Arrow, providing practical insights into its applications. By the end of this book, you’ll have all the building blocks to create efficient and powerful analytical services and utilities with Apache Arrow.What you will learn Use Apache Arrow libraries to access data files, both locally and in the cloud Understand the zero-copy elements of the Apache Arrow format Improve the read performance of data pipelines by memory-mapping Arrow files Produce and consume Apache Arrow data efficiently by sharing memory with the C API Leverage the Arrow compute engine, Acero, to perform complex operations Create Arrow Flight servers and clients for transferring data quickly Build the Arrow libraries locally and contribute to the community Who this book is for This book is for developers, data engineers, and data scientists looking to explore the capabilities of Apache Arrow from the ground up. Whether you’re building utilities for data analytics and query engines, or building full pipelines with tabular data, this book can help you out regardless of your preferred programming language. A basic understanding of data analysis concepts is needed, but not necessary. Code examples are provided using C++, Python, and Go throughout the book.

Download or read book Elastic Stack 8 x Cookbook written by Huage Chen and published by Packt Publishing Ltd. This book was released on 2024-06-28 with total page 688 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unlock the full potential of Elastic Stack for search, analytics, security, and observability and manage substantial data workloads in both on-premise and cloud environments Key Features Explore the diverse capabilities of the Elastic Stack through a comprehensive set of recipes Build search applications, analyze your data, and observe cloud-native applications Harness powerful machine learning and AI features to create data science and search applications Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionLearn how to make the most of the Elastic Stack (ELK Stack) products—including Elasticsearch, Kibana, Elastic Agent, and Logstash—to take data reliably and securely from any source, in any format, and then search, analyze, and visualize it in real-time. This cookbook takes a practical approach to unlocking the full potential of Elastic Stack through detailed recipes step by step. Starting with installing and ingesting data using Elastic Agent and Beats, this book guides you through data transformation and enrichment with various Elastic components and explores the latest advancements in search applications, including semantic search and Generative AI. You'll then visualize and explore your data and create dashboards using Kibana. As you progress, you'll advance your skills with machine learning for data science, get to grips with natural language processing, and discover the power of vector search. The book covers Elastic Observability use cases for log, infrastructure, and synthetics monitoring, along with essential strategies for securing the Elastic Stack. Finally, you'll gain expertise in Elastic Stack operations to effectively monitor and manage your system.What you will learn Discover techniques for collecting data from diverse sources Visualize data and create dashboards using Kibana to extract business insights Explore machine learning, vector search, and AI capabilities of Elastic Stack Handle data transformation and data formatting Build search solutions from the ingested data Leverage data science tools for in-depth data exploration Monitor and manage your system with Elastic Stack Who this book is for This book is for Elastic Stack users, developers, observability practitioners, and data professionals ranging from beginner to expert level. If you’re a developer, you’ll benefit from the easy-to-follow recipes for using APIs and features to build powerful applications, and if you’re an observability practitioner, this book will help you with use cases covering APM, Kubernetes, and cloud monitoring. For data engineers and AI enthusiasts, the book covers dedicated recipes on vector search and machine learning. No prior knowledge of the Elastic Stack is required.

Download or read book Polars Cookbook written by Yuki Kakegawa and published by Packt Publishing Ltd. This book was released on 2024-08-23 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage a lightning fast DataFrame library for efficient data wrangling in Python Key Features Unlock the power of Python Polars for faster and more efficient data analysis workflows Master the fundamentals of Python Polars with step-by-step recipes Discover data manipulation techniques to apply across multiple data problems Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionPolars Cookbook is a complete guide that not only helps you get started with Python Polars but also gives you effective solutions to your day-to-day data problems. Dive into the world of Polars, a high-performance DataFrame library designed for efficient data processing and analysis. This cookbook takes a practical approach to unlocking the full potential of Polars through detailed, step-by-step recipes. Starting with installation and basic operations, this book guides you through data manipulation, advanced querying, and performance optimization techniques. You’ll learn how to handle large datasets, perform complex transformations, and leverage Polars’ powerful features for data science tasks. As you progress, you’ll explore Polars’ integration with other tools and libraries, and discover how to deploy Polars in both onpremises and cloud environments. You’ll also explore use cases for data engineering, time series analysis, statistical analysis, and machine learning, providing essential strategies for securing and optimizing your Polars workflows. By the end of this book, you’ll have acquired the knowledge and skills to build scalable, efficient, and reliable data processing solutions using Polars.What you will learn Read from different data sources and write to various files and databases Apply aggregations, window functions, and string manipulations Perform common data tasks such as handling missing values and performing list and array operations Discover how to reshape and tidy your data by pivoting, joining, and concatenating Analyze your time series data in Python Polars Create better workflows with testing and debugging Who this book is for This book is for data analysts, data scientists, and data engineers who want to learn how to use Polars in their workflows. Working knowledge of the Python programming language is required. Experience working with a DataFrame library such as pandas or PySpark will also be helpful.

