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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 vocabulary Perform basic write operations at different levels of safety and speed Create complex queries, with options for limiting, skipping, and sorting results Design an application that works well with MongoDB Aggregate data, including counting, finding distinct values, grouping documents, and using MapReduce Gather and interpret statistics about your collections and databases Set up replica sets and automatic failover in MongoDB Use sharding to scale horizontally, and learn how it impacts applications Delve into monitoring, security and authentication, backup/restore, and other administrative tasks
Giving comprehensive, soup-to-nuts coverage of database administration, this guide is written from a platform-independent viewpoint, emphasizing best practices.
A comprehensive guide to everything scientists need to know about data management, this book is essential for researchers who need to learn how to organize, document and take care of their own data. Researchers in all disciplines are faced with the challenge of managing the growing amounts of digital data that are the foundation of their research. Kristin Briney offers practical advice and clearly explains policies and principles, in an accessible and in-depth text that will allow researchers to understand and achieve the goal of better research data management. Data Management for Researchers includes sections on: * The data problem – an introduction to the growing importance and challenges of using digital data in research. Covers both the inherent problems with managing digital information, as well as how the research landscape is changing to give more value to research datasets and code. * The data lifecycle – a framework for data’s place within the research process and how data’s role is changing. Greater emphasis on data sharing and data reuse will not only change the way we conduct research but also how we manage research data. * Planning for data management – covers the many aspects of data management and how to put them together in a data management plan. This section also includes sample data management plans. * Documenting your data – an often overlooked part of the data management process, but one that is critical to good management; data without documentation are frequently unusable. * Organizing your data – explains how to keep your data in order using organizational systems and file naming conventions. This section also covers using a database to organize and analyze content. * Improving data analysis – covers managing information through the analysis process. This section starts by comparing the management of raw and analyzed data and then describes ways to make analysis easier, such as spreadsheet best practices. It also examines practices for research code, including version control systems. * Managing secure and private data – many researchers are dealing with data that require extra security. This section outlines what data falls into this category and some of the policies that apply, before addressing the best practices for keeping data secure. * Short-term storage – deals with the practical matters of storage and backup and covers the many options available. This section also goes through the best practices to insure that data are not lost. * Preserving and archiving your data – digital data can have a long life if properly cared for. This section covers managing data in the long term including choosing good file formats and media, as well as determining who will manage the data after the end of the project. * Sharing/publishing your data – addresses how to make data sharing across research groups easier, as well as how and why to publicly share data. This section covers intellectual property and licenses for datasets, before ending with the altmetrics that measure the impact of publicly shared data. * Reusing data – as more data are shared, it becomes possible to use outside data in your research. This chapter discusses strategies for finding datasets and lays out how to cite data once you have found it. This book is designed for active scientific researchers but it is useful for anyone who wants to get more from their data: academics, educators, professionals or anyone who teaches data management, sharing and preservation. "An excellent practical treatise on the art and practice of data management, this book is essential to any researcher, regardless of subject or discipline." —Robert Buntrock, Chemical Information Bulletin
Object storage is the primary storage solution that is used in the cloud and on-premises solutions as a central storage platform for unstructured data. IBM Cloud Object Storage is a software-defined storage (SDS) platform that breaks down barriers for storing massive amounts of data by optimizing the placement of data on commodity x86 servers across the enterprise. This IBM Redbooks® publication describes the major features, use case scenarios, deployment options, configuration details, initial customization, performance, and scalability considerations of IBM Cloud Object Storage on-premises offering. For more information about the IBM Cloud Object Storage architecture and technology that is behind the product, see IBM Cloud Object Storage Concepts and Architecture , REDP-5537. The target audience for this publication is IBM Cloud Object Storage IT specialists and storage administrators.
Every enterprise application creates data, whether it’s log messages, metrics, user activity, outgoing messages, or something else. And how to move all of this data becomes nearly as important as the data itself. If you’re an application architect, developer, or production engineer new to Apache Kafka, this practical guide shows you how to use this open source streaming platform to handle real-time data feeds. Engineers from Confluent and LinkedIn who are responsible for developing Kafka explain how to deploy production Kafka clusters, write reliable event-driven microservices, and build scalable stream-processing applications with this platform. Through detailed examples, you’ll learn Kafka’s design principles, reliability guarantees, key APIs, and architecture details, including the replication protocol, the controller, and the storage layer. Understand publish-subscribe messaging and how it fits in the big data ecosystem. Explore Kafka producers and consumers for writing and reading messages Understand Kafka patterns and use-case requirements to ensure reliable data delivery Get best practices for building data pipelines and applications with Kafka Manage Kafka in production, and learn to perform monitoring, tuning, and maintenance tasks Learn the most critical metrics among Kafka’s operational measurements Explore how Kafka’s stream delivery capabilities make it a perfect source for stream processing systems
Managing data continues to grow as a necessity for modern organizations. There are seemingly infinite opportunities for organic growth, reduction of costs, and creation of new products and services. It has become apparent that none of these opportunities can happen smoothly without data governance. The cost of exponential data growth and privacy / security concerns are becoming burdensome. Organizations will encounter unexpected consequences in new sources of risk. The solution to these challenges is also data governance; ensuring balance between risk and opportunity. Data Governance, Second Edition, is for any executive, manager or data professional who needs to understand or implement a data governance program. It is required to ensure consistent, accurate and reliable data across their organization. This book offers an overview of why data governance is needed, how to design, initiate, and execute a program and how to keep the program sustainable. This valuable resource provides comprehensive guidance to beginning professionals, managers or analysts looking to improve their processes, and advanced students in Data Management and related courses. With the provided framework and case studies all professionals in the data governance field will gain key insights into launching successful and money-saving data governance program. - Incorporates industry changes, lessons learned and new approaches - Explores various ways in which data analysts and managers can ensure consistent, accurate and reliable data across their organizations - Includes new case studies which detail real-world situations - Explores all of the capabilities an organization must adopt to become data driven - Provides guidance on various approaches to data governance, to determine whether an organization should be low profile, central controlled, agile, or traditional - Provides guidance on using technology and separating vendor hype from sincere delivery of necessary capabilities - Offers readers insights into how their organizations can improve the value of their data, through data quality, data strategy and data literacy - Provides up to 75% brand-new content compared to the first edition
Complete Guide to Indian Railways RRB Group D Level 1 Exam 2019 - English Edition covers the complete syllabus as per the latest notification. The book provides complete preparatory theory and practice exercises with solutions. The book has been divided into 4 sections - Mathematics, General Intelligence & Reasoning, General Science & General Awareness. The book also provides Latest Current Affairs.
Use Microsoft SQL Server 2019 to implement, administer, and secure a robust database solution that is disaster-proof and highly available Key FeaturesExplore new features of SQL Server 2019 to set up, administer, and maintain your database solution successfullyDevelop a dynamic SQL Server environment and streamline big data pipelinesDiscover best practices for fixing performance issues, database access management, replication, and securityBook Description SQL Server is one of the most popular relational database management systems developed by Microsoft. This second edition of the SQL Server Administrator's Guide will not only teach you how to administer an enterprise database, but also help you become proficient at managing and keeping the database available, secure, and stable. You’ll start by learning how to set up your SQL Server and configure new and existing environments for optimal use. The book then takes you through designing aspects and delves into performance tuning by showing you how to use indexes effectively. You’ll understand certain choices that need to be made about backups, implement security policy, and discover how to keep your environment healthy. Tools available for monitoring and managing a SQL Server database, including automating health reviews, performance checks, and much more, will also be discussed in detail. As you advance, the book covers essential topics such as migration, upgrading, and consolidation, along with the techniques that will help you when things go wrong. Once you’ve got to grips with integration with Azure and streamlining big data pipelines, you’ll learn best practices from industry experts for maintaining a highly reliable database solution. Whether you are an administrator or are looking to get started with database administration, this SQL Server book will help you develop the skills you need to successfully create, design, and deploy database solutions. What you will learnDiscover SQL Server 2019’s new features and how to implement themFix performance issues by optimizing queries and making use of indexesDesign and use an optimal database management strategyCombine SQL Server 2019 with Azure and manage your solution using various automation techniquesImplement efficient backup and recovery techniques in line with security policiesGet to grips with migrating, upgrading, and consolidating with SQL ServerSet up an AlwaysOn-enabled stable and fast SQL Server 2019 environmentUnderstand how to work with Big Data on SQL Server environmentsWho this book is for This book is for database administrators, database developers, and anyone who wants to administer large and multiple databases single-handedly using Microsoft's SQL Server 2019. Basic awareness of database concepts and experience with previous SQL Server versions is required.
With their rapidly changing architecture and API-driven automation, cloud platforms come with unique security challenges and opportunities. This hands-on book guides you through security best practices for multivendor cloud environments, whether your company plans to move legacy on-premises projects to the cloud or build a new infrastructure from the ground up. Developers, IT architects, and security professionals will learn cloud-specific techniques for securing popular cloud platforms such as Amazon Web Services, Microsoft Azure, and IBM Cloud. Chris Dotson—an IBM senior technical staff member—shows you how to establish data asset management, identity and access management, vulnerability management, network security, and incident response in your cloud environment.
Manage your data with a system designed to support modern application development. Updated for MongoDB 4.2, the third edition of this authoritative and accessible guide shows you the advantages of using document-oriented databases. You’ll learn how this secure, high-performance system enables flexible data models, high availability, and horizontal scalability. Authors Shannon Bradshaw, Eoin Brazil, and Kristina Chodorow provide guidance for database developers, advanced configuration for system administrators, and use cases for a variety of projects. NoSQL newcomers and experienced MongoDB users will find updates on querying, indexing, aggregation, transactions, replica sets, ops management, sharding and data administration, durability, monitoring, and security. In six parts, this book shows you how to: Work with MongoDB, perform write operations, find documents, and create complex queries Index collections, aggregate data, and use transactions for your application Configure a local replica set and learn how replication interacts with your application Set up cluster components and choose a shard key for a variety of applications Explore aspects of application administration and configure authentication and authorization Use stats when monitoring, back up and restore deployments, and use system settings when deploying MongoDB