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''The Ultimate Power Query Cookbook for Power BI and Excel''serves up easy-to-follow recipes that transform data into meaningful insights. You will learn to clean messy files, combine datasets, and even use AI magic to Power BI and Excel.

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 resultsTransform: Discover variable types and the tools to work with themImport: Get data into R and in a form convenient for analysisProgram: Learn R tools for solving data problems with greater clarity and easeCommunicate: Integrate prose, code, and results with Quarto

As legacy and other critical systems continue to migrate online, the need for continuous operation is imperative. Code has to handle data issues as well as hard external problems today, including outages of networks, storage systems, power, and ancillary systems. This practical guide provides system administrators, DevSecOps engineers, and cloud architects with a concise yet comprehensive overview on how to use PL/SQL to develop resilient database solutions.Integration specialist Stephen B Morris helps you understand the language, build a PL/SQL toolkit, and collect a suite of reusable components and patterns. You'll dive into the benefits of synthesizing the toolkit with a requirements-driven, feature-oriented approach and learn how to produce resilient solutions by synthesizing the PL/SQL toolkit in conjunction with a scale of resilience.Build solid PL/SQL solutions while avoiding common PL/SQL antipatternsLearn why embedding complex business logic in SQL is often a brittle propositionLearn how to recognize and improve weak PL/SQL codeVerify PL/SQL code by running data-driven, in-database testsUnderstand the safe operation, maintenance, and modification of complex PL/SQL systemsLearn the benefits of thinking about features rather than just use casesDefine good requirements for PL/SQL and hybrid solutions involving PL/SQL and high level languages

Business Database Technology provides essential knowledge of database technology for four-year college/university business students who study information technology and data resource management. Students will learn basic data structure tec

Essential to database design, entity-relationship (ER) diagrams are known for their usefulness in data modeling and mapping out clear database designs. They are also well-known for being difficult to master. With Database Design Using Entity-Relationship Diagrams, Third Edition, database designers, developers, and students preparing to enter the field can quickly learn the ins and outs of data modeling through ER diagramming. Building on the success of the bestselling first and second editions, this accessible text includes a new chapter on the relational model and functional dependencies. It also includes expanded chapters on Enhanced Entity-Relationship (EER) diagrams and reverse mapping. It uses cutting-edge case studies and examples to help readers master database development basics and defines ER and EER diagramming in terms of requirements (end user requests) and specifications (designer feedback to those requests), facilitating agile database development. This book Describes a step-by-step approach for producing an ER diagram and developing a relational database from it Contains exercises, examples, case studies, bibliographies, and summaries in each chapter Details the rules for mapping ER diagrams to relational databases Explains how to reverse engineer a relational database back to an entity-relationship model Includes grammar for the ER diagrams that can be presented back to the user, facilitating agile database development The updated exercises and chapter summaries provide the real-world understanding needed to develop ER and EER diagrams, map them to relational databases, and test the resulting relational database. Complete with a wealth of additional exercises and examples throughout, this edition should be a basic component of any database course. Its comprehensive nature and easy-to-navigate structure make it a resource that students and professionals will turn to throughout their careers.

More organizations than ever understand the importance of data lake architectures for deriving value from their data. Building a robust, scalable, and performant data lake remains a complex proposition, however, with a buffet of tools and options that need to work together to provide a seamless end-to-end pipeline from data to insights.This book provides a concise yet comprehensive overview on the setup, management, and governance of a cloud data lake. Author Rukmani Gopalan, a product management leader and data enthusiast, guides data architects and engineers through the major aspects of working with a cloud data lake, from design considerations and best practices to data format optimizations, performance optimization, cost management, and governance.Learn the benefits of a cloud-based big data strategy for your organizationGet guidance and best practices for designing performant and scalable data lakesExamine architecture and design choices, and data governance principles and strategiesBuild a data strategy that scales as your organizational and business needs increaseImplement a scalable data lake in the cloudUse cloud-based advanced analytics to gain more value from your data

Imagine what you could do if scalability wasn't a problem. With this hands-on guide, you'll learn how the Cassandra database management system handles hundreds of terabytes of data while remaining highly available across multiple data centers. This revised third edition--updated for Cassandra 4.0 and new developments in the Cassandra ecosystem, including deployments in Kubernetes with K8ssandra--provides technical details and practical examples to help you put this database to work in a production environment.Authors Jeff Carpenter and Eben Hewitt demonstrate the advantages of Cassandra's nonrelational design, with special attention to data modeling. Developers, DBAs, and application architects looking to solve a database scaling issue or future-proof an application will learn how to harness Cassandra's speed and flexibility.Understand Cassandra's distributed and decentralized structureUse the Cassandra Query Language (CQL) and cqlsh (the CQL shell)Create a working data model and compare it with an equivalent relational modelDesign and develop applications using client driversExplore cluster topology and learn how nodes exchange dataMaintain a high level of performance in your clusterDeploy Cassandra onsite, in the cloud, or with Docker and KubernetesIntegrate Cassandra with Spark, Kafka, Elasticsearch, Solr, and Lucene

Get the lowdown on CockroachDB, the elastic SQL database built to handle the demands of today's data-driven world. With this practical guide, software developers, architects, and DevOps teams will discover the advantages of building on a distributed SQL database. You'll learn how to create applications that scale elastically and provide seamless delivery for end users while remaining exceptionally resilient and indestructible.Written from scratch for the cloud and architected to scale elastically to handle the demands of cloud native and open source, CockroachDB makes it easier to build and scale modern applications. If you're familiar with distributed systems, you'll quickly discover the benefits of strong data correctness and consistency guarantees as well as optimizations for delivering ultralow latencies to globally distributed end users.With this thorough guide, you'll learn how to:Plan and build applications for distributed infrastructure, including data modeling and schema designMigrate data into CockroachDBRead and write data and run ACID transactions across distributed infrastructureOptimize queries for performance across geographically distributed replicasPlan a CockroachDB deployment for resiliency across single-region and multiregion clustersSecure, monitor, and optimize your CockroachDB deployment

Mikhail Zhilkin, a data scientist who has worked on projects ranging from Candy Crush games to Premier League football players'physical performance, shares his strong views on some of the best and, more importantly, worst practices in data analytics and business intelligence. Why data science is hard, what pitfalls analysts and decision-makers fall into, and what everyone involved can do to give themselves a fighting chance—the book examines these and other questions with the skepticism of someone who has seen the sausage being made. Honest and direct, full of examples from real life, Data Science Without Makeup: A Guidebook for End-Users, Analysts and Managers will be of great interest to people who aspire to work with data, people who already work with data, and people who work with people who work with data—from students to professional researchers and from early-career to seasoned professionals.Mikhail Zhilkin is a data scientist at Arsenal FC. He has previously worked on the popular Candy Crush mobile games and in sports betting.