Download or read book Amazon DynamoDB The Definitive Guide written by Aman Dhingra and published by Packt Publishing Ltd. This book was released on 2024-08-30 with total page 415 pages. Available in PDF, EPUB and Kindle. Book excerpt: Harness the potential and scalability of DynamoDB to effortlessly construct resilient, low-latency databases Key Features Discover how DynamoDB works behind the scenes to make the most of its features Learn how to keep latency and costs minimal even when scaling up Integrate DynamoDB with other AWS services to create a full data analytics system Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThis book will help you master Amazon DynamoDB, the fully managed, serverless, NoSQL database service designed for high performance at any scale. Authored by Aman Dhingra, senior DynamoDB specialist solutions architect at AWS, and Mike Mackay, former senior NoSQL specialist solutions architect at AWS, this guide draws on their expertise to equip you with the knowledge and skills needed to harness DynamoDB's full potential. This book not only introduces you to DynamoDB's core features and real-world applications, but also provides in-depth guidance on transitioning from traditional relational databases to the NoSQL world. You'll learn essential data modeling techniques, such as vertical partitioning, and explore the nuances of DynamoDB's indexing capabilities, capacity modes, and consistency models. The chapters also help you gain a solid understanding of advanced topics such as enhanced analytical patterns, implementing caching with DynamoDB Accelerator (DAX), and integrating DynamoDB with other AWS services to optimize your data strategies. By the end of this book, you’ll be able to design, build, and deliver low-latency, high-throughput DynamoDB solutions, driving new levels of efficiency and performance for your applications.What you will learn Master key-value data modeling in DynamoDB for efficiency Transition from RDBMSs to NoSQL with optimized strategies Implement read consistency and ACID transactions effectively Explore vertical partitioning for specific data access patterns Optimize data retrieval using secondary indexes in DynamoDB Manage capacity modes, backup strategies, and core components Enhance DynamoDB with caching, analytics, and global tables Evaluate and design your DynamoDB migration strategy Who this book is for This book is for software architects designing scalable systems, developers optimizing performance with DynamoDB, and engineering managers guiding decision-making. Data engineers will learn to integrate DynamoDB into workflows, while product owners will explore its innovative capabilities. DBAs transitioning to NoSQL will find valuable insights on DynamoDB and RDBMS integration. Basic knowledge of software engineering, Python, and cloud computing is helpful. Hands-on AWS or DynamoDB experience is beneficial but not required.

Download or read book DevOps for Data Science written by Alex Gold and published by CRC Press. This book was released on 2024-06-19 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Scientists are experts at analyzing, modelling and visualizing data but, at one point or another, have all encountered difficulties in collaborating with or delivering their work to the people and systems that matter. Born out of the agile software movement, DevOps is a set of practices, principles and tools that help software engineers reliably deploy work to production. This book takes the lessons of DevOps and aplies them to creating and delivering production-grade data science projects in Python and R. This book’s first section explores how to build data science projects that deploy to production with no frills or fuss. Its second section covers the rudiments of administering a server, including Linux, application, and network administration before concluding with a demystification of the concerns of enterprise IT/Administration in its final section, making it possible for data scientists to communicate and collaborate with their organization’s security, networking, and administration teams. Key Features: • Start-to-finish labs take readers through creating projects that meet DevOps best practices and creating a server-based environment to work on and deploy them. • Provides an appendix of cheatsheets so that readers will never be without the reference they need to remember a Git, Docker, or Command Line command. • Distills what a data scientist needs to know about Docker, APIs, CI/CD, Linux, DNS, SSL, HTTP, Auth, and more. • Written specifically to address the concern of a data scientist who wants to take their Python or R work to production. There are countless books on creating data science work that is correct. This book, on the otherhand, aims to go beyond this, targeted at data scientists who want their work to be than merely accurate and deliver work that matters.

