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| dataset for sql practice: Practical SQL, 2nd Edition Anthony DeBarros, 2022-01-25 Analyze data like a pro, even if you’re a beginner. 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 related tables using your own data Aggregate, sort, and filter data to find patterns Use functions for basic math and advanced statistical operations Identify errors in data and clean them up Analyze spatial data with a geographic information system (PostGIS) Create advanced queries and automate tasks This updated second edition has been thoroughly revised to reflect the latest in SQL features, including additional advanced query techniques for wrangling data. This edition also has two new chapters: an expanded set of instructions on for setting up your system plus a chapter on using PostgreSQL with the popular JSON data interchange format. Learning SQL doesn’t have to be dry and complicated. Practical SQL delivers clear examples with an easy-to-follow approach to teach you the tools you need to build and manage your own databases. * Microsoft SQL Server employs a variant of the language called T-SQL, which is not covered by Practical SQL. |
| dataset for sql practice: SQL Cookbook Anthony Molinaro, 2006 A guide to SQL covers such topics as retrieving records, metadata queries, working with strings, data arithmetic, date manipulation, reporting and warehousing, and hierarchical queries. |
| dataset for sql practice: Learning SQL Alan Beaulieu, 2009-04-11 Updated for the latest database management systems -- including MySQL 6.0, Oracle 11g, and Microsoft's SQL Server 2008 -- this introductory guide will get you up and running with SQL quickly. Whether you need to write database applications, perform administrative tasks, or generate reports, Learning SQL, Second Edition, will help you easily master all the SQL fundamentals. Each chapter presents a self-contained lesson on a key SQL concept or technique, with numerous illustrations and annotated examples. Exercises at the end of each chapter let you practice the skills you learn. With this book, you will: Move quickly through SQL basics and learn several advanced features Use SQL data statements to generate, manipulate, and retrieve data Create database objects, such as tables, indexes, and constraints, using SQL schema statements Learn how data sets interact with queries, and understand the importance of subqueries Convert and manipulate data with SQL's built-in functions, and use conditional logic in data statements Knowledge of SQL is a must for interacting with data. With Learning SQL, you'll quickly learn how to put the power and flexibility of this language to work. |
| dataset for sql practice: Sams Teach Yourself SQL in 24 Hours Ryan Stephens, Ron Plew, Arie D. Jones, 2008-05-30 In just 24 lessons of one hour or less, you will learn professional techniques to design and build efficient databases and query them to extract useful information. Using a straightforward, step-by-step approach, each lesson builds on the previous one, allowing you to learn the essentials of ANSI SQL from the ground up. Example code demonstrates the authors’ professional techniques, while exercises written for MySQL offer the reader hands-on learning with an open-source database. Included are advanced techniques for using views, managing transactions, database administration, and extending SQL. Step-by-step instructions carefully walk you through the most common SQL tasks. Q&As, Quizzes, and Exercises at the end of each chapter help you test your knowledge. Notes and Tips point out shortcuts and solutions. New terms are clearly defined and explained. Learn how to... Use SQL-2003, the latest standard for the Structured Query Language Design and deploy efficient, secure databases Build advanced queries for information retrieval Sort, group, and summarize information for best presentation Tune databases and queries for maximum performance Understand database administration and security techniques For more than ten years the authors have studied, applied, and documented the SQL standard and its application to critical database systems. Ryan Stephens and Ron Plew are entrepreneurs, speakers, and cofounders of Perpetual Technologies, Inc. (PTI), a fast-growing IT management and consulting firm which specializes in database technologies. They taught database courses for Indiana University–Purdue University in Indianapolis for five years and have authored more than a dozen books on Oracle, SQL, database design, and the high availability of critical systems. Arie D. Jones is Senior SQL Server database administrator and analyst for PTI. He is a regular speaker at technical events and has authored several books and articles. Category: Database Covers: ANSI SQL User Level: Beginning–Intermediate Register your book at informit.com/title/9780672330186 for convenient access to updates and corrections as they become available. |
| dataset for sql practice: SQL for Data Scientists Renee M. P. Teate, 2021-08-17 Jump-start your career as a data scientist—learn to develop datasets for exploration, analysis, and machine learning SQL for Data Scientists: A Beginner's Guide for Building Datasets for Analysis is a resource that’s dedicated to the Structured Query Language (SQL) and dataset design skills that data scientists use most. Aspiring data scientists will learn how to how to construct datasets for exploration, analysis, and machine learning. You can also discover how to approach query design and develop SQL code to extract data insights while avoiding common pitfalls. You may be one of many people who are entering the field of Data Science from a range of professions and educational backgrounds, such as business analytics, social science, physics, economics, and computer science. Like many of them, you may have conducted analyses using spreadsheets as data sources, but never retrieved and engineered datasets from a relational database using SQL, which is a programming language designed for managing databases and extracting data. This guide for data scientists differs from other instructional guides on the subject. It doesn’t cover SQL broadly. Instead, you’ll learn the subset of SQL skills that data analysts and data scientists use frequently. You’ll also gain practical advice and direction on how to think about constructing your dataset. Gain an understanding of relational database structure, query design, and SQL syntax Develop queries to construct datasets for use in applications like interactive reports and machine learning algorithms Review strategies and approaches so you can design analytical datasets Practice your techniques with the provided database and SQL code In this book, author Renee Teate shares knowledge gained during a 15-year career working with data, in roles ranging from database developer to data analyst to data scientist. She guides you through SQL code and dataset design concepts from an industry practitioner’s perspective, moving your data scientist career forward! |
