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| data management databases and organizations: Data Management Richard T. Watson, 2004 PART I: THE MANAGERIAL PERSPECTIVE. Managing Data. Information. PART II: DATA MODELING AND SQL. The Single Entity. The One-to-Many Relationship. The Many-to-Many Relationship. One-to-One and Recursive Relationships. Data Modeling. Normalization and Other Data Modeling Methods. The Relational Model and Relational Algebra. SQL. PART III: DATABASE ARCHITECTURES AND IMPLEMENTATIONS. Data Structure and Storage. Data Processing Architectures. Object-Oriented Data Management. Spatial and Temporal Data Management. PART IV: ORGANIZATIONAL MEMORY TECHNOLOGIES. Organizational Intelligence Technologies. The Web and Data Management. XML: Managing Data Exchange. PART V: MANAGING ORGANIZTIONAL MEMORY. Data Integrity. Data Administration. U-Commerce and Data Management. Photo Credits. Index. |
| data management databases and organizations: Data Management Richard T. Watson, 2005-08-26 Updated with the latest developments in the field, the Fifth Edition will help you design and create relational databases, formulate complex SQL queries, understand OLAP, use SQL with Java, learn how to use XML, and prepare yourself for the real world of data management.--Jacket. |
| data management databases and organizations: Data Management Richard Watson, 2022-10-05 |
| data management databases and organizations: Database Management Richard T. Watson, 1996 Complete coverage of database management with the correct balance of business and technical material for the MIS professional. This book covers the technical aspects of database design and implementation, with an equal emphasis on the why and how of the management of databases, and the managerial uses and philosophy behind databases. |
| data management databases and organizations: Databases for Small Business Anna Manning, 2015-11-21 This book covers the practical aspects of database design, data cleansing, data analysis, and data protection, among others. The focus is on what you really need to know to create the right database for your small business and to leverage it most effectively to spur growth and revenue. Databases for Small Business is a practical handbook for entrepreneurs, managers, staff, and professionals in small organizations who are not IT specialists but who recognize the need to ramp up their small organizations’ use of data and to round out their own business expertise and office skills with basic database proficiency. Anna Manning—a data scientist who has worked on database design and data analysis in a computer science university research lab, her own small business, and a nonprofit—walks you through the progression of steps that will enable you to extract actionable intelligence and maximum value from your business data in terms of marketing, sales, customer relations, decision making, and business strategy. Dr. Manning illustrates the steps in the book with four running case studies of a small online business, an engineering startup, a small legal firm, and a nonprofit organization. Databases for Small Business teaches non-techie entrepreneurs and professionals how to: Design a small business database from scratch Extract the maximum profit from your data Follow guidance on data protection law Effectively use data collection and data cleansing techniques Train staff to leverage your data |
| data management databases and organizations: Data Management , 2015-08-28 |
| data management databases and organizations: DATA MANAGEMENT, DATABASES AND ORGANIZATIONS, 3RD ED Richard T. Watson, 2008 Market_Desc: · Database Designers · SQL Programmers Special Features: · Includes sections on UML for data modeling, server-side scripting (PHP) for linking a database to Web server, XML, data warehousing, OLAP, and data mining About The Book: Twice recognized as one of the top ten most productive MIS researchers, Watson provides a balanced treatment of the technical and business sides of managing data. Management of data has never been more critical for organizations of any size. This book discusses the technical aspects of database design and implementation as well as the why and how of the management of databases, and the managerial issues and business philosophy behind databases. |
| data management databases and organizations: Management of Heterogeneous and Autonomous Database Systems Ahmed K. Elmagarmid, Marek Rusinkiewicz, Amit Sheth, 1999 An Overview of Multidatabase Systems: Past and Present / Athman Bouguettaya, Boualem Benatallah, Ahmed Elmagarmid / - Local Autonomy and Its Effects on Multidatabase Systems / Ahmed Elmagarmid, Weimin Du, Rafi Ahmed / - Semantic Similarities Between Objects in Multiple Databases / Vipul Kashyap, Amit Sheth / - Resolution of Representational Diversity in Multidatabase Systems / Joachim Hammer, Dennis McLeod / - Schema Integration: Past, Present, and Future / Sudha Ram, V. Ramesh / - Schema and Language Translation / Bogdan Czejdo, Le Gruenwald / - Multidatabase Languages / Paolo Missier, Marek Rusinkiewicz, W. Jin / - Interdependent Database Systems / George Karabatis, Marek Rusinkiewicz, Amit Sheth / - Correctness Criteria and Concurrency Control / Panos K. Chrysanthis, Krithi Ramamritham / - Transaction Management in Multidatabase Systems: Current Technologies and Formalisms / Ken Barker, Ahmed Elmagarmid / - Transaction-Based Recovery / Jari Veijalainen. ... |
| data management databases and organizations: Principles of Database Management Wilfried Lemahieu, Seppe vanden Broucke, Bart Baesens, 2018-07-12 Introductory, theory-practice balanced text teaching the fundamentals of databases to advanced undergraduates or graduate students in information systems or computer science. |