Download or read book Duckdb Up and Running written by Wei-Meng Lee and published by . This book was released on 2025-03-04 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Analytics Engineering with SQL and dbt written by Rui Pedro Machado and published by "O'Reilly Media, Inc.". This book was released on 2023-12-08 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the shift from data warehouses to data lakes, data now lands in repositories before it's been transformed, enabling engineers to model raw data into clean, well-defined datasets. dbt (data build tool) helps you take data further. This practical book shows data analysts, data engineers, BI developers, and data scientists how to create a true self-service transformation platform through the use of dynamic SQL. Authors Rui Machado from Monstarlab and Hélder Russa from Jumia show you how to quickly deliver new data products by focusing more on value delivery and less on architectural and engineering aspects. If you know your business well and have the technical skills to model raw data into clean, well-defined datasets, you'll learn how to design and deliver data models without any technical influence. With this book, you'll learn: What dbt is and how a dbt project is structured How dbt fits into the data engineering and analytics worlds How to collaborate on building data models The main tools and architectures for building useful, functional data models How to fit dbt into data warehousing and laking architecture How to build tests for data transformations

Download or read book Analyzing Baseball Data with R written by Jim Albert and published by CRC Press. This book was released on 2024-08-01 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: “Our community has continued to grow exponentially, thanks to those who inspire the next generation. And inspiring the next generation is what the authors of Analyzing Baseball Data with R are doing. They are setting the career path for still thousands more. We all need some sort of kickstart to take that first or second step. You may be a beginner R coder, but you need access to baseball data. How do you access this data, how do you manipulate it, how do you analyze it? This is what this book does for you. But it does more, by doing what sabermetrics does best: it asks baseball questions. Throughout the book, baseball questions are asked, some straightforward, and others more thought-provoking.” From the Foreword by Tom Tango Analyzing Baseball Data with R Third Edition introduces R to sabermetricians, baseball enthusiasts, and students interested in exploring the richness of baseball data. It equips you with the necessary skills and software tools to perform all the analysis steps, from importing the data to transforming them into an appropriate format to visualizing the data via graphs to performing a statistical analysis. The authors first present an overview of publicly available baseball datasets and a gentle introduction to the type of data structures and exploratory and data management capabilities of R. They also cover the ggplot2 graphics functions and employ a tidyverse-friendly workflow throughout. Much of the book illustrates the use of R through popular sabermetrics topics, including the Pythagorean formula, runs expectancy, catcher framing, career trajectories, simulation of games and seasons, patterns of streaky behavior of players, and launch angles and exit velocities. All the datasets and R code used in the text are available for download online. New to the third edition is the revised R code to make use of new functions made available through the tidyverse. The third edition introduces three chapters of new material, focusing on communicating results via presentations using the Quarto publishing system, web applications using the Shiny package, and working with large data files. An online version of this book is hosted at https://beanumber.github.io/abdwr3e/.

Download or read book SQL Server 2012 Data Design and Retrieval written by Mike Hotek and published by Createspace Independent Pub. This book was released on 2013-03-29 with total page 526 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book takes you on a tour from the basics through the advanced details delivering a reference which you can employ in solving the real-world problems faced every day by database professionals. Each topic is reinforced with detailed exercises taken from real customer implementations. All of the content is updated for SQL Server 2012 SP1 and includes the new features which were introduced. Each topic starts with the basics, giving beginners a good starting point, and then drills down to the advanced details which will interest even the most seasoned SQL Server professionals.

Download or read book SQL Queries for Mere Mortals written by John L. Viescas and published by Pearson Education. This book was released on 2014 with total page 792 pages. Available in PDF, EPUB and Kindle. Book excerpt: The #1 Easy, Common-Sense Guide to SQL Queries--Updated for Today's Databases, Standards, and Challenges SQL Queries for Mere Mortals ® has earned worldwide praise as the clearest, simplest tutorial on writing effective SQL queries. The authors have updated this hands-on classic to reflect new SQL standards and database applications and teach valuable new techniques. Step by step, John L. Viescas and Michael J. Hernandez guide you through creating reliable queries for virtually any modern SQL-based database. They demystify all aspects of SQL query writing, from simple data selection and filtering to joining multiple tables and modifying sets of data. Three brand-new chapters teach you how to solve a wide range of challenging SQL problems. You'll learn how to write queries that apply multiple complex conditions on one table, perform sophisticated logical evaluations, and think "outside the box" using unlinked tables. Coverage includes -- Getting started: understanding what relational databases are, and ensuring that your database structures are sound -- SQL basics: using SELECT statements, creating expressions, sorting information with ORDER BY, and filtering data using WHERE -- Summarizing and grouping data with GROUP BY and HAVING clauses -- Drawing data from multiple tables: using INNER JOIN, OUTER JOIN, and UNION operators, and working with subqueries -- Modifying data sets with UPDATE, INSERT, and DELETE statements Advanced queries: complex NOT and AND, conditions, if-then-else using CASE, unlinked tables, driver tables, and more Practice all you want with downloadable sample databases for today's versions of Microsoft Office Access, Microsoft SQL Server, and the open source MySQL database. Whether you're a DBA, developer, user, or student, there's no better way to master SQL. informit.com/aw forMereMortals.com