| dataset for sql practice: SQL Practice Problems Sylvia Moestl Vasilik, 2016-11-09 Real-world practice problems to bring your SQL skills to the next level It's easy to find basic SQL syntax and keyword information online. What's hard to find is challenging, well-designed, real-world problems--the type of problems that come up all the time when you're dealing with data. Learning how to solve these problems will give you the skill and confidence to step up in your career. With SQL Practice Problems, you can get that level of experience by solving sets of targeted problems. These aren't just problems designed to give an example of specific syntax, or keyword. These are the common problems you run into all the time when you deal with data. You will get real world practice, with real world data. I'll teach you how to think in SQL, how to analyze data problems, figure out the fundamentals, and work towards a solution that you can be proud of. It contains challenging problems, that hone your ability to write high quality SQL code. What do you get when you buy SQL Practice Problems? You get instructions on how set up MS SQL Server Express Edition 2016 and SQL Server Management Studio 2016, both free downloads. Almost all the SQL presented here works for previous versions of MS SQLServer, and any exceptions are highlighted. You'll also get a customized sample database, with video walk-through instructions on how to set it up on your computer. And of course, you get the actual practice problems - 57 problems that you work through step-by-step. There are targeted hints if you need them that help guide you through the question. For the more complex questions there are multiple levels of hints. Each answer comes with a short, targeted discussion section with alternative answers and tips on usage and good programming practice. What kind of problems are there in SQL Practice Problems? SQL Practice Problems has data analysis and reporting oriented challenges that are designed to step you through introductory, intermediate and advanced SQL Select statements, with a learn-by-doing technique. Most textbooks and courses have some practice problems. But most often, they're used just to illustrate a particular piece of syntax, with no filtering on what's most useful. What you'll get with SQL Practice Problems is the problems that illustrate some the most common challenges you'll run into with data, and the best, most useful techniques to solve them. These practice problems involve only Select statements, used for data analysis and reporting, and not statements to modify data (insert, delete, update), or to create stored procedures. About the author: Hi, my name is Sylvia Moestl Vasilik. I've been a database programmer and engineer for more than 15 years, working at top organizations like Expedia, Microsoft, T-Mobile, and the Gates Foundation. In 2015, I was teaching a SQL Server Certificate course at the University of Washington Continuing Education. It was a 10 week course, and my students paid more than $1000 for it. My students learned the basics of SQL, most of the keywords, and worked through practice problems every week of the course. But because of the emphasis on getting a broad overview of all features of SQL, we didn't spend enough time on the types of SQL that's used 95% of the time--intermediate and advanced Select statements. After the course was over, some of my students emailed me to ask where they could get more practice. That's when I was inspired to start work on this book. |
| dataset for sql practice: SQL Queries for Mere Mortals John L. Viescas, Michael James Hernandez, 2014 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 |
| dataset for sql practice: SQL For Dummies Allen G. Taylor, 2018-12-11 Get ready to make SQL easy! Updated for the latest version of SQL, the new edition of this perennial bestseller shows programmers and web developers how to use SQL to build relational databases and get valuable information from them. Covering everything you need to know to make working with SQL easier than ever, topics include how to use SQL to structure a DBMS and implement a database design; secure a database; and retrieve information from a database; and much more. SQL is the international standard database language used to create, access, manipulate, maintain, and store information in relational database management systems (DBMS) such as Access, Oracle, SQL Server, and MySQL. SQL adds powerful data manipulation and retrieval capabilities to conventional languages—and this book shows you how to harness the core element of relational databases with ease. Server platform that gives you choices of development languages, data types, on-premises or cloud, and operating systems Find great examples on the use of temporal data Jump right in—without previous knowledge of database programming or SQL As database-driven websites continue to grow in popularity—and complexity—SQL For Dummies is the easy-to-understand, go-to resource you need to use it seamlessly. |
| dataset for sql practice: Data Modeling Essentials Graeme Simsion, Graham Witt, 2004-12-03 Data Modeling Essentials, Third Edition, covers the basics of data modeling while focusing on developing a facility in techniques, rather than a simple familiarization with the rules. In order to enable students to apply the basics of data modeling to real models, the book addresses the realities of developing systems in real-world situations by assessing the merits of a variety of possible solutions as well as using language and diagramming methods that represent industry practice. This revised edition has been given significantly expanded coverage and reorganized for greater reader comprehension even as it retains its distinctive hallmarks of readability and usefulness. Beginning with the basics, the book provides a thorough grounding in theory before guiding the reader through the various stages of applied data modeling and database design. Later chapters address advanced subjects, including business rules, data warehousing, enterprise-wide modeling and data management. It includes an entirely new section discussing the development of logical and physical modeling, along with new material describing a powerful technique for model verification. It also provides an excellent resource for additional lectures and exercises. This text is the ideal reference for data modelers, data architects, database designers, DBAs, and systems analysts, as well as undergraduate and graduate-level students looking for a real-world perspective. - Thorough coverage of the fundamentals and relevant theory - Recognition and support for the creative side of the process - Expanded coverage of applied data modeling includes new chapters on logical and physical database design - New material describing a powerful technique for model verification - Unique coverage of the practical and human aspects of modeling, such as working with business specialists, managing change, and resolving conflict |
