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Just Enough R
Just Enough R

If your job involves working with data in any manner, you cannot afford to ignore the R revolution! If your domain is called data analysis, analytics, informatics, data science, reporting, business intelligence, data management, big data, or visualization, you just have to learn R as this programming language is a game-changing sledgehammer. However, if you have looked at a standard text on R or read some of the online discussions, you might feel that there is a steep learning curve of six months or more to grok the language. I will debunk this myth through my book by focusing on practical essentials instead of theory. If you have programmed in some language in the past (whether that language be SAS, SPSS, C, C++, C#, Java, Python, Perl, Visual Basic, Ruby, Scala, shell scripts, or plain old SQL), even if you are rusty, this book will get you up and running with R in a single day, writing programs for data analysis and visualization. ...
Practical SQL, 2nd Edition
Practical SQL, 2nd Edition

Practical SQL is an approachable and fast-paced guide to SQL (Structured Query Language), the standard programming language for defining, organizing, and exploring data in relational databases. Anthony DeBarros, a journalist and data analyst, focuses on using SQL to find the story within your data. The examples and code use the open-source database PostgreSQL and its companion pgAdmin interface, and the concepts you learn will apply to most database management systems, including MySQL, Oracle, SQLite, and others. You'll first cover the fundamentals of databases and the SQL language, then build skills by analyzing data from real-world datasets such as US Census demographics, New York City taxi rides, and earthquakes from US Geological Survey. Each chapter includes exercises and examples that teach even those who have never programmed before all the tools necessary to build powerful databases and access information quickly and efficiently. You'll learn how to: Create databases and ...
Generic Data Structures and Algorithms in Go
Generic Data Structures and Algorithms in Go

Advance your understanding of generic data structures and algorithms and their applications using Go and the effective use of concurrency. You are invited on a journey that aims to improve your programming and problem-solving skills. This book takes you to the next step by showing how to get your programs to work efficiently as well as correctly. As you explore many data structures and the algorithms and applications associated with them, you'll focus on the trade-offs between speed and storage and the benefits of deploying concurrency when appropriate. This book will demonstrate the huge increases in application performance that are possible. The presentation of classic data structures and techniques of algorithm design (greedy, divide and conquer, branch-and-bound to name a few) provides an essential foundation and toolkit for problem solving. But this book goes further by presenting heuristic algorithms and their implementations for solving computationally intractable combinator ...
Beginning Spring Data
Beginning Spring Data

Use the popular Spring Data project for data access and persistence using various Java-based APIs such as JDBC, JPA, MongoDB, and more. This book shows how to easily incorporate data persistence and accessibility into your microservices, cloud-native applications, and monolithic enterprise applications. It also teaches you how to perform unit and performance testing of a component that accesses a database. And it walks you through an example of each type of SQL and NoSQL database covered. After reading this book, you'll be able to create an application that interacts with one or multiple types of databases, and conduct unit and performance testing to analyze possible problems. ...
Data Management at Scale, 2nd Edition
Data Management at Scale, 2nd Edition

As data management continues to evolve rapidly, managing all of your data in a central place, such as a data warehouse, is no longer scalable. Today's world is about quickly turning data into value. This requires a paradigm shift in the way we federate responsibilities, manage data, and make it available to others. With this practical book, you'll learn how to design a next-gen data architecture that takes into account the scale you need for your organization. Executives, architects and engineers, analytics teams, and compliance and governance staff will learn how to build a next-gen data landscape. Author Piethein Strengholt provides blueprints, principles, observations, best practices, and patterns to get you up to speed. Examine data management trends, including regulatory requirements, privacy concerns, and new developments such as data mesh and data fabric; Go deep into building a modern data architecture, including cloud data landing zones, domain-driven design, data produc ...
Programming Hive
Programming Hive

Need to move a relational database application to Hadoop? This comprehensive guide introduces you to Apache Hive, Hadoop's data warehouse infrastructure. You'll quickly learn how to use Hive's SQL dialect - HiveQL - to summarize, query, and analyze large datasets stored in Hadoop's distributed filesystem. This example-driven guide shows you how to set up and configure Hive in your environment, provides a detailed overview of Hadoop and MapReduce, and demonstrates how Hive works within the Hadoop ecosystem. You'll also find real-world case studies that describe how companies have used Hive to solve unique problems involving petabytes of data. Use Hive to create, alter, and drop databases, tables, views, functions, and indexes;Customize data formats and storage options, from files to external databases;Load and extract data from tables - and use queries, grouping, filtering, joining, and other conventional query methods;Gain best practices for creating ...
Data Structures and Algorithms in Python
Data Structures and Algorithms in Python

Based on the authors' market leading data structures books in Java and C++, this textbook offers a comprehensive, definitive introduction to data structures in Python by respected authors. Data Structures and Algorithms in Python is the first mainstream object-oriented book available for the Python data structures course. Designed to provide a comprehensive introduction to data structures and algorithms, including their design, analysis, and implementation, the text will maintain the same general structure as Data Structures and Algorithms in Java and Data Structures and Algorithms in C++. ...
Analyzing the Analyzers
Analyzing the Analyzers

There has been intense excitement in recent years around activities labeled "data science," "big data," and "analytics." However, the lack of clarity around these terms and, particularly, around the skill sets and capabilities of their practitioners has led to inefficient communication between "data scientists" and the organizations requiring their services. This lack of clarity has frequently led to missed opportunities. To address this issue, we surveyed several hundred practitioners via the Web to explore the varieties of skills, experiences, and viewpoints in the emerging data science community. ...
Data Structures and Algorithms with JavaScript
Data Structures and Algorithms with JavaScript

As an experienced JavaScript developer moving to server-side programming, you need to implement classic data structures and algorithms associated with conventional object-oriented languages like C# and Java. This practical guide shows you how to work hands-on with a variety of storage mechanisms—including linked lists, stacks, queues, and graphs—within the constraints of the JavaScript environment. Determine which data structures and algorithms are most appropriate for the problems you're trying to solve, and understand the tradeoffs when using them in a JavaScript program. ...
Storm Blueprints: Patterns for Distributed Real-time Computation
Storm Blueprints: Patterns for Distributed Real-time Computation

Storm is the most popular framework for real-time stream processing. Storm provides the fundamental primitives and guarantees required for fault-tolerant distributed computing in high-volume, mission critical applications. It is both an integration technology as well as a data flow and control mechanism, making it the core of many big data platforms. Storm is essential if you want to deploy, operate, and develop data processing flows capable of processing billions of transactions. Storm: Distributed Real-time Computation Blueprints - covers a broad range of distributed computing topics, including not only design and integration patterns, but also domains and applications to which the technology is immediately useful and commonly applied. This book introduces you to Storm using real-world examples, beginning with simple Storm topologies. ...
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