Design, administer, and deploy high-volume and fault-tolerant database applications using MongoDB 4.xKey FeaturesBuild a powerful and scalable MongoDB database using real industry dataUnderstand the process of designing NoSQL schema with the latest release of MongoDB 4.xExplore the ins and outs of MongoDB, including queries, replication, sharding, and vital admin tasksBook DescriptionWhen it comes to managing a high volume of unstructured and non-relational datasets, MongoDB is the defacto database management system (DBMS) for DBAs and data architects. This updated book includes the latest release and covers every feature in MongoDB 4.x, while helping you get hands-on with building a MongoDB database app. You'll get to grips with MongoDB 4.x concepts such as indexes, database design, data modeling, authentication, and aggregation. As you progress, you'll cover tasks such as performing routine operations when developing a dynamic database-driven website. Using examples, you'll learn how to work with queries and regular database operations. The book will not only guide you through design and implementation, but also help you monitor operations to achieve optimal performance and secure your MongoDB database systems. You'll also be introduced to advanced techniques such as aggregation, map-reduce, complex queries, and generating ad hoc financial reports on the fly. Later, the book shows you how to work with multiple collections as well as embedded arrays and documents, before finally exploring key topics such as replication, sharding, and security using practical examples. By the end of this book, you'll be well-versed with MongoDB 4.x and be able to perform development and administrative tasks associated with this NoSQL database.What you will learnUnderstand how to configure and install MongoDB 4.xBuild a database-driven website using MongoDB as the backendPerform basic database operations and handle complex MongoDB queriesDevelop a successful MongoDB database design for large corporate customers with complex requirementsSecure MongoDB database systems by establishing role-based access control with X.509 transport-level securityOptimize reads and writes directed to a replica set or sharded clusterPerform essential MongoDB administration tasksMaintain database performance through monitoringWho this book is forThis book is a MongoDB tutorial for DevOps engineers, database developers, database administrators, system administrators and those who are just getting started with NoSQL and looking to build document-oriented databases and gain real-world experience in managing databases using MongoDB. Basic knowledge of databases and Python is required to get started with this DBMS book.

Discover how to use Neo4j to identify relationships within complex and large graph datasets using graph modeling, graph algorithms, and machine learningKey FeaturesGet up and running with graph analytics with the help of real-world examplesExplore various use cases such as fraud detection, graph-based search, and recommendation systemsGet to grips with the Graph Data Science library with the help of examples, and use Neo4j in the cloud for effective application scalingBook DescriptionNeo4j is a graph database that includes plugins to run complex graph algorithms. The book starts with an introduction to the basics of graph analytics, the Cypher query language, and graph architecture components, and helps you to understand why enterprises have started to adopt graph analytics within their organizations. You'll find out how to implement Neo4j algorithms and techniques and explore various graph analytics methods to reveal complex relationships in your data. You'll be able to implement graph analytics catering to different domains such as fraud detection, graph-based search, recommendation systems, social networking, and data management. You'll also learn how to store data in graph databases and extract valuable insights from it. As you become well-versed with the techniques, you'll discover graph machine learning in order to address simple to complex challenges using Neo4j. You will also understand how to use graph data in a machine learning model in order to make predictions based on your data. Finally, you'll get to grips with structuring a web application for production using Neo4j. By the end of this book, you'll not only be able to harness the power of graphs to handle a broad range of problem areas, but you'll also have learned how to use Neo4j efficiently to identify complex relationships in your data.What you will learnBecome well-versed with Neo4j graph database building blocks, nodes, and relationshipsDiscover how to create, update, and delete nodes and relationships using Cypher queryingUse graphs to improve web search and recommendationsUnderstand graph algorithms such as pathfinding, spatial search, centrality, and community detectionFind out different steps to integrate graphs in a normal machine learning pipelineFormulate a link prediction problem in the context of machine learningImplement graph embedding algorithms such as DeepWalk, and use them in Neo4j graphsWho this book is forThis book is for data analysts, business analysts, graph analysts, and database developers looking to store and process graph data to reveal key data insights. This book will also appeal to data scientists who want to build intelligent graph applications catering to different domains. Some experience with Neo4j is required.

With the aim of simplifying relational database modeling, Database Modeling Step-by-Step presents the standard approach to database normalization and then adds its own approach, which is a more simplistic, intuitive way to building relational database models. Going from basics to contemporary topics, the book opens with relational data modeling and ends with BigData database modeling following a road map of the evolution in relational modeling and including brief introductions to data warehousing and BigData modeling. A break-down of the elements of a model explains what makes up a relational data model. This is followed by a comparison between standard normalization and a more simplistic intuitive approach to data modeling that a beginner can follow and understand. A brief chapter explains how to use the database programming language SQL (Structured Query Language), which reads from and writes to a relational database. SQL is fundamental to data modeling because it helps in understanding how the model is used. In addition to the relational model, the last three chapters cover important modern world topics including denormalization that leads into data warehouses and BigData database modeling. The book explains how there is not much to logical data modeling in BigData databases because as they are often schema-less, which means that BigData databases do not have schemas embedded into the database itself, they have no metadata and thus not much of a logical data model. Online bonus chapters include a case study that covers relational data modeling and are available at the author's web site: www.oracletroubleshooter.com/datamodeling.html

As data floods into your company, you need to put it to work right away—and SQL is the best tool for the job. With the latest edition of this introductory guide, author Alan Beaulieu helps developers get up to speed with SQL fundamentals for writing database applications, performing administrative tasks, and generating reports. You'll find new chapters on SQL and big data, analytic functions, and working with very large databases.Each chapter presents a self-contained lesson on a key SQL concept or technique using numerous illustrations and annotated examples. Exercises let you practice the skills you learn. Knowledge of SQL is a must for interacting with data. With Learning SQL, you'll quickly discover how to put the power and flexibility of this language to work.Move quickly through SQL basics and several advanced featuresUse SQL data statements to generate, manipulate, and retrieve dataCreate database objects, such as tables, indexes, and constraints with SQL schema statementsLearn how datasets interact with queries; understand the importance of subqueriesConvert and manipulate data with SQL's built-in functions and use conditional logic in data statements