| dataset for sql practice: SQL for Data Analysis Cathy Tanimura, 2021-09-09 With the explosion of data, computing power, and cloud data warehouses, SQL has become an even more indispensable tool for the savvy analyst or data scientist. This practical book reveals new and hidden ways to improve your SQL skills, solve problems, and make the most of SQL as part of your workflow. You'll learn how to use both common and exotic SQL functions such as joins, window functions, subqueries, and regular expressions in new, innovative ways--as well as how to combine SQL techniques to accomplish your goals faster, with understandable code. If you work with SQL databases, this is a must-have reference. Learn the key steps for preparing your data for analysis Perform time series analysis using SQL's date and time manipulations Use cohort analysis to investigate how groups change over time Use SQL's powerful functions and operators for text analysis Detect outliers in your data and replace them with alternate values Establish causality using experiment analysis, also known as A/B testing |
| dataset for sql practice: Data Analysis Using SQL and Excel Gordon S. Linoff, 2010-09-16 Useful business analysis requires you to effectively transform data into actionable information. This book helps you use SQL and Excel to extract business information from relational databases and use that data to define business dimensions, store transactions about customers, produce results, and more. Each chapter explains when and why to perform a particular type of business analysis in order to obtain useful results, how to design and perform the analysis using SQL and Excel, and what the results should look like. |
| dataset for sql practice: Practical Apache Spark Subhashini Chellappan, Dharanitharan Ganesan, 2018-12-12 Work with Apache Spark using Scala to deploy and set up single-node, multi-node, and high-availability clusters. This book discusses various components of Spark such as Spark Core, DataFrames, Datasets and SQL, Spark Streaming, Spark MLib, and R on Spark with the help of practical code snippets for each topic. Practical Apache Spark also covers the integration of Apache Spark with Kafka with examples. You’ll follow a learn-to-do-by-yourself approach to learning – learn the concepts, practice the code snippets in Scala, and complete the assignments given to get an overall exposure. On completion, you’ll have knowledge of the functional programming aspects of Scala, and hands-on expertise in various Spark components. You’ll also become familiar with machine learning algorithms with real-time usage. What You Will LearnDiscover the functional programming features of Scala Understand the complete architecture of Spark and its componentsIntegrate Apache Spark with Hive and Kafka Use Spark SQL, DataFrames, and Datasets to process data using traditional SQL queries Work with different machine learning concepts and libraries using Spark's MLlib packages Who This Book Is For Developers and professionals who deal with batch and stream data processing. |
| dataset for sql practice: Head First SQL Lynn Beighley, 2007-08-28 With its visually rich format designed for the way the brain works, this series of engaging narrative lessons that build on each other gives readers hands-on experience working with the SQL database language. |
| dataset for sql practice: SQL For Dummies Allen G. Taylor, 2013-08-07 Uncover the secrets of SQL and start building better relational databases today! This fun and friendly guide will help you demystify database management systems so you can create more powerful databases and access information with ease. Updated for the latest SQL functionality, SQL For Dummies, 8th Edition covers the core SQL language and shows you how to use SQL to structure a DBMS, implement a database design, secure your data, and retrieve information when you need it. Includes new enhancements of SQL:2011, including temporal data functionality which allows you to set valid times for transactions to occur and helps prevent database corruption Covers creating, accessing, manipulating, maintaining, and storing information in relational database management systems like Access, Oracle, SQL Server, and MySQL Provides tips for keeping your data safe from theft, accidental or malicious corruption, or loss due to equipment failures and advice on eliminating errors in your work Don't be daunted by database development anymore - get SQL For Dummies, 8th Edition, and you'll be on your way to SQL stardom. |
| dataset for sql practice: Learn SQL Database Programming Josephine Bush, 2020-05-29 Learn everything you need to know to build efficient SQL queries using this easy-to-follow beginner’s guide Key FeaturesExplore all SQL statements in depth using a variety of examplesGet to grips with database querying, data aggregate, manipulation, and much moreUnderstand how to explore and process data of varying complexity to tell a storyBook Description SQL is a powerful querying language that's used to store, manipulate, and retrieve data, and it is one of the most popular languages used by developers to query and analyze data efficiently. If you're looking for a comprehensive introduction to SQL, Learn SQL Database Programming will help you to get up to speed with using SQL to streamline your work in no time. Starting with an overview of relational database management systems, this book will show you how to set up and use MySQL Workbench and design a database using practical examples. You'll also discover how to query and manipulate data with SQL programming using MySQL Workbench. As you advance, you’ll create a database, query single and multiple tables, and modify data using SQL querying. This SQL book covers advanced SQL techniques, including aggregate functions, flow control statements, error handling, and subqueries, and helps you process your data to present your findings. Finally, you’ll implement best practices for writing SQL and designing indexes and tables. By the end of this SQL programming book, you’ll have gained the confidence to use SQL queries to retrieve and manipulate data. What you will learnInstall, configure, and use MySQL Workbench to restore a databaseExplore different data types such as string, numeric, and date and timeQuery a single table using the basic SQL SELECT statement and the FROM, WHERE, and ORDER BY clausesQuery multiple tables by understanding various types of table relationshipsModify data in tables using the INSERT, UPDATE, and DELETE statementsUse aggregate functions to group and summarize dataDetect bad data, duplicates, and irrelevant values while processing dataWho this book is for This book is for business analysts, SQL developers, database administrators, and students learning SQL. If you want to learn how to query and manipulate SQL data for database administration tasks or simply extract and organize relevant data for analysis, you’ll find this book useful. No prior SQL experience is required. |