Download or read book R for Data Science written by Hadley Wickham and published by "O'Reilly Media, Inc.". This book was released on 2016-12-12 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results

Download or read book Streaming Databases written by Hubert Dulay and published by "O'Reilly Media, Inc.". This book was released on 2024-08-08 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: Real-time applications are becoming the norm today. But building a model that works properly requires real-time data from the source, in-flight stream processing, and low latency serving of its analytics. With this practical book, data engineers, data architects, and data analysts will learn how to use streaming databases to build real-time solutions. Authors Hubert Dulay and Ralph M. Debusmann take you through streaming database fundamentals, including how these databases reduce infrastructure for real-time solutions. You'll learn the difference between streaming databases, stream processing, and real-time online analytical processing (OLAP) databases. And you'll discover when to use push queries versus pull queries, and how to serve synchronous and asynchronous data emanating from streaming databases. This guide helps you: Explore stream processing and streaming databases Learn how to build a real-time solution with a streaming database Understand how to construct materialized views from any number of streams Learn how to serve synchronous and asynchronous data Get started building low-complexity streaming solutions with minimal setup

Download or read book R for Data Science written by Hadley Wickham and published by "O'Reilly Media, Inc.". This book was released on 2023-06-08 with total page 579 pages. Available in PDF, EPUB and Kindle. Book excerpt: Use R to turn data into insight, knowledge, and understanding. With this practical book, aspiring data scientists will learn how to do data science with R and RStudio, along with the tidyverse—a collection of R packages designed to work together to make data science fast, fluent, and fun. Even if you have no programming experience, this updated edition will have you doing data science quickly. You'll learn how to import, transform, and visualize your data and communicate the results. And you'll get a complete, big-picture understanding of the data science cycle and the basic tools you need to manage the details. Updated for the latest tidyverse features and best practices, new chapters show you how to get data from spreadsheets, databases, and websites. Exercises help you practice what you've learned along the way. You'll understand how to: Visualize: Create plots for data exploration and communication of results Transform: Discover variable types and the tools to work with them Import: Get data into R and in a form convenient for analysis Program: Learn R tools for solving data problems with greater clarity and ease Communicate: Integrate prose, code, and results with Quarto

Download or read book Learning SQL Queries for R Users written by Djoni Darmawikarta and published by Createspace Independent Publishing Platform. This book was released on 2016-01-20 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book title implies that SQL Queries for R Users is for R users who need to get the data they need from a database. Loading large raw data from a database into R workspace is often unnecessary or even prohibitive. The book teaches you how to write SQL queries to retrieve precisely only the data needed from an SQL database. But, this book covers topics on metadata, which is equally important if not more than the SQL queries. To write an SQL query you must first know where the data is, the name of the tables and columns, their relationships, and the characteristics of the data. The book shows you how to identify this information. In Oracle SQL Developer ...... Explore Metadata Visualize Data Model Inquire Data Dictionary Build and Test Query Incrementally Wrap and Secure Query as Database View Deploy Generic SELECT query in R program

Download or read book WCF Multi layer Services Development with Entity Framework Fourth Edition written by Mike Liu and published by Packt Publishing Ltd. This book was released on 2014-10-31 with total page 551 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you are a C#, VB.NET, or C++ developer and want to get started with WCF and Entity Framework, then this book is for you. Competence in Entity Framework will be needed to follow the examples in the book, but experience in creating WCF services using Entity Framework is not necessary. Developers and architects evaluating SOA implementation technologies for their company will find this book useful.