Graph Databases in Action introduces you to graph database concepts by comparing them with relational database constructs. You'll learn just enough theory to get started, then progress to hands-on development. Discover use cases involving social networking, recommendation engines, and personalization.Summary Relationships in data often look far more like a web than an orderly set of rows and columns. Graph databases shine when it comes to revealing valuable insights within complex, interconnected data such as demographics, financial records, or computer networks. In Graph Databases in Action, experts Dave Bechberger and Josh Perryman illuminate the design and implementation of graph databases in real-world applications. You'll learn how to choose the right database solutions for your tasks, and how to use your new knowledge to build agile, flexible, and high-performing graph-powered applications! Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Isolated data is a thing of the past! Now, data is connected, and graph databases—like Amazon Neptune, Microsoft Cosmos DB, and Neo4j—are the essential tools of this new reality. Graph databases represent relationships naturally, speeding the discovery of insights and driving business value. About the book Graph Databases in Action introduces you to graph database concepts by comparing them with relational database constructs. You'll learn just enough theory to get started, then progress to hands-on development. Discover use cases involving social networking, recommendation engines, and personalization. What's inside Graph databases vs. relational databases Systematic graph data modeling Querying and navigating a graph Graph patterns Pitfalls and antipatterns About the reader For software developers. No experience with graph databases required. About the author Dave Bechberger and Josh Perryman have decades of experience building complex data-driven systems and have worked with graph databases since 2014. Table of Contents PART 1 - GETTING STARTED WITH GRAPH DATABASES 1 Introduction to graphs 2 Graph data modeling 3 Running basic and recursive traversals 4 Pathfinding traversals and mutating graphs 5 Formatting results 6 Developing an application PART 2 - BUILDING ON GRAPH DATABASES 7 Advanced data modeling techniques 8 Building traversals using known walks 9 Working with subgraphs PART 3 - MOVING BEYOND THE BASICS 10 Performance, pitfalls, and anti-patterns 11 What's next: Graph analytics, machine learning, and resources

Imagine what you could do if scalability wasn't a problem. With this hands-on guide, you'll learn how the Cassandra database management system handles hundreds of terabytes of data while remaining highly available across multiple data centers. This third edition—updated for Cassandra 4.0—provides the technical details and practical examples you need to put this database to work in a production environment.Authors Jeff Carpenter and Eben Hewitt demonstrate the advantages of Cassandra's nonrelational design, with special attention to data modeling. If you're a developer, DBA, or application architect looking to solve a database scaling issue or future-proof your application, this guide helps you harness Cassandra's speed and flexibility.Understand Cassandra's distributed and decentralized structureUse the Cassandra Query Language (CQL) and cqlsh—the CQL shellCreate a working data model and compare it with an equivalent relational modelDevelop sample applications using client drivers for languages including Java, Python, and Node.jsExplore cluster topology and learn how nodes exchange data

Leverage the power of MongoDB 4.x to build and administer fault-tolerant database applicationsKey FeaturesMaster the new features and capabilities of MongoDB 4.xImplement advanced data modeling, querying, and administration techniques in MongoDBIncludes rich case-studies and best practices followed by expert MongoDB developersBook DescriptionMongoDB is the best platform for working with non-relational data and is considered to be the smartest tool for organizing data in line with business needs. The recently released MongoDB 4.x supports ACID transactions and makes the technology an asset for enterprises across the IT and fintech sectors. This book provides expertise in advanced and niche areas of managing databases (such as modeling and querying databases) along with various administration techniques in MongoDB, thereby helping you become a successful MongoDB expert. The book helps you understand how the newly added capabilities function with the help of some interesting examples and large datasets. You will dive deeper into niche areas such as high-performance configurations, optimizing SQL statements, configuring large-scale sharded clusters, and many more. You will also master best practices in overcoming database failover, and master recovery and backup procedures for database security. By the end of the book, you will have gained a practical understanding of administering database applications both on premises and on the cloud; you will also be able to scale database applications across all servers.What you will learnPerform advanced querying techniques such as indexing and expressionsConfigure, monitor, and maintain a highly scalable MongoDB environmentMaster replication and data sharding to optimize read/write performanceAdminister MongoDB-based applications on premises or on the cloudIntegrate MongoDB with big data sources to process huge amounts of dataDeploy MongoDB on Kubernetes containersUse MongoDB in IoT, mobile, and serverless environmentsWho this book is forThis book is ideal for MongoDB developers and database administrators who wish to become successful MongoDB experts and build scalable and fault-tolerant applications using MongoDB. It will also be useful for database professionals who wish to become certified MongoDB professionals. Some understanding of MongoDB and basic database concepts is required to get the most out of this book.

Leverage the power of PostgreSQL 10 to design, administer and maintain a high-performance database solutionKey Features[•]Obtain optimal PostgreSQL 10 database performance, ranging from initial design to routine maintenance[•] Fine tune the performance of your queries and avoid the common pitfalls that can slow your system down[•] Contains tips and tricks on scaling successful database installations, and ensuring a highly available PostgreSQL solutionBook DescriptionPostgreSQL database servers have a common set of problems that they encounter as their usage gets heavier and requirements get more demanding. Peek into the future of your PostgreSQL 10 database's problems today. Know the warning signs to look for and how to avoid the most common issues before they even happen. Surprisingly, most PostgreSQL database applications evolve in the same way—choose the right hardware, tune the operating system and server memory use, optimize queries against the database and CPUs with the right indexes, and monitor every layer, from hardware to queries, using tools from inside and outside PostgreSQL. Also, using monitoring insight, PostgreSQL database applications continuously rework the design and configuration. On reaching the limits of a single server, they break things up; connection pooling, caching, partitioning, replication, and parallel queries can all help handle increasing database workloads. By the end of this book, you will have all the knowledge you need to design, run, and manage your PostgreSQL solution while ensuring high performance and high availabilityWhat you will learn[•]Learn best practices for scaling PostgreSQL 10 installations[•]Discover the best hardware for developing high-performance PostgreSQL applications[•]Benchmark your whole system – from hardware to application[•]Learn by real examples how server parameters impact performance[•]Discover PostgreSQL 10 features for partitioning and parallel query[•]Monitor your server, both inside and outside the database[•]Design and implement a good replication system on PostgreSQL 10Who this book is forThis book is designed for database administrators and PostgreSQL architects who already use or plan to exploit the features of PostgreSQL 10 to design and maintain a high-performance PostgreSQL database. A working knowledge of SQL, and some experience with PostgreSQL will be helpful in getting the most out of this book.

Develop and run efficient R scripts and predictive models for SQL Server 2017Key FeaturesLearn how you can combine the power of R and SQL Server 2017 to build efficient, cost-effective data science solutionsLeverage the capabilities of R Services to perform advanced analytics—from data exploration to predictive modelingA quick primer with practical examples to help you get up- and- running with SQL Server 2017 Machine Learning Services with R, as part of database solutions with continuous integration / continuous delivery.Book DescriptionR Services was one of the most anticipated features in SQL Server 2016, improved significantly and rebranded as SQL Server 2017 Machine Learning Services. Prior to SQL Server 2016, many developers and data scientists were already using R to connect to SQL Server in siloed environments that left a lot to be desired, in order to do additional data analysis, superseding SSAS Data Mining or additional CLR programming functions. With R integrated within SQL Server 2017, these developers and data scientists can now benefit from its integrated, effective, efficient, and more streamlined analytics environment. This book gives you foundational knowledge and insights to help you understand SQL Server 2017 Machine Learning Services with R. First and foremost, the book provides practical examples on how to implement, use, and understand SQL Server and R integration in corporate environments, and also provides explanations and underlying motivations. It covers installing Machine Learning Services;maintaining, deploying, and managing code;and monitoring your services. Delving more deeply into predictive modeling and the RevoScaleR package, this book also provides insights into operationalizing code and exploring and visualizing data. To complete the journey, this book covers the new features in SQL Server 2017 and how they are compatible with R, amplifying their combined power.What you will learnGet an overview of SQL Server 2017 Machine Learning Services with RManage SQL Server Machine Learning Services from installation to configuration and maintenanceHandle and operationalize R codeExplore RevoScaleR R algorithms and create predictive modelsDeploy, manage, and monitor database solutions with RExtend R with SQL Server 2017 featuresExplore the power of R for database administratorsWho this book is forThis book is for data analysts, data scientists, and database administrators with some or no experience in R but who are eager to easily deliver practical data science solutions in their day-to-day work (or future projects) using SQL Server.