| dataset for sql practice: Learning Spark Jules S. Damji, Brooke Wenig, Tathagata Das, Denny Lee, 2020-07-16 Data is bigger, arrives faster, and comes in a variety of formats—and it all needs to be processed at scale for analytics or machine learning. But how can you process such varied workloads efficiently? Enter Apache Spark. Updated to include Spark 3.0, this second edition shows data engineers and data scientists why structure and unification in Spark matters. Specifically, this book explains how to perform simple and complex data analytics and employ machine learning algorithms. Through step-by-step walk-throughs, code snippets, and notebooks, you’ll be able to: Learn Python, SQL, Scala, or Java high-level Structured APIs Understand Spark operations and SQL Engine Inspect, tune, and debug Spark operations with Spark configurations and Spark UI Connect to data sources: JSON, Parquet, CSV, Avro, ORC, Hive, S3, or Kafka Perform analytics on batch and streaming data using Structured Streaming Build reliable data pipelines with open source Delta Lake and Spark Develop machine learning pipelines with MLlib and productionize models using MLflow |
| dataset for sql practice: Mining of Massive Datasets Jure Leskovec, Jurij Leskovec, Anand Rajaraman, Jeffrey David Ullman, 2014-11-13 Now in its second edition, this book focuses on practical algorithms for mining data from even the largest datasets. |
| dataset for sql practice: Learning MySQL and MariaDB Russell J.T. Dyer, 2015-03-30 With an easy, step-by-step approach, this guide shows beginners how to install, use, and maintain the world's most popular open source database: MySQL. You'll learn through real-world examples and many practical tips, including information on how to improve database performance. Database systems such as MySQL help data handling for organizations large and small handle data, providing robust and efficient access in ways not offered by spreadsheets and other types of data stores. This book is also useful for web developers and programmers interested in adding MySQL to their skill sets. Topics include: Installation and basic administration ; Introduction to databases and SQL ; Functions, subqueries, and other query enhancements ; Improving database performance ; Accessing MySQL from popular languages-- |
| dataset for sql practice: SQL for Data Science Antonio Badia, 2020-11-09 This textbook explains SQL within the context of data science and introduces the different parts of SQL as they are needed for the tasks usually carried out during data analysis. Using the framework of the data life cycle, it focuses on the steps that are very often given the short shift in traditional textbooks, like data loading, cleaning and pre-processing. The book is organized as follows. Chapter 1 describes the data life cycle, i.e. the sequence of stages from data acquisition to archiving, that data goes through as it is prepared and then actually analyzed, together with the different activities that take place at each stage. Chapter 2 gets into databases proper, explaining how relational databases organize data. Non-traditional data, like XML and text, are also covered. Chapter 3 introduces SQL queries, but unlike traditional textbooks, queries and their parts are described around typical data analysis tasks like data exploration, cleaning and transformation. Chapter 4 introduces some basic techniques for data analysis and shows how SQL can be used for some simple analyses without too much complication. Chapter 5 introduces additional SQL constructs that are important in a variety of situations and thus completes the coverage of SQL queries. Lastly, chapter 6 briefly explains how to use SQL from within R and from within Python programs. It focuses on how these languages can interact with a database, and how what has been learned about SQL can be leveraged to make life easier when using R or Python. All chapters contain a lot of examples and exercises on the way, and readers are encouraged to install the two open-source database systems (MySQL and Postgres) that are used throughout the book in order to practice and work on the exercises, because simply reading the book is much less useful than actually using it. This book is for anyone interested in data science and/or databases. It just demands a bit of computer fluency, but no specific background on databases or data analysis. All concepts are introduced intuitively and with a minimum of specialized jargon. After going through this book, readers should be able to profitably learn more about data mining, machine learning, and database management from more advanced textbooks and courses. |
| dataset for sql practice: Web Database Applications with PHP and MySQL Hugh E. Williams, David Lane, David John Lane, 2002 Introduces techniques for building applications that integrate large databases with web interfaces. Using a three-tier architecture, the book focuses on the middle tier and the application logic that brings together the fundamentally different client and database tiers. The authors explain the principles behind searching, browsing, storing user data, validating user input, managing user transactions, and security. Annotation copyrighted by Book News, Inc., Portland, OR. |