| data management databases and organizations: XML Data Management Akmal B. Chaudhri, Awais Rashid, Roberto Zicari, 2003 In this book, you will find discussions on the newest native XML databases, along with information on working with XML-enabled relational database systems. In addition, XML Data Management thoroughly examines benchmarks and analysis techniques for performance of XML databases. This book is best used by students that are knowledgeable in database technology and are familiar with XML. |
| data management databases and organizations: Data Management at Scale Piethein Strengholt, 2020-07-29 As data management and integration continue to evolve rapidly, storing all your data in one place, such as a data warehouse, is no longer scalable. In the very near future, data will need to be distributed and available for several technological solutions. With this practical book, you’ll learnhow to migrate your enterprise from a complex and tightly coupled data landscape to a more flexible architecture ready for the modern world of data consumption. Executives, data architects, analytics teams, and compliance and governance staff will learn how to build a modern scalable data landscape using the Scaled Architecture, which you can introduce incrementally without a large upfront investment. Author Piethein Strengholt provides blueprints, principles, observations, best practices, and patterns to get you up to speed. Examine data management trends, including technological developments, regulatory requirements, and privacy concerns Go deep into the Scaled Architecture and learn how the pieces fit together Explore data governance and data security, master data management, self-service data marketplaces, and the importance of metadata |
| data management databases and organizations: Data Management Watson, 2013-02-01 |
| data management databases and organizations: Data Management Watson, Richard T Watson, 2001-08-24 Includes sections on UML for data modeling, server-side scripting (PHP) for linking a database to Web server, XML, data warehousing, OLAP, and data mining. Contains useful reference sections, with deep coverage of data modeling and SQL, that will help information systems professionals throughout their careers. Broader than most database books, thus providing a more managerial outlook. |
| data management databases and organizations: DAMA-DMBOK Dama International, 2017 Defining a set of guiding principles for data management and describing how these principles can be applied within data management functional areas; Providing a functional framework for the implementation of enterprise data management practices; including widely adopted practices, methods and techniques, functions, roles, deliverables and metrics; Establishing a common vocabulary for data management concepts and serving as the basis for best practices for data management professionals. DAMA-DMBOK2 provides data management and IT professionals, executives, knowledge workers, educators, and researchers with a framework to manage their data and mature their information infrastructure, based on these principles: Data is an asset with unique properties; The value of data can be and should be expressed in economic terms; Managing data means managing the quality of data; It takes metadata to manage data; It takes planning to manage data; Data management is cross-functional and requires a range of skills and expertise; Data management requires an enterprise perspective; Data management must account for a range of perspectives; Data management is data lifecycle management; Different types of data have different lifecycle requirements; Managing data includes managing risks associated with data; Data management requirements must drive information technology decisions; Effective data management requires leadership commitment. |
| data management databases and organizations: In-Memory Data Management Hasso Plattner, Alexander Zeier, 2012-04-17 In the last fifty years the world has been completely transformed through the use of IT. We have now reached a new inflection point. This book presents, for the first time, how in-memory data management is changing the way businesses are run. Today, enterprise data is split into separate databases for performance reasons. Multi-core CPUs, large main memories, cloud computing and powerful mobile devices are serving as the foundation for the transition of enterprises away from this restrictive model. This book provides the technical foundation for processing combined transactional and analytical operations in the same database. In the year since we published the first edition of this book, the performance gains enabled by the use of in-memory technology in enterprise applications has truly marked an inflection point in the market. The new content in this second edition focuses on the development of these in-memory enterprise applications, showing how they leverage the capabilities of in-memory technology. The book is intended for university students, IT-professionals and IT-managers, but also for senior management who wish to create new business processes. |
| data management databases and organizations: Journal of Database Management ( Vol 23 ISS 1) Keng Siau, 2011-12 |