Data is getting bigger and more complex by the day, and so are your choices in handling it. Explore some of the most cutting-edge databases available - from a traditional relational database to newer NoSQL approaches - and make informed decisions about challenging data storage problems. This is the only comprehensive guide to the world of NoSQL databases, with in-depth practical and conceptual introductions to seven different technologies: Redis, Neo4J, CouchDB, MongoDB, HBase, Postgres, and DynamoDB. This second edition includes a new chapter on DynamoDB and updated content for each chapter. While relational databases such as MySQL remain as relevant as ever, the alternative, NoSQL paradigm has opened up new horizons in performance and scalability and changed the way we approach data-centric problems. This book presents the essential concepts behind each database alongside hands-on examples that make each technology come alive. With each database, tackle a real-world problem that highlights the concepts and features that make it shine. Along the way, explore five database models - relational, key/value, columnar, document, and graph - from the perspective of challenges faced by real applications. Learn how MongoDB and CouchDB are strikingly different, make your applications faster with Redis and more connected with Neo4J, build a cluster of HBase servers using cloud services such as Amazon's Elastic MapReduce, and more. This new edition brings a brand new chapter on DynamoDB, updated code samples and exercises, and a more up-to-date account of each database's feature set. Whether you're a programmer building the next big thing, a data scientist seeking solutions to thorny problems, or a technology enthusiast venturing into new territory, you will find something to inspire you in this book.What You Need:You'll need a •nix shell (Mac OS or Linux preferred, Windows users will need Cygwin), Java 6 (or greater), and Ruby 1.8.7 (or greater). Each chapter will list the downloads required for that database.

Find, explore, and extract big data to transform into actionable insights Key FeaturesPerform end-to-end data analysis—from exploration to visualizationReal-world examples, tasks, and interview queries to be a proficient data scientistUnderstand how SQL is used for big data processing using HiveQL and SparkSQLBook DescriptionSQL Server is a relational database management system that enables you to cover end-to-end data science processes using various inbuilt services and features. Hands-On Data Science with SQL Server 2017 starts with an overview of data science with SQL to understand the core tasks in data science. You will learn intermediate-to-advanced level concepts to perform analytical tasks on data using SQL Server. The book has a unique approach, covering best practices, tasks, and challenges to test your abilities at the end of each chapter. You will explore the ins and outs of performing various key tasks such as data collection, cleaning, manipulation, aggregations, and filtering techniques. As you make your way through the chapters, you will turn raw data into actionable insights by wrangling and extracting data from databases using T-SQL. You will get to grips with preparing and presenting data in a meaningful way, using Power BI to reveal hidden patterns. In the concluding chapters, you will work with SQL Server integration services to transform data into a useful format and delve into advanced examples covering machine learning concepts such as predictive analytics using real-world examples. By the end of this book, you will be in a position to handle the growing amounts of data and perform everyday activities that a data science professional performs.What you will learnUnderstand what data science is and how SQL Server is used for big data processingAnalyze incoming data with SQL queries and visualizationsCreate, train, and evaluate predictive modelsMake predictions using trained models and establish regular retraining coursesIncorporate data source querying into SQL ServerEnhance built-in T-SQL capabilities using SQLCLRVisualize data with Reporting Services, Power View, and Power BITransform data with R, Python, and AzureWho this book is forHands-On Data Science with SQL Server 2017 is intended for data scientists, data analysts, and big data professionals who want to master their skills learning SQL and its applications. This book will be helpful even for beginners who want to build their career as data science professionals using the power of SQL Server 2017. Basic familiarity with SQL language will aid with understanding the concepts covered in this book.

Mine Ether, deploy smart contracts, tokens, and ICOs, and manage security vulnerabilities of EthereumKey FeaturesBuild end-to-end decentralized Ethereum apps using Truffle, Web3, and SolidityExplore various solution-based recipes to build smart contracts and foolproof decentralized applicationsDevelop decentralized marketplaces from scratch, build wallets, and manage transactionsBook DescriptionEthereum and Blockchain will change the way software is built for business transactions. Most industries have been looking to leverage these new technologies to gain efficiencies and create new business models and opportunities. The Ethereum Cookbook covers various solutions such as setting up Ethereum, writing smart contracts, and creating tokens, among others. You'll learn about the security vulnerabilities, along with other protocols of Ethereum. Once you have understood the basics, you'll move on to exploring various design decisions and tips to make your application scalable and secure. In addition to this, you'll work with various Ethereum packages such as Truffle, Web3, and Ganache. By the end of this book, you'll have comprehensively grasped the Ethereum principles and ecosystem. What you will learnEfficiently write smart contracts in EthereumBuild scalable distributed applications and deploy themUse tools and frameworks to develop, deploy, and test your applicationUse block explorers such as Etherscan to find a specific transactionCreate your own tokens, initial coin offerings (ICOs), and gamesUnderstand various security flaws in smart contracts in order to avoid themWho this book is forThe Ethereum Cookbook is for you if you are a software engineer, Blockchain developer, or research scientist who wants to build smart contracts, develop decentralized applications, and facilitate peer-to-peer transaction. It is assumed that you are familiar with Blockchain concepts and have sound knowledge of JavaScript.