| dataset for sql practice: Learning Spark SQL Aurobindo Sarkar, 2017-09-07 Design, implement, and deliver successful streaming applications, machine learning pipelines and graph applications using Spark SQL API About This Book Learn about the design and implementation of streaming applications, machine learning pipelines, deep learning, and large-scale graph processing applications using Spark SQL APIs and Scala. Learn data exploration, data munging, and how to process structured and semi-structured data using real-world datasets and gain hands-on exposure to the issues and challenges of working with noisy and dirty real-world data. Understand design considerations for scalability and performance in web-scale Spark application architectures. Who This Book Is For If you are a developer, engineer, or an architect and want to learn how to use Apache Spark in a web-scale project, then this is the book for you. It is assumed that you have prior knowledge of SQL querying. A basic programming knowledge with Scala, Java, R, or Python is all you need to get started with this book. What You Will Learn Familiarize yourself with Spark SQL programming, including working with DataFrame/Dataset API and SQL Perform a series of hands-on exercises with different types of data sources, including CSV, JSON, Avro, MySQL, and MongoDB Perform data quality checks, data visualization, and basic statistical analysis tasks Perform data munging tasks on publically available datasets Learn how to use Spark SQL and Apache Kafka to build streaming applications Learn key performance-tuning tips and tricks in Spark SQL applications Learn key architectural components and patterns in large-scale Spark SQL applications In Detail In the past year, Apache Spark has been increasingly adopted for the development of distributed applications. Spark SQL APIs provide an optimized interface that helps developers build such applications quickly and easily. However, designing web-scale production applications using Spark SQL APIs can be a complex task. Hence, understanding the design and implementation best practices before you start your project will help you avoid these problems. This book gives an insight into the engineering practices used to design and build real-world, Spark-based applications. The book's hands-on examples will give you the required confidence to work on any future projects you encounter in Spark SQL. It starts by familiarizing you with data exploration and data munging tasks using Spark SQL and Scala. Extensive code examples will help you understand the methods used to implement typical use-cases for various types of applications. You will get a walkthrough of the key concepts and terms that are common to streaming, machine learning, and graph applications. You will also learn key performance-tuning details including Cost Based Optimization (Spark 2.2) in Spark SQL applications. Finally, you will move on to learning how such systems are architected and deployed for a successful delivery of your project. Style and approach This book is a hands-on guide to designing, building, and deploying Spark SQL-centric production applications at scale. |
| dataset for sql practice: Practical Database Programming with Visual Basic.NET Ying Bai, 2012-05-09 Practical Database Programming with Visual Basic.NET The most up-to-date Visual Basic.NET programming textbook—covering both fundamentals and advanced-level programming techniques—complete with examples and solutions Visual Basic.NET (VB.NET) is an object-oriented computer programming language that can be viewed as an evolution of the classic Visual Basic (VB), which is implemented on the .NET Framework. Microsoft currently supplies two major implementations of Visual Basic: Microsoft Visual Studio (which is commercial software) and Microsoft Visual Studio Express (which is free of charge). Forgoing the large amounts of programming codes found in most database programming books, Practical Database Programming with Visual Basic.NET shows students and professionals both how to develop professional and practical database programs in a Visual Basic.NET environment by using Visual Studio.NET Data Tools and Wizards related to ADO.NET 4.0, and how to apply codes that are auto-generated by solely using Wizards. The fully updated Second Edition: Covers both fundamentals and advanced database programming techniques Introduces three popular database systems with practical examples including MS Access, SQL Server 2008, and Oracle Features more than fifty sample projects with detailed illustrations and explanations to help students understand key techniques and programming technologies Includes downloadable programming codes and exercise questions This book provides undergraduate and graduate students as well as database programmers and software engineers with the necessary tools to handle the database programming issues in the Visual Studio.NET environment. |
| dataset for sql practice: Learning SAS by Example Ron Cody, 2018-07-03 Learn to program SAS by example! Learning SAS by Example, A Programmer’s Guide, Second Edition, teaches SAS programming from very basic concepts to more advanced topics. Because most programmers prefer examples rather than reference-type syntax, this book uses short examples to explain each topic. The second edition has brought this classic book on SAS programming up to the latest SAS version, with new chapters that cover topics such as PROC SGPLOT and Perl regular expressions. This book belongs on the shelf (or e-book reader) of anyone who programs in SAS, from those with little programming experience who want to learn SAS to intermediate and even advanced SAS programmers who want to learn new techniques or identify new ways to accomplish existing tasks. In an instructive and conversational tone, author Ron Cody clearly explains each programming technique and then illustrates it with one or more real-life examples, followed by a detailed description of how the program works. The text is divided into four major sections: Getting Started, DATA Step Processing, Presenting and Summarizing Your Data, and Advanced Topics. Subjects addressed include Reading data from external sources Learning details of DATA step programming Subsetting and combining SAS data sets Understanding SAS functions and working with arrays Creating reports with PROC REPORT and PROC TABULATE Getting started with the SAS macro language Leveraging PROC SQL Generating high-quality graphics Using advanced features of user-defined formats and informats Restructuring SAS data sets Working with multiple observations per subject Getting started with Perl regular expressions You can test your knowledge and hone your skills by solving the problems at the end of each chapter. |
| dataset for sql practice: Advanced SQL:1999 Jim Melton, 2003 This guide documents SQL: 1999Us advanced features in the same practical, programmercentric way that the first volume documented the language's basic features. This is no mere representation of the standard, but rather authoritative guidance on making an application conform to it, both formally and effectively. |