| data management databases and organizations: A Primer in Financial Data Management Martijn Groot, 2017-05-10 A Primer in Financial Data Management describes concepts and methods, considering financial data management, not as a technological challenge, but as a key asset that underpins effective business management. This broad survey of data management in financial services discusses the data and process needs from the business user, client and regulatory perspectives. Its non-technical descriptions and insights can be used by readers with diverse interests across the financial services industry. The need has never been greater for skills, systems, and methodologies to manage information in financial markets. The volume of data, the diversity of sources, and the power of the tools to process it massively increased. Demands from business, customers, and regulators on transparency, safety, and above all, timely availability of high quality information for decision-making and reporting have grown in tandem, making this book a must read for those working in, or interested in, financial management. - Focuses on ways information management can fuel financial institutions' processes, including regulatory reporting, trade lifecycle management, and customer interaction - Covers recent regulatory and technological developments and their implications for optimal financial information management - Views data management from a supply chain perspective and discusses challenges and opportunities, including big data technologies and regulatory scrutiny |
| data management databases and organizations: Effective Big Data Management and Opportunities for Implementation Singh, Manoj Kumar, G., Dileep Kumar, 2016-06-20 “Big data” has become a commonly used term to describe large-scale and complex data sets which are difficult to manage and analyze using standard data management methodologies. With applications across sectors and fields of study, the implementation and possible uses of big data are limitless. Effective Big Data Management and Opportunities for Implementation explores emerging research on the ever-growing field of big data and facilitates further knowledge development on methods for handling and interpreting large data sets. Providing multi-disciplinary perspectives fueled by international research, this publication is designed for use by data analysts, IT professionals, researchers, and graduate-level students interested in learning about the latest trends and concepts in big data. |
| data management databases and organizations: Web Data Management Serge Abiteboul, Ioana Manolescu, Philippe Rigaux, Marie-Christine Rousset, Pierre Senellart, 2011-11-28 The Internet and World Wide Web have revolutionized access to information. Users now store information across multiple platforms from personal computers to smartphones and websites. As a consequence, data management concepts, methods and techniques are increasingly focused on distribution concerns. Now that information largely resides in the network, so do the tools that process this information. This book explains the foundations of XML with a focus on data distribution. It covers the many facets of distributed data management on the Web, such as description logics, that are already emerging in today's data integration applications and herald tomorrow's semantic Web. It also introduces the machinery used to manipulate the unprecedented amount of data collected on the Web. Several 'Putting into Practice' chapters describe detailed practical applications of the technologies and techniques. The book will serve as an introduction to the new, global, information systems for Web professionals and master's level courses. |
| data management databases and organizations: Information-Driven Business Robert Hillard, 2010-08-23 Information doesn't just provide a window on the business, increasingly it is the business. The global economy is moving from products to services which are described almost entirely electronically. Even those businesses that are traditionally associated with making things are less concerned with managing the manufacturing process (which is largely outsourced) than they are with maintaining their intellectual property. Information-Driven Business helps you to understand this change and find the value in your data. Hillard explains techniques that organizations can use and how businesses can apply them immediately. For example, simple changes to the way data is described will let staff support their customers much more quickly; and two simple measures let executives know whether they will be able to use the content of a database before it is even built. This book provides the foundation on which analytical and data rich organizations can be created. Innovative and revealing, this book provides a robust description of Information Management theory and how you can pragmatically apply it to real business problems, with almost instant benefits. Information-Driven Business comprehensively tackles the challenge of managing information, starting with why information has become important and how it is encoded, through to how to measure its use. |
| data management databases and organizations: Access Control for Databases Elisa Bertino, Gabriel Ghinita, Ashish Kamra, 2011-02 A comprehensive survey of the foundational models and recent research trends in access control models and mechanisms for database management systems. |
| data management databases and organizations: Information Systems for Business and Beyond David T. Bourgeois, 2014 Information Systems for Business and Beyond introduces the concept of information systems, their use in business, and the larger impact they are having on our world.--BC Campus website. |