Expert tabular modeling techniques for building and deploying cutting-edge business analytical reporting solutionsKey Features[•] Build and deploy Tabular Model projects from relational data sources[•] Leverage DAX and create high-performing calculated fields and measures[•] Create ad-hoc reports based on a Tabular Model solution[•] Useful tips to monitor and optimize your tabular solutionsBook DescriptionSQL Server Analysis Service (SSAS) has been widely used across multiple businesses to build smart online analytical reporting solutions. It includes two different types of modeling for analysis services: Tabular and Multi Dimensional. This book covers Tabular modeling, which uses tables and relationships with a fast in-memory engine to provide state of the art compression algorithms and query performance. The book begins by quickly taking you through the concepts required to model tabular data and set up the necessary tools and services. As you learn to create tabular models using tools such as Excel and Power View, you'll be shown various strategies to deploy your model on the server and choose a query mode (In-memory or DirectQuery) that best suits your reporting needs. You'll also learn how to implement key and newly introduced DAX functions to create calculated columns and measures for your model data. Last but not least, you'll be shown techniques that will help you administer and secure your BI implementation along with some widely used tips and tricks to optimize your reporting solution. By the end of this book, you'll have gained hands-on experience with the powerful new features that have been added to Tabular models in SSAS 2016 and you'll be able to improve user satisfaction with faster reports and analytical queries.What you will learn[•] Learn all about Tabular services mode and how it speeds up development[•] Build solutions using sample datasets[•] Explore built-in actions and transitions in SSAS 2016[•] Implement row-column, and role-based security in a Tabular Data model[•] Realize the benefits of in-memory and DirectQuery deployment modes[•] Get up to date with the new features added to SQL Server 2016 Analysis Services[•] Optimize Data Models and Relationships UsageWho this book is forThis book is for SQL BI professionals and Architects who want to exploit the full power of the new Tabular models in Analysis Services. Some knowledge of previous versions of Analysis services would be helpful but is not essential.

Leverage the power of PostgreSQL 10 to build powerful database and data warehousing applications.Key FeaturesBe introduced to the concept of relational databases and PostgreSQL, one of the fastest growing open source databases in the worldLearn client-side and server-side programming in PostgreSQL, and how to administer PostgreSQL databasesDiscover tips on implementing efficient database solutions with PostgreSQL 10Book DescriptionPostgreSQL is one of the most popular open source databases in the world, supporting the most advanced features included in SQL standards. This book will familiarize you with the latest features released in PostgreSQL 10. We'll start with a thorough introduction to PostgreSQL and the new features introduced in PostgreSQL 10. We'll cover the Data Definition Language (DDL) with an emphasis on PostgreSQL, and the common DDL commands supported by ANSI SQL. You'll learn to create tables, define integrity constraints, build indexes, and set up views and other schema objects. Moving on, we'll cover the concepts of Data Manipulation Language (DML) and PostgreSQL server-side programming capabilities using PL/pgSQL. We'll also explore the NoSQL capabilities of PostgreSQL and connect to your PostgreSQL database to manipulate data objects. By the end of this book, you'll have a thorough understanding of the basics of PostgreSQL 10 and will have the necessary skills to build efficient database solutions.What you will learnUnderstand the fundamentals of relational databases, relational algebra, and data modelingInstall a PostgreSQL cluster, create a database, and implement your data modelCreate tables and views, define indexes, and implement triggers, stored procedures, and other schema objectsUse the Structured Query Language (SQL) to manipulate data in the databaseImplement business logic on the server side with triggers and stored procedures using PL/pgSQLMake use of advanced data types supported by PostgreSQL 10: arrays, hstore, JSONB, and othersDevelop OLAP database solutions using the most recent features of PostgreSQL 10Connect your Python applications to a PostgreSQL database and work with data efficientlyTest your database code, find bottlenecks, improve performance, and enhance the reliability of database applicationsWho this book is forIf you're interested in learning more about PostgreSQL, one of the most popular relational databases in the world, then this book is for you. Those looking to build solid database or data warehousing applications with PostgreSQL 10 will also find this book a useful resource. No prior knowledge of database programming or administration is required to get started with this book.

It is almost universally accepted that requirements documents for new or enhanced IT systems by business analysts should include a ‘data model'to represent the information that has to be handled by the system. Starting from first principles, this book will help business analysts to develop the skills required to construct data models through comprehensive coverage of entity relationship and class modelling, in line with, and beyond, the BCS Data Analysis syllabus.

Key Features[•] Master the advanced modeling, querying, and administration techniques in MongoDB and become a MongoDB expert[•] Covers the latest updates and Big Data features frequently used by professional MongoDB developers and administrators[•] If your goal is to become a certified MongoDB professional, this book is your perfect companionBook DescriptionMongoDB has grown to become the de facto NoSQL database with millions of users—from small startups to Fortune 500 companies. Addressing the limitations of SQL schema-based databases, MongoDB pioneered a shift of focus for DevOps and offered sharding and replication maintainable by DevOps teams. The book is based on MongoDB 3.x and covers topics ranging from database querying using the shell, built in drivers, and popular ODM mappers to more advanced topics such as sharding, high availability, and integration with big data sources. You will get an overview of MongoDB and how to play to its strengths, with relevant use cases. After that, you will learn how to query MongoDB effectively and make use of indexes as much as possible. The next part deals with the administration of MongoDB installations on-premise or in the cloud. We deal with database internals in the next section, explaining storage systems and how they can affect performance. The last section of this book deals with replication and MongoDB scaling, along with integration with heterogeneous data sources. By the end this book, you will be equipped with all the required industry skills and knowledge to become a certified MongoDB developer and administrator. What you will learn[•] Get hands-on with advanced querying techniques such as indexing, expressions, arrays, and more.[•] Configure, monitor, and maintain highly scalable MongoDB environment like an expert.[•] Master replication and data sharding to optimize read/write performance.[•] Design secure and robust applications based on MongoDB.[•] Administer MongoDB-based applications on-premise or in the cloud[•] Scale MongoDB to achieve your design goals[•] Integrate MongoDB with big data sources to process huge amounts of dataWho this book is forMastering MongoDB is a book for database developers, architects, and administrators who want to learn how to use MongoDB more effectively and productively. If you have experience in, and are interested in working with, NoSQL databases to build apps and websites, then this book is for you.

Get the most out of the popular Java libraries and tools to perform efficient data analysisKey FeaturesGet your basics right for data analysis with Java and make sense of your data through effective visualizations.Use various Java APIs and tools such as Rapidminer and WEKA for effective data analysis and machine learning.This is your companion to understanding and implementing a solid data analysis solution using JavaBook DescriptionData analysis is a process of inspecting, cleansing, transforming, and modeling data with the aim of discovering useful information. Java is one of the most popular languages to perform your data analysis tasks. This book will help you learn the tools and techniques in Java to conduct data analysis without any hassle. After getting a quick overview of what data science is and the steps involved in the process, you'll learn the statistical data analysis techniques and implement them using the popular Java APIs and libraries. Through practical examples, you will also learn the machine learning concepts such as classification and regression. In the process, you'll familiarize yourself with tools such as Rapidminer and WEKA and see how these Java-based tools can be used effectively for analysis. You will also learn how to analyze text and other types of multimedia. Learn to work with relational, NoSQL, and time-series data. This book will also show you how you can utilize different Java-based libraries to create insightful and easy to understand plots and graphs. By the end of this book, you will have a solid understanding of the various data analysis techniques, and how to implement them using Java. What you will learnDevelop Java programs that analyze data sets of nearly any size, including textImplement important machine learning algorithms such as regression, classification, and clusteringInterface with and apply standard open source Java libraries and APIs to analyze and visualize dataProcess data from both relational and non-relational databases and from time-series dataEmploy Java tools to visualize data in various formsUnderstand multimedia data analysis algorithms and implement them in Java.Who this book is forIf you are a student or Java developer or a budding data scientist who wishes to learn the fundamentals of data analysis and learn to perform data analysis with Java, this book is for you. Some familiarity with elementary statistics and relational databases will be helpful but is not mandatory, to get the most out of this book. A firm understanding of Java is required.