| dataset for sql practice: Beginning Oracle SQL for Oracle Database 18c Ben Brumm, 2019-08-05 Start developing with Oracle SQL. This book is a one-stop introduction to everything you need to know about getting started developing an Oracle Database. You'll learn about foundational concepts, setting up a simple schema, adding data, reading data from the database, and making changes. No experience with databases is required to get started. Examples in the book are built around Oracle Live SQL, a freely available, online sandbox for practicing and experimenting with SQL statements, and Oracle Express Edition, a free version of Oracle Database that is available for download. A marquee feature of Beginning Oracle SQL for Oracle Database 18c is the small chapter size. Content is divided into easily digestible chunks that can be read and practiced in very short intervals of time, making this the ideal book for a busy professional to learn from. Even just a 15-20 minute block of free time can be put to good use. Author Ben Brumm begins by helping you understand what a database is, and getting you set up with a sandbox in which to practice the SQL that you are learning. From there, easily digestible chapters cover, point-by-point, the different aspects of writing queries to get data out of a database. You’ll also learn about creating tables and getting data into the database. Crucial topics such as working with nulls and writing analytic queries are given the attention they deserve, helping you to avoid pitfalls when writing queries for production use. What You'll LearnCreate, update, and delete tables in an Oracle database Add, update, delete data from those database tables Query and view data stored in your database Manipulate and transform data using in-built database functions and features Correctly choose when to use Oracle-specific syntax and features Who This Book Is For Those new to Oracle who are planning to develop software using Oracle as the back-end data store. The book is also for those who are getting started in software development and realize they need to learn some kind of database language. Those who are learning software development on the side of their normal job, or learning it as a college student, who are ready to learn what a database is and how to use it also will find this book useful. |
| dataset for sql practice: Storytelling with Data Cole Nussbaumer Knaflic, 2015-10-09 Don't simply show your data—tell a story with it! Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You'll discover the power of storytelling and the way to make data a pivotal point in your story. The lessons in this illuminative text are grounded in theory, but made accessible through numerous real-world examples—ready for immediate application to your next graph or presentation. Storytelling is not an inherent skill, especially when it comes to data visualization, and the tools at our disposal don't make it any easier. This book demonstrates how to go beyond conventional tools to reach the root of your data, and how to use your data to create an engaging, informative, compelling story. Specifically, you'll learn how to: Understand the importance of context and audience Determine the appropriate type of graph for your situation Recognize and eliminate the clutter clouding your information Direct your audience's attention to the most important parts of your data Think like a designer and utilize concepts of design in data visualization Leverage the power of storytelling to help your message resonate with your audience Together, the lessons in this book will help you turn your data into high impact visual stories that stick with your audience. Rid your world of ineffective graphs, one exploding 3D pie chart at a time. There is a story in your data—Storytelling with Data will give you the skills and power to tell it! |
| dataset for sql practice: Sams Teach Yourself SQL in 10 Minutes Ben Forta, 2004 With this updated text, readers can learn the fundamentals of SQL quickly through the use of numerous examples depicting all the major components of SQL. |
| dataset for sql practice: The Art of SQL Stephane Faroult, Peter Robson, 2006-03-10 For all the buzz about trendy IT techniques, data processing is still at the core of our systems, especially now that enterprises all over the world are confronted with exploding volumes of data. Database performance has become a major headache, and most IT departments believe that developers should provide simple SQL code to solve immediate problems and let DBAs tune any bad SQL later. In The Art of SQL, author and SQL expert Stephane Faroult argues that this safe approach only leads to disaster. His insightful book, named after Art of War by Sun Tzu, contends that writing quick inefficient code is sweeping the dirt under the rug. SQL code may run for 5 to 10 years, surviving several major releases of the database management system and on several generations of hardware. The code must be fast and sound from the start, and that requires a firm understanding of SQL and relational theory. The Art of SQL offers best practices that teach experienced SQL users to focus on strategy rather than specifics. Faroult's approach takes a page from Sun Tzu's classic treatise by viewing database design as a military campaign. You need knowledge, skills, and talent. Talent can't be taught, but every strategist from Sun Tzu to modern-day generals believed that it can be nurtured through the experience of others. They passed on their experience acquired in the field through basic principles that served as guiding stars amid the sound and fury of battle. This is what Faroult does with SQL. Like a successful battle plan, good architectural choices are based on contingencies. What if the volume of this or that table increases unexpectedly? What if, following a merger, the number of users doubles? What if you want to keep several years of data online? Faroult's way of looking at SQL performance may be unconventional and unique, but he's deadly serious about writing good SQL and using SQL well. The Art of SQL is not a cookbook, listing problems and giving recipes. The aim is to get you-and your manager-to raise good questions. |
| dataset for sql practice: M Is for (Data) Monkey Ken Puls, Miguel Escobar, 2015-06-01 Power Query is one component of the Power BI (Business Intelligence) product from Microsoft, and M is the name of the programming language created by it. As more business intelligence pros begin using Power Pivot, they find that they do not have the Excel skills to clean the data in Excel; Power Query solves this problem. This book shows how to use the Power Query tool to get difficult data sets into both Excel and Power Pivot, and is solely devoted to Power Query dashboarding and reporting. |
| dataset for sql practice: Python Data Science Handbook Jake VanderPlas, 2016-11-21 For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you’ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms |
| dataset for sql practice: SQL in 10 Minutes, Sams Teach Yourself Ben Forta, 2012-10-25 Sams Teach Yourself SQL in 10 Minutes, Fourth Edition New full-color code examples help you see how SQL statements are structured Whether you're an application developer, database administrator, web application designer, mobile app developer, or Microsoft Office users, a good working knowledge of SQL is an important part of interacting with databases. And Sams Teach Yourself SQL in 10 Minutes offers the straightforward, practical answers you need to help you do your job. Expert trainer and popular author Ben Forta teaches you just the parts of SQL you need to know–starting with simple data retrieval and quickly going on to more complex topics including the use of joins, subqueries, stored procedures, cursors, triggers, and table constraints. You'll learn methodically, systematically, and simply–in 22 short, quick lessons that will each take only 10 minutes or less to complete. With the Fourth Edition of this worldwide bestseller, the book has been thoroughly updated, expanded, and improved. Lessons now cover the latest versions of IBM DB2, Microsoft Access, Microsoft SQL Server, MySQL, Oracle, PostgreSQL, SQLite, MariaDB, and Apache Open Office Base. And new full-color SQL code listings help the beginner clearly see the elements and structure of the language. 10 minutes is all you need to learn how to... Use the major SQL statements Construct complex SQL statements using multiple clauses and operators Retrieve, sort, and format database contents Pinpoint the data you need using a variety of filtering techniques Use aggregate functions to summarize data Join two or more related tables Insert, update, and delete data Create and alter database tables Work with views, stored procedures, and more Table of Contents 1 Understanding SQL 2 Retrieving Data 3 Sorting Retrieved Data 4 Filtering Data 5 Advanced Data Filtering 6 Using Wildcard Filtering 7 Creating Calculated Fields 8 Using Data Manipulation Functions 9 Summarizing Data 10 Grouping Data 11 Working with Subqueries 12 Joining Tables 13 Creating Advanced Joins 14 Combining Queries 15 Inserting Data 16 Updating and Deleting Data 17 Creating and Manipulating Tables 18 Using Views 19 Working with Stored Procedures 20 Managing Transaction Processing 21 Using Cursors 22 Understanding Advanced SQL Features Appendix A: Sample Table Scripts Appendix B: Working in Popular Applications Appendix C : SQL Statement Syntax Appendix D: Using SQL Datatypes Appendix E: SQL Reserved Words |
| dataset for sql practice: Joe Celko's SQL for Smarties Joe Celko, 2000 An industry consultant shares his most useful tips and tricks for advanced SQL programming to help the working programmer gain performance and work around system deficiencies. |
| dataset for sql practice: Mastering Oracle PL/SQL Christopher Beck, Joel Kallman, Chaim Katz, David C. Knox, Connor McDonald, 2008-01-01 If you have mastered the fundamentals of the PL/SQL language and are now looking for an in-depth, practical guide to solving real problems with PL/SQL stored procedures, then this is the book for you. |
| dataset for sql practice: SQL in 10 Minutes a Day, Sams Teach Yourself Ben Forta, 2019-10-29 Just the parts of SQL you need to know from simple data retrieval to the use of SQL joins, subqueries, stored procedures, cursors, triggers, and table constraints Designed for anyone interacting with databases, this SQL book methodically, systematically, and simply teaches you in lessons that each take 10 minutes or less to complete. Lessons include SQL statements, including complex SQL statements using multiple clauses and operators Data management: retrieve, sort, and format database contents, including inserting, updating, and deleting Data analytics: Pinpoint the data you need using a variety of filtering techniques and aggregate functions to summarize data Tables: create, alter, and join database tables Views Stored procedures Expert trainer and popular author Ben Forta created this book for most of us who just need to learn SQL and do not need to understand database design and normalization to relational database theory and administrative concerns. Each lesson includes Full-color code examples to help you understand how SQL statements are structured Tips that point out shortcuts and solutions Cautions to help you avoid common pitfalls Notes that explain additional concepts, and provide additional information |
| dataset for sql practice: R for Data Science Hadley Wickham, Garrett Grolemund, 2016-12-12 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 |
| dataset for sql practice: Joe Celko's SQL Programming Style Joe Celko, 2005-05-19 Are you an SQL programmer that, like many, came to SQL after learning and writing procedural or object-oriented code? Or have switched jobs to where a different brand of SQL is being used, or maybe even been told to learn SQL yourself? If even one answer is yes, then you need this book. A Manual of Style for the SQL programmer, this book is a collection of heuristics and rules, tips, and tricks that will help you improve SQL programming style and proficiency, and for formatting and writing portable, readable, maintainable SQL code. Based on many years of experience consulting in SQL shops, and gathering questions and resolving his students' SQL style issues, Joe Celko can help you become an even better SQL programmer. - Help you write Standard SQL without an accent or a dialect that is used in another programming language or a specific flavor of SQL, code that can be maintained and used by other people. - Enable you to give your group a coding standard for internal use, to enable programmers to use a consistent style. - Give you the mental tools to approach a new problem with SQL as your tool, rather than another programming language — one that someone else might not know! |
| dataset for sql practice: Google BigQuery: The Definitive Guide Valliappa Lakshmanan, Jordan Tigani, 2019-10-23 Work with petabyte-scale datasets while building a collaborative, agile workplace in the process. This practical book is the canonical reference to Google BigQuery, the query engine that lets you conduct interactive analysis of large datasets. BigQuery enables enterprises to efficiently store, query, ingest, and learn from their data in a convenient framework. With this book, you’ll examine how to analyze data at scale to derive insights from large datasets efficiently. Valliappa Lakshmanan, tech lead for Google Cloud Platform, and Jordan Tigani, engineering director for the BigQuery team, provide best practices for modern data warehousing within an autoscaled, serverless public cloud. Whether you want to explore parts of BigQuery you’re not familiar with or prefer to focus on specific tasks, this reference is indispensable. |
