Get unique insights from your data by combining the power of SQL Server, R and Python Key Features Use the features of SQL Server 2017 to implement the data science project life cycle Leverage the power of R and Python to design and develop efficient data models find unique insights from your data with powerful techniques for data preprocessing and analysis Book Description SQL Server only started to fully support data science with its two most recent editions. If you are a professional from both worlds, SQL Server and data science, and interested in using SQL Server and Machine Learning (ML) Services for your projects, then this is the ideal book for you. This book is the ideal introduction to data science with Microsoft SQL Server and In-Database ML Services. It covers all stages of a data science project, from businessand data understanding,through data overview, data preparation, modeling and using algorithms, model evaluation, and deployment. You will learn to use the engines and languages that come with SQL Server, including ML Services with R and Python languages and Transact-SQL. You will also learn how to choose which algorithm to use for which task, and learn the working of each algorithm. What you will learn Use the popular programming languages,T-SQL, R, and Python, for data science Understand your data with queries and introductory statistics Create and enhance the datasets for ML Visualize and analyze data using basic and advanced graphs Explore ML using unsupervised and supervised models Deploy models in SQL Server and perform predictions Who this book is for SQL Server professionals who want to start with data science, and data scientists who would like to start using SQL Server in their projects will find this book to be useful. Prior exposure to SQL Server will be helpful.
Get unique insights from your data by combining the power of SQL Server, R and Python Key Features Use the features of SQL Server 2017 to implement the data science project life cycle Leverage the power of R and Python to design and develop efficient data models find unique insights from your data with powerful techniques for data preprocessing and analysis Book Description SQL Server only started to fully support data science with its two most recent editions. If you are a professional from both worlds, SQL Server and data science, and interested in using SQL Server and Machine Learning (ML) Services for your projects, then this is the ideal book for you. This book is the ideal introduction to data science with Microsoft SQL Server and In-Database ML Services. It covers all stages of a data science project, from businessand data understanding,through data overview, data preparation, modeling and using algorithms, model evaluation, and deployment. You will learn to use the engines and languages that come with SQL Server, including ML Services with R and Python languages and Transact-SQL. You will also learn how to choose which algorithm to use for which task, and learn the working of each algorithm. What you will learn Use the popular programming languages,T-SQL, R, and Python, for data science Understand your data with queries and introductory statistics Create and enhance the datasets for ML Visualize and analyze data using basic and advanced graphs Explore ML using unsupervised and supervised models Deploy models in SQL Server and perform predictions Who this book is for SQL Server professionals who want to start with data science, and data scientists who would like to start using SQL Server in their projects will find this book to be useful. Prior exposure to SQL Server will be helpful.
THE BEST SQL BOOK FOR BEGINNERS - HANDS DOWN! *INCLUDES FREE ACCESS TO A SAMPLE DATABASE, SQL BROWSER APP, COMPREHENSION QUIZES & SEVERAL OTHER DIGITAL RESOURCES!* Not sure how to prepare for the data-driven future? This book shows you EXACTLY what you need to know to successfully use the SQL programming language to enhance your career! Are you a developer who wants to expand your mastery to database management? Then you NEED this book. Buy now and start reading today! Are you a project manager who needs to better understand your development team’s needs? A decision maker who needs to make deeper data-driven analysis? Everything you need to know is included in these pages! The ubiquity of big data means that now more than ever there is a burning need to warehouse, access, and understand the contents of massive databases quickly and efficiently. That’s where SQL comes in. SQL is the workhorse programming language that forms the backbone of modern data management and interpretation. Any database management professional will tell you that despite trendy data management languages that come and go, SQL remains the most widely used and most reliable to date, with no signs of stopping. In this comprehensive guide, experienced mentor and SQL expert Walter Shields draws on his considerable knowledge to make the topic of relational database management accessible, easy to understand, and highly actionable. SQL QuickStart Guide is ideal for those seeking to increase their job prospects and enhance their careers, for developers looking to expand their programming capabilities, or for anyone who wants to take advantage of our inevitably data-driven future—even with no prior coding experience! SQL QuickStart Guide Is For: - Professionals looking to augment their job skills in preparation for a data-driven future - Job seekers who want to pad their skills and resume for a durable employability edge - Beginners with zero prior experienceManagers, decision makers, and business owners looking to manage data-driven business insights - Developers looking to expand their mastery beyond the full stackAnyone who wants to be better prepared for our data-driven future! In SQL QuickStart Guide You'll Discover: - The basic structure of databases—what they are, how they work, and how to successfully navigate them - How to use SQL to retrieve and understand data no matter the scale of a database (aided by numerous images and examples) - The most important SQL queries, along with how and when to use them for best effect - Professional applications of SQL and how to “sell” your new SQL skills to your employer, along with other career-enhancing considerations *LIFETIME ACCESS TO FREE SQL RESOURCES*: Each book comes with free lifetime access to tons of exclusive online resources to help you master SQL, such as workbooks, cheat sheets and reference guides. *GIVING BACK* QuickStart Guides proudly supports One Tree Planted as a reforestation partner.
With constantly expanding options such as Azure Data Lake Server (ADLS) and Azure SQL Data Warehouse (ADW), how can developers learn the process and components required to successfully move this data? Quick Start Guide to Azure Data Factory, Azure Data Lake Server, and Azure Data Warehouse teaches you the basics of moving data between Azure SQL solutions using Azure Data Factory. Discover how to build and deploy each of the components needed to integrate data in the cloud with local SQL databases. Mark Beckner's step by step instructions on how to build each component, how to test processes and debug, and how to track and audit the movement of data, will help you to build your own solutions instantly and efficiently. This book includes information on configuration, development, and administration of a fully functional solution and outlines all of the components required for moving data from a local SQL instance through to a fully functional data warehouse with facts and dimensions.
Troubleshoot query performance issues, identify anti-patterns in code, and write efficient T-SQL queries Key Features Discover T-SQL functionalities and services that help you interact with relational databases Understand the roles, tasks, and responsibilities of a T-SQL developer Explore solutions for carrying out database querying tasks, database administration, and troubleshooting Book DescriptionTransact-SQL (T-SQL) is Microsoft's proprietary extension to the SQL language used with Microsoft SQL Server and Azure SQL Database. This book will be a usefu to learning the art of writing efficient T-SQL code in modern SQL Server versions as well as the Azure SQL Database. The book will get you started with query processing fundamentals to help you write powerful, performant T-SQL queries. You will then focus on query execution plans and leverage them for troubleshooting. In later chapters, you will explain how to identify various T-SQL patterns and anti-patterns. This will help you analyze execution plans to gain insights into current performance, and determine whether or not a query is scalable. You will also build diagnostic queries using dynamic management views (DMVs) and dynamic management functions (DMFs) to address various challenges in T-SQL execution. Next, you will work with the built-in tools of SQL Server to shorten the time taken to address query performance and scalability issues. In the concluding chapters, this will guide you through implementing various features, such as Extended Events, Query Store, and Query Tuning Assistant, using hands-on examples. By the end of the book, you will have developed the skills to determine query performance bottlenecks, avoid pitfalls, and discover the anti-patterns in use.What you will learn Use Query Store to understand and easily change query performance Recognize and eliminate bottlenecks that lead to slow performance Deploy quick fixes and long-term solutions to improve query performance Implement best practices to minimize performance risk using T-SQL Achieve optimal performance by ensuring careful query and index design Use the latest performance optimization features in SQL Server 2017 and SQL Server 2019 Protect query performance during upgrades to newer versions of SQL Server Who this book is for This book is for database administrators, database developers, data analysts, data scientists, and T-SQL practitioners who want to get started with writing T-SQL code and troubleshooting query performance issues with the help of practical examples. Previous knowledge of T-SQL querying is not required to get started with this book.
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
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.
This book explains relational theory in practice, and demonstrates through two projects how you can apply it to your use of MariaDB and SQL Server databases. This book covers the important requirements of teaching databases with a practical and progressive perspective. This book offers the straightforward, practical answers you need to help you do your job. This hands-on tutorial/reference/guide to MariaDB and SQL Server is not only perfect for students and beginners, but it also works for experienced developers who aren't getting the most from MariaDB and SQL Server. As you would expect, this book shows how to build from scratch two different databases: MariaDB and SQL Server using Java. In designing a GUI and as an IDE, you will make use of the NetBeans tool. In chapter one, you will learn the basics of cryptography using Java. Here, you will learn how to write a Java program to count Hash, MAC (Message Authentication Code), store keys in a KeyStore, generate PrivateKey and PublicKey, encrypt / decrypt data, and generate and verify digital prints. You will also learn how to create and store salt passwords and verify them. In chapter two, you will create a PostgreSQL database, named Bank, and its tables. In chapter three, you will create a Login table. In this case, you will see how to create a Java GUI using NetBeans to implement it. In addition to the Login table, in this chapter you will also create a Client table. In the case of the Client table, you will learn how to generate and save public and private keys into a database. You will also learn how to encrypt / decrypt data and save the results into a database. In chapter four, you will create an Account table. This account table has the following ten fields: account_id (primary key), client_id (primarykey), account_number, account_date, account_type, plain_balance, cipher_balance, decipher_balance, digital_signature, and signature_verification. In this case, you will learn how to implement generating and verifying digital prints and storing the results into a database. In chapter five, you create a table named Client_Data, which has seven columns: client_data_id (primary key), account_id (primary_key), birth_date, address, mother_name, telephone, and photo_path. In chapter six, you will be taught how to create a SQL Server database, named Crime, and its tables. In chapter seven, you will be taught how to extract image features, utilizing BufferedImage class, in Java GUI. In chapter eight, you will be taught to create Java GUI to view, edit, insert, and delete Suspect table data. This table has eleven columns: suspect_id (primary key), suspect_name, birth_date, case_date, report_date, suspect_ status, arrest_date, mother_name, address, telephone, and photo. In chapter nine, you will be taught to create Java GUI to view, edit, insert, and delete Feature_Extraction table data. This table has eight columns: feature_id (primary key), suspect_id (foreign key), feature1, feature2, feature3, feature4, feature5, and feature6. In chapter ten, you will add two tables: Police_Station and Investigator. These two tables will later be joined to Suspect table through another table, File_Case, which will be built in the seventh chapter. The Police_Station has six columns: police_station_id (primary key), location, city, province, telephone, and photo. The Investigator has eight columns: investigator_id (primary key), investigator_name, rank, birth_date, gender, address, telephone, and photo. Here, you will design a Java GUI to display, edit, fill, and delete data in both tables. In chapter eleven, you will add two tables: Victim and File_Case. The File_Case table will connect four other tables: Suspect, Police_Station, Investigator and Victim. The Victim table has nine columns: victim_id (primary key), victim_name, crime_type, birth_date, crime_date, gender, address, telephone, and photo. The File_Case has seven columns: file_case_id (primary key), suspect_id (foreign key), police_station_id (foreign key), investigator_id (foreign key), victim_id (foreign key), status, and description. Here, you will also design a Java GUI to display, edit, fill, and delete data in both tables. Finally, this book is hopefully useful and can improve database programming skills for every Java/MariaDB/SQL Server programmer.
Build reporting applications and dashboards using the different MicroStrategy objects Key FeaturesLearn the fundamentals of MicroStrategyUse MicroStrategy to get actionable insights from your business dataCreate visualizations and build intuitive dashboards and reportsBook Description MicroStrategy is an enterprise business intelligence application. It turns data into reports for making and executing key organization decisions. This book shows you how to implement Business Intelligence (BI) with MicroStrategy. It takes you from setting up and configuring MicroStrategy to security and administration. The book starts by detailing the different components of the MicroStrategy platform, and the key concepts of Metadata and Project Source. You will then install and configure MicroStrategy and lay down the foundations for building MicroStrategy BI solutions. By learning about objects and different object types, you will develop a strong understanding of the MicroStrategy Schema and Public Objects. With these MicroStrategy objects, you will enhance and scale your BI and Analytics solutions. Finally, you will learn about the administration, security, and monitoring of your BI solution. What you will learnSet up the MicroStrategy Intelligence Server and client toolsCreate a MicroStrategy metadata repository and your first ProjectExplore the main MicroStrategy object types and their dependencies Create, manipulate, and share ReportsCreate and share DashboardsManage Users and GroupsWho this book is for This book is for Business Intelligence professionals or data analysts who want to get started with Microstrategy. Some basic understanding of BI and data analysis will be required to get the most from this book.
With constantly expanding options such as Azure Data Lake Server (ADLS) and Azure SQL Data Warehouse (ADW), how can developers learn the process and components required to successfully move this data? Quick Start Guide to Azure Data Factory, Azure Data Lake Server, and Azure Data Warehouse teaches you the basics of moving data between Azure SQL solutions using Azure Data Factory. Discover how to build and deploy each of the components needed to integrate data in the cloud with local SQL databases. Mark Beckner's step by step instructions on how to build each component, how to test processes and debug, and how to track and audit the movement of data, will help you to build your own solutions instantly and efficiently. This book includes information on configuration, development, and administration of a fully functional solution and outlines all of the components required for moving data from a local SQL instance through to a fully functional data warehouse with facts and dimensions.