SummaryMongoDB in Action, Second Edition is a completely revised and updated version. It introduces MongoDB 3.0 and the document-oriented database model. This perfectly paced book gives you both the big picture you'll need as a developer and enough low-level detail to satisfy system engineers.Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.About the TechnologyThis document-oriented database was built for high availability, supports rich, dynamic schemas, and lets you easily distribute data across multiple servers. MongoDB 3.0 is flexible, scalable, and very fast, even with big data loads.About the BookMongoDB in Action, Second Edition is a completely revised and updated version. It introduces MongoDB 3.0 and the document-oriented database model. This perfectly paced book gives you both the big picture you'll need as a developer and enough low-level detail to satisfy system engineers. Lots of examples will help you develop confidence in the crucial area of data modeling. You'll also love the deep explanations of each feature, including replication, auto-sharding, and deployment.What's InsideIndexes, queries, and standard DB operationsAggregation and text searchingMap-reduce for custom aggregations and reportingDeploying for scale and high availabilityUpdated for Mongo 3.0 About the ReaderWritten for developers. No previous MongoDB or NoSQL experience is assumed.About the AuthorsAfter working at MongoDB, Kyle Banker is now at a startup. Peter Bakkum is a developer with MongoDB expertise. Shaun Verch has worked on the core server team at MongoDB. A Genentech engineer, Doug Garrett is one of the winners of the MongoDB Innovation Award for Analytics. A software architect, Tim Hawkins has led search engineering at Yahoo Europe. Technical Contributor: Wouter Thielen. Technical Editor: Mihalis Tsoukalos. Table of ContentsPART 1 GETTING STARTEDA database for the modern web MongoDB through the JavaScript shell Writing programs using MongoDB PART 2 APPLICATION DEVELOPMENT IN MONGODBDocument-oriented data Constructing queries Aggregation Updates, atomic operations, and deletes PART 3 MONGODB MASTERYIndexing and query optimization Text search WiredTiger and pluggable storage Replication Scaling your system with sharding Deployment and administration

Familiarize yourself with probabilistic graphical models through real-world problems and illustrative code examples in RKey Features[•] Predict and use a probabilistic graphical models (PGM) as an expert system[•] Comprehend how your computer can learn Bayesian modeling to solve real-world problems[•] Know how to prepare data and feed the models by using the appropriate algorithms from the appropriate R packageBook DescriptionProbabilistic graphical models (PGM, also known as graphical models) are a marriage between probability theory and graph theory. Generally, PGMs use a graph-based representation. Two branches of graphical representations of distributions are commonly used, namely Bayesian networks and Markov networks. R has many packages to implement graphical models. We'll start by showing you how to transform a classical statistical model into a modern PGM and then look at how to do exact inference in graphical models. Proceeding, we'll introduce you to many modern R packages that will help you to perform inference on the models. We will then run a Bayesian linear regression and you'll see the advantage of going probabilistic when you want to do prediction. Next, you'll master using R packages and implementing its techniques. Finally, you'll be presented with machine learning applications that have a direct impact in many fields. Here, we'll cover clustering and the discovery of hidden information in big data, as well as two important methods, PCA and ICA, to reduce the size of big problems. What you will learn[•] Understand the concepts of PGM and which type of PGM to use for which problem[•] Tune the model's parameters and explore new models automatically[•] Understand the basic principles of Bayesian models, from simple to advanced[•] Transform the old linear regression model into a powerful probabilistic model[•] Use standard industry models but with the power of PGM[•] Understand the advanced models used throughout today s industry[•] See how to compute posterior distribution with exact and approximate inference algorithmsWho this book is forThis book is for anyone who has to deal with lots of data and draw conclusions from it, especially when the data is noisy or uncertain. Data scientists, machine learning enthusiasts, engineers, and those who curious about the latest advances in machine learning will find PGM interesting.

Imagine what you could do if scalability wasn't a problem. With this hands-on guide, you'll learn how the Cassandra database management system handles hundreds of terabytes of data while remaining highly available across multiple data centers. This expanded second edition—updated for Cassandra 3.0—provides the technical details and practical examples you need to put this database to work in a production environment.Authors Jeff Carpenter and Eben Hewitt demonstrate the advantages of Cassandra's non-relational design, with special attention to data modeling. If you're a developer, DBA, or application architect looking to solve a database scaling issue or future-proof your application, this guide helps you harness Cassandra's speed and flexibility.Understand Cassandra's distributed and decentralized structureUse the Cassandra Query Language (CQL) and cqlsh—the CQL shellCreate a working data model and compare it with an equivalent relational modelDevelop sample applications using client drivers for languages including Java, Python, and Node.jsExplore cluster topology and learn how nodes exchange dataMaintain a high level of performance in your clusterDeploy Cassandra on site, in the Cloud, or with DockerIntegrate Cassandra with Spark, Hadoop, Elasticsearch, Solr, and Lucene

SummaryJava Persistence with Hibernate, Second Edition explores Hibernate by developing an application that ties together hundreds of individual examples. In this revised edition, authors Christian Bauer, Gavin King, and Gary Gregory cover Hibernate 5 in detail with the Java Persistence 2.1 standard (JSR 338). All examples have been updated for the latest Hibernate and Java EE specification versions.About the TechnologyPurchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.Persistence—the ability of data to outlive an instance of a program—is central to modern applications. Hibernate, the most popular Java persistence tool, offers automatic and transparent object/relational mapping, making it a snap to work with SQL databases in Java applications.About the BookJava Persistence with Hibernate, Second Edition explores Hibernate by developing an application that ties together hundreds of individual examples. You'll immediately dig into the rich programming model of Hibernate, working through mappings, queries, fetching strategies, transactions, conversations, caching, and more. Along the way you'll find a well-illustrated discussion of best practices in database design and optimization techniques. In this revised edition, authors Christian Bauer, Gavin King, and Gary Gregory cover Hibernate 5 in detail with the Java Persistence 2.1 standard (JSR 338). All examples have been updated for the latest Hibernate and Java EE specification versions.What's InsideObject/relational mapping conceptsEfficient database application designComprehensive Hibernate and Java Persistence referenceIntegration of Java Persistence with EJB, CDI, JSF, and JAX-RS • Unmatched breadth and depthAbout the ReaderThe book assumes a working knowledge of Java.About the AuthorsChristian Bauer is a member of the Hibernate developer team and a trainer and consultant. Gavin King is the founder of the Hibernate project and a member of the Java Persistence expert group (JSR 220). Gary Gregory is a principal software engineer working on application servers and legacy integration.Table of ContentsPART 1 GETTING STARTED WITH ORMUnderstanding object/relational persistenceStarting a projectDomain models and metadataPART 2 MAPPING STRATEGIESMapping persistent classesMapping value typesMapping inheritanceMapping collections and entity associationsAdvanced entity association mappingsComplex and legacy schemasPART 3 TRANSACTIONAL DATA PROCESSINGManaging dataTransactions and concurrencyFetch plans, strategies, and profilesFiltering dataPART 4 WRITING QUERIESCreating and executing queriesThe query languagesAdvanced query optionsCustomizing SQL