| dataset for sql practice: Modern Data Science with R Benjamin S. Baumer, Daniel T. Kaplan, Nicholas J. Horton, 2021-03-31 From a review of the first edition: Modern Data Science with R... is rich with examples and is guided by a strong narrative voice. What’s more, it presents an organizing framework that makes a convincing argument that data science is a course distinct from applied statistics (The American Statistician). Modern Data Science with R is a comprehensive data science textbook for undergraduates that incorporates statistical and computational thinking to solve real-world data problems. Rather than focus exclusively on case studies or programming syntax, this book illustrates how statistical programming in the state-of-the-art R/RStudio computing environment can be leveraged to extract meaningful information from a variety of data in the service of addressing compelling questions. The second edition is updated to reflect the growing influence of the tidyverse set of packages. All code in the book has been revised and styled to be more readable and easier to understand. New functionality from packages like sf, purrr, tidymodels, and tidytext is now integrated into the text. All chapters have been revised, and several have been split, re-organized, or re-imagined to meet the shifting landscape of best practice. |
| dataset for sql practice: T-SQL Querying Itzik Ben-Gan, Adam Machanic, Dejan Sarka, Kevin Farlee, 2015-02-17 T-SQL insiders help you tackle your toughest queries and query-tuning problems Squeeze maximum performance and efficiency from every T-SQL query you write or tune. Four leading experts take an in-depth look at T-SQL’s internal architecture and offer advanced practical techniques for optimizing response time and resource usage. Emphasizing a correct understanding of the language and its foundations, the authors present unique solutions they have spent years developing and refining. All code and techniques are fully updated to reflect new T-SQL enhancements in Microsoft SQL Server 2014 and SQL Server 2012. Write faster, more efficient T-SQL code: Move from procedural programming to the language of sets and logic Master an efficient top-down tuning methodology Assess algorithmic complexity to predict performance Compare data aggregation techniques, including new grouping sets Efficiently perform data-analysis calculations Make the most of T-SQL’s optimized bulk import tools Avoid date/time pitfalls that lead to buggy, poorly performing code Create optimized BI statistical queries without additional software Use programmable objects to accelerate queries Unlock major performance improvements with In-Memory OLTP Master useful and elegant approaches to manipulating graphs About This Book For experienced T-SQL practitioners Includes coverage updated from Inside Microsoft SQL Server 2008 T-SQL Querying and Inside Microsoft SQL Server 2008 T-SQL Programming Valuable to developers, DBAs, BI professionals, and data scientists Covers many MCSE 70-464 and MCSA/MCSE 70-461 exam topics |
| dataset for sql practice: Practical SQL, 2nd Edition Anthony DeBarros, 2022-01-25 Analyze data like a pro, even if you’re a beginner. 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 related tables using your own data Aggregate, sort, and filter data to find patterns Use functions for basic math and advanced statistical operations Identify errors in data and clean them up Analyze spatial data with a geographic information system (PostGIS) Create advanced queries and automate tasks This updated second edition has been thoroughly revised to reflect the latest in SQL features, including additional advanced query techniques for wrangling data. This edition also has two new chapters: an expanded set of instructions on for setting up your system plus a chapter on using PostgreSQL with the popular JSON data interchange format. Learning SQL doesn’t have to be dry and complicated. Practical SQL delivers clear examples with an easy-to-follow approach to teach you the tools you need to build and manage your own databases. * Microsoft SQL Server employs a variant of the language called T-SQL, which is not covered by Practical SQL. |
Dataset vs. data set - WordReference Forums
Oct 4, 2008 · For me, a dataset is a common name used to talk about data that come from the same origin (are in the same file, the …
在看一些论文中经常遇到，data set 与 dataset ，那请问这二者的区别在哪里?
dataset 和 data set 的含义有微妙的区别。data 和 set 本来是两个词，一般来说用 the data set(s) 是不会错的，也很正规，注意一定要加冠词，来指 …
Pytorch中的Dataset 和 DataLoader起什么作用？ - 知乎
第一，DataLoader则是把Dataset中的单个样本拼成一个个mini-batch，给神经网络使用。 第二，DataLoader是PyTorch中用于数据加载和批 …
The experiment was run the whole dataset
Feb 21, 2014 · I am unsure for noun 'dataset', when should we use perp. in and when use on or in and on both are exchangable, no …
This approach is not needed in or on this dataset
Jan 23, 2014 · The members of the dataset are in the dataset, but you use a method on something: on a value, on a set of ...
Dataset vs. data set - WordReference Forums
Oct 4, 2008 · For me, a dataset is a common name used to talk about data that come from the same origin (are in the same file, the same database, etc.) while a data set is a more general set of …
在看一些论文中经常遇到，data set 与 dataset ，那请问这二者的 …
dataset 和 data set 的含义有微妙的区别。data 和 set 本来是两个词，一般来说用 the data set(s) 是不会错的，也很正规，注意一定要加冠词，来指出特定的数据集，dataset 作为一个新词相对于 data …
Pytorch中的Dataset 和 DataLoader起什么作用？ - 知乎
第一，DataLoader则是把Dataset中的单个样本拼成一个个mini-batch，给神经网络使用。 第二，DataLoader是PyTorch中用于数据加载和批处理的实用工具，它能够以可定制的方式加载数据集 …
The experiment was run the whole dataset
Feb 21, 2014 · I am unsure for noun 'dataset', when should we use perp. in and when use on or in and on both are exchangable, no essential difference? For an example, we can say: 1. We run a …
This approach is not needed in or on this dataset
Jan 23, 2014 · The members of the dataset are in the dataset, but you use a method on something: on a value, on a set of ...
发SCI让加数据可用性声明怎么弄？ - 知乎
Dec 3, 2019 · 发SCI时需要添加数据可用性声明，求大神解答如何操作。
Flink实战(四) - DataSet API编程 - 知乎
1 你将学到 DataSet API开发概述 计数器 DataSource 分布式缓存 Transformation Sink 2 Data Set API 简介Flink中的DataSet程序是实现数据集转换（例如，过滤，映射，连接，分组）的常规程序.
加载数据集的时候经常用到def __getitem__(self, index):具体怎么理 …
Feb 5, 2021 · 并且因为这是magic方法，所以只要使用过dataset[index]，__getitem__（self,index）就会获得了这个index。 2.我是使用DataLoader加载数据集的，这其中有batch_size,这意味着必然要 …
如何用dataset加载mnist？ - 知乎
基于此，我考虑的情况是当下载了两个第三方库后，由于有同名问题，系统先扫描了第三库中的dataset和common库文件夹，结果发现没有load_mnist和sigmoid, softmax函数，直接选择报错， …
如何理解Benchmarks？ - 知乎
Benchmark 在机器学习里的定义： Benchmarking measures performance using a specific indicator, resulting in a metric that is then compared to others.Key performance indicators typically …