| data management databases and organizations: Encyclopedia of Database Technologies and Applications Rivero, Laura C., Doorn, Jorge Horacio, Ferraggine, Viviana E., 2005-06-30 Addresses the evolution of database management, technologies and applications along with the progress and endeavors of new research areas.--P. xiii. |
| data management databases and organizations: Data Architecture Charles Tupper, 2011-05-09 Data Architecture: From Zen to Reality explains the principles underlying data architecture, how data evolves with organizations, and the challenges organizations face in structuring and managing their data. Using a holistic approach to the field of data architecture, the book describes proven methods and technologies to solve the complex issues dealing with data. It covers the various applied areas of data, including data modelling and data model management, data quality, data governance, enterprise information management, database design, data warehousing, and warehouse design. This text is a core resource for anyone customizing or aligning data management systems, taking the Zen-like idea of data architecture to an attainable reality. The book presents fundamental concepts of enterprise architecture with definitions and real-world applications and scenarios. It teaches data managers and planners about the challenges of building a data architecture roadmap, structuring the right team, and building a long term set of solutions. It includes the detail needed to illustrate how the fundamental principles are used in current business practice. The book is divided into five sections, one of which addresses the software-application development process, defining tools, techniques, and methods that ensure repeatable results. Data Architecture is intended for people in business management involved with corporate data issues and information technology decisions, ranging from data architects to IT consultants, IT auditors, and data administrators. It is also an ideal reference tool for those in a higher-level education process involved in data or information technology management. - Presents fundamental concepts of enterprise architecture with definitions and real-world applications and scenarios - Teaches data managers and planners about the challenges of building a data architecture roadmap, structuring the right team, and building a long term set of solutions - Includes the detail needed to illustrate how the fundamental principles are used in current business practice |
| data management databases and organizations: The DAMA Dictionary of Data Management Dama International, 2011 A glossary of over 2,000 terms which provides a common data management vocabulary for IT and Business professionals, and is a companion to the DAMA Data Management Body of Knowledge (DAMA-DMBOK). Topics include: Analytics & Data Mining Architecture Artificial Intelligence Business Analysis DAMA & Professional Development Databases & Database Design Database Administration Data Governance & Stewardship Data Management Data Modeling Data Movement & Integration Data Quality Management Data Security Management Data Warehousing & Business Intelligence Document, Record & Content Management Finance & Accounting Geospatial Data Knowledge Management Marketing & Customer Relationship Management Meta-Data Management Multi-dimensional & OLAP Normalization Object-Orientation Parallel Database Processing Planning Process Management Project Management Reference & Master Data Management Semantic Modeling Software Development Standards Organizations Structured Query Language (SQL) XML Development |
| data management databases and organizations: Enterprise Master Data Management Allen Dreibelbis, Eberhard Hechler, Ivan Milman, Martin Oberhofer, Paul van Run, Dan Wolfson, 2008-06-05 The Only Complete Technical Primer for MDM Planners, Architects, and Implementers Companies moving toward flexible SOA architectures often face difficult information management and integration challenges. The master data they rely on is often stored and managed in ways that are redundant, inconsistent, inaccessible, non-standardized, and poorly governed. Using Master Data Management (MDM), organizations can regain control of their master data, improve corresponding business processes, and maximize its value in SOA environments. Enterprise Master Data Management provides an authoritative, vendor-independent MDM technical reference for practitioners: architects, technical analysts, consultants, solution designers, and senior IT decisionmakers. Written by the IBM ® data management innovators who are pioneering MDM, this book systematically introduces MDM’s key concepts and technical themes, explains its business case, and illuminates how it interrelates with and enables SOA. Drawing on their experience with cutting-edge projects, the authors introduce MDM patterns, blueprints, solutions, and best practices published nowhere else—everything you need to establish a consistent, manageable set of master data, and use it for competitive advantage. Coverage includes How MDM and SOA complement each other Using the MDM Reference Architecture to position and design MDM solutions within an enterprise Assessing the value and risks to master data and applying the right security controls Using PIM-MDM and CDI-MDM Solution Blueprints to address industry-specific information management challenges Explaining MDM patterns as enablers to accelerate consistent MDM deployments Incorporating MDM solutions into existing IT landscapes via MDM Integration Blueprints Leveraging master data as an enterprise asset—bringing people, processes, and technology together with MDM and data governance Best practices in MDM deployment, including data