SQL is full of difficulties and traps for the unwary. You can avoid them if you understand relational theory, but only if you know how to put that theory into practice. In this book, Chris Date explains relational theory in depth, and demonstrates through numerous examples and exercises how you can apply it to your use of SQL.This third edition has been revised, extended, and improved throughout. Topics whose treatment has been expanded include data types and domains, table comparisons, image relations, aggregate operators and summarization, view updating, and subqueries. A special feature of this edition is a new appendix on NoSQL and relational theory.Could you write an SQL query to find employees who have worked at least once in every programming department in the company? And be sure it's correct?Why is proper column naming so important?Nulls in the database cause wrong answers. Why? What you can do about it?How can image relations help you formulate complex SQL queries?SQL supports'quantified comparisons,'but they're better avoided. Why? And how?Database theory and practice have evolved considerably since Codd first defined the relational model, back in 1969. This book draws on decades of experience to present the most up to date treatment of the material available anywhere. Anyone with a modest to advanced background in SQL can benefit from the insights it contains. The book is product independent.

Discover how graph databases can help you manage and query highly connected data. With this practical book, you'll learn how to design and implement a graph database that brings the power of graphs to bear on a broad range of problem domains. Whether you want to speed up your response to user queries or build a database that can adapt as your business evolves, this book shows you how to apply the schema-free graph model to real-world problems.This second edition includes new code samples and diagrams, using the latest Neo4j syntax, as well as information on new functionality. Learn how different organizations are using graph databases to outperform their competitors. With this book's data modeling, query, and code examples, you'll quickly be able to implement your own solution.Model data with the Cypher query language and property graph modelLearn best practices and common pitfalls when modeling with graphsPlan and implement a graph database solution in test-driven fashionExplore real-world examples to learn how and why organizations use a graph databaseUnderstand common patterns and components of graph database architectureUse analytical techniques and algorithms to mine graph database information

If you are interested in Cassandra and want to develop real-world analysis applications, then this book is perfect for you. It would be helpful to have prior knowledge of NoSQL database.

Whether you're building a social media site or an internal-use enterprise application, this hands-on guide shows you the connection between MongoDB and the business problems it's designed to solve. You'll learn how to apply MongoDB design patterns to several challenging domains, such as ecommerce, content management, and online gaming. Using Python and JavaScript code examples, you'll discover how MongoDB lets you scale your data model while simplifying the development process.Many businesses launch NoSQL databases without understanding the techniques for using their features most effectively. This book demonstrates the benefits of document embedding, polymorphic schemas, and other MongoDB patterns for tackling specific big data use cases, including:Operational intelligence: Perform real-time analytics of business dataEcommerce: Use MongoDB as a product catalog master or inventory management systemContent management: Learn methods for storing content nodes, binary assets, and discussionsOnline advertising networks: Apply techniques for frequency capping ad impressions, and keyword targeting and biddingSocial networking: Learn how to store a complex social graph, modeled after Google+Online gaming: Provide concurrent access to character and world data for a multiplayer role-playing game

This book will have a practical approach, thus making it easy for the readers to understand and learn with step-by-step instructions.This book is for Java developers who would like to learn all about the MyBatis framework and are looking for a practical guide to get started. The prerequisites required for this book are basic Java and SQL skills. No prior knowledge of MyBatis is expected.

How can you bring out MySQL's full power? With High Performance MySQL, you'll learn advanced techniques for everything from designing schemas, indexes, and queries to tuning your MySQL server, operating system, and hardware to their fullest potential. This guide also teaches you safe and practical ways to scale applications through replication, load balancing, high availability, and failover.Updated to reflect recent advances in MySQL and InnoDB performance, features, and tools, this third edition not only offers specific examples of how MySQL works, it also teaches you why this system works as it does, with illustrative stories and case studies that demonstrate MySQL's principles in action. With this book, you'll learn how to think in MySQL.Learn the effects of new features in MySQL 5.5, including stored procedures, partitioned databases, triggers, and viewsImplement improvements in replication, high availability, and clusteringAchieve high performance when running MySQL in the cloudOptimize advanced querying features, such as full-text searchesTake advantage of modern multi-core CPUs and solid-state disksExplore backup and recovery strategies—including new tools for hot online backups

Data is getting bigger and more complex by the day, and so are the choices in handling that data. As a modern application developer you need to understand the emerging field of data management, both RDBMS and NoSQL. Seven Databases in Seven Weeks takes you on a tour of some of the hottest open source databases today. In the tradition of Bruce A. Tate's Seven Languages in Seven Weeks, this book goes beyond your basic tutorial to explore the essential concepts at the core each technology.Redis, Neo4J, CouchDB, MongoDB, HBase, Riak and Postgres. With each database, you'll tackle a real-world data problem that highlights the concepts and features that make it shine. You'll explore the five data models employed by these databases-relational, key/value, columnar, document and graph-and which kinds of problems are best suited to each.You'll learn how MongoDB and CouchDB are strikingly different, and discover the Dynamo heritage at the heart of Riak. Make your applications faster with Redis and more connected with Neo4J. Use MapReduce to solve Big Data problems. Build clusters of servers using scalable services like Amazon's Elastic Compute Cloud (EC2).Discover the CAP theorem and its implications for your distributed data. Understand the tradeoffs between consistency and availability, and when you can use them to your advantage. Use multiple databases in concert to create a platform that's more than the sum of its parts, or find one that meets all your needs at once. Seven Databases in Seven Weeks will take you on a deep dive into each of the databases, their strengths and weaknesses, and how to choose the ones that fit your needs.What You Need:To get the most of of this book you'll have to follow along, and that means you'll need a •nix shell (Mac OSX or Linux preferred, Windows users will need Cygwin), and Java 6 (or greater) and Ruby 1.8.7 (or greater). Each chapter will list the downloads required for that database.

SQL is full of difficulties and traps for the unwary. You can avoid them if you understand relational theory, but only if you know how to put the theory into practice. In this insightful book, author C.J. Date explains relational theory in depth, and demonstrates through numerous examples and exercises how you can apply it directly to your use of SQL.This second edition includes new material on recursive queries, “missing information” without nulls, new update operators, and topics such as aggregate operators, grouping and ungrouping, and view updating. If you have a modest-to-advanced background in SQL, you'll learn how to deal with a host of common SQL dilemmas.Why is proper column naming so important?Nulls in your database are causing you to get wrong answers. Why? What can you do about it?Is it possible to write an SQL query to find employees who have never been in the same department for more than six months at a time?SQL supports “quantified comparisons,” but they're better avoided. Why? How do you avoid them?Constraints are crucially important, but most SQL products don't support them properly. What can you do to resolve this situation?Database theory and practice have evolved since the relational model was developed more than 40 years ago. SQL and Relational Theory draws on decades of research to present the most up-to-date treatment of SQL available.C.J. Date has a stature that is unique within the database industry. A prolific writer well known for the bestselling textbook An Introduction to Database Systems (Addison-Wesley), he has an exceptionally clear style when writing about complex principles and theory.

• Provides a practical overview of the most common database management tasks for those who need to manage data

Create a MongoDB cluster that will grow to meet the needs of your application. With this short and concise book, you'll get guidelines for setting up and using clusters to store a large volume of data, and learn how to access the data efficiently. In the process, you'll understand how to make your application work with a distributed database system.Scaling MongoDB will help you:Set up a MongoDB cluster through shardingWork with a cluster to query and update dataOperate, monitor, and backup your clusterPlan your application to deal with outagesBy following the advice in this book, you'll be well on your way to building and running an efficient, predictable distributed system using MongoDB.

Manage the huMONGOus amount of data collected through your web application with MongoDB. This authoritative introduction—written by a core contributor to the project—shows you the many advantages of using document-oriented databases, and demonstrates how this reliable, high-performance system allows for almost infinite horizontal scalability.This updated second edition provides guidance for database developers, advanced configuration for system administrators, and an overview of the concepts and use cases for other people on your project. Ideal for NoSQL newcomers and experienced MongoDB users alike, this guide provides numerous real-world schema design examples.Get started with MongoDB core concepts and vocabularyPerform basic write operations at different levels of safety and speedCreate complex queries, with options for limiting, skipping, and sorting resultsDesign an application that works well with MongoDBAggregate data, including counting, finding distinct values, grouping documents, and using MapReduceGather and interpret statistics about your collections and databasesSet up replica sets and automatic failover in MongoDBUse sharding to scale horizontally, and learn how it impacts applicationsDelve into monitoring, security and authentication, backup/restore, and other administrative tasks

Harnessing Hibernate is an ideal introduction to the popular framework that lets Java developers work with information from a relational database easily and efficiently. Databases are a very different world than Java objects, and they often involve people with different skills and specializations. With Hibernate, bridging these two worlds is significantly easier, and with this book, you can get up to speed with Hibernate quickly.Rather than present you with another reference, Harnessing Hibernate lets you explore the system, from download and configuration through a series of projects that demonstrate how to accomplish a variety of practical goals. The new edition of this concise guide walks you through Hibernate's primary features, which include mapping from Java classes to database tables, and from Java data types to SQL data types. You will also learn about Hibernate's data query and retrieval facilities, and much more.By reading and following along with the examples, you can get your own Hibernate environment set up quickly and start using it for real-world tasks right away. Harnessing Hibernate teaches you how to:Perform Object/Relational mappingWork with persistent data from Java codeWork with groups and relationships between objectsExtend Hibernate's rich type support for your own needsSimplify query creation using criteria and examplesUse the Hibernate Query Language (HQL) and understand how it differs from SQLUse Hibernate in conjunction with SpringUse Hibernate in conjunction with other packages, such as the Stripes web framework and the Eclipse IDEOnce you're past the first few chapters, you can jump to topics that you find particularly interesting or relevant. All background material and explanations of how Hibernate works and why is in the service of a focused task. Source code can be downloaded from the book's website.If using SQL is an uncomfortable chore, Harnessing Hibernate offers you an effective and trouble-free method for working with the information you store in your applications.

Information Modeling and Relational Databases, Second Edition, provides an introduction to ORM (Object-Role Modeling)and much more. In fact, it is the only book to go beyond introductory coverage and provide all of the in-depth instruction you need to transform knowledge from domain experts into a sound database design. This book is intended for anyone with a stake in the accuracy and efficacy of databases: systems analysts, information modelers, database designers and administrators, and programmers. Terry Halpin, a pioneer in the development of ORM, blends conceptual information with practical instruction that will let you begin using ORM effectively as soon as possible. Supported by examples, exercises, and useful background information, his step-by-step approach teaches you to develop a natural-language-based ORM model, and then, where needed, abstract ER and UML models from it. This book will quickly make you proficient in the modeling technique that is proving vital to the development of accurate and efficient databases that best meet real business objectives. - Presents the most indepth coverage of Object-Role Modeling available anywhere, including a thorough update of the book for ORM2, as well as UML2 and E-R (Entity-Relationship) modeling - Includes clear coverage of relational database concepts, and the latest developments in SQL and XML, including a new chapter on the impact of XML on information modeling, exchange and transformation - New and improved case studies and exercises are provided for many topics

PL/SQL, Oracle's powerful procedural language, has been the cornerstone of Oracle application development for nearly 15 years. Although primarily a tool for developers, PL/SQL has also become an essential tool for database administration, as DBAs take increasing responsibility for site performance and as the lines between developers and DBAs blur.Until now, there has not been a book focused squarely on the language topics of special concern to DBAs Oracle PL/SQL for DBAs fills the gap. Covering the latest Oracle version, Oracle Database 10g Release 2 and packed with code and usage examples, it contains:A quick tour of the PL/SQL language, providing enough basic information about language fundamentals to get DBAs up and runningExtensive coverage of security topics for DBAs: Encryption (including both traditional methods and Oracle's new Transparent Data Encryption, TDE); Row-Level Security(RLS), Fine-Grained Auditing (FGA); and random value generationMethods for DBAs to improve query and database performance with cursors and table functionsCoverage of Oracle scheduling, which allows jobs such as database monitoring andstatistics gathering to be scheduled for regular executionUsing Oracle's built-in packages (DBMS_CRYPTO, DBMS_RLS, DBMS_FGA, DBMS_RANDOM,DBMS_SCHEDULING) as a base, the book describes ways of building on top of these packages to suit particular organizational needs. Authors are Arup Nanda, Oracle Magazine 2003 DBA of the Year, and Steven Feuerstein, the world's foremost PL/SQL expert and coauthor of the classic reference, Oracle PL/SQL Programming.DBAs who have not yet discovered how helpful PL/SQL can be will find this book a superb introduction to the language and its special database administration features. Even if you have used PL/SQL for years, you'll find the detailed coverage in this book to be an invaluable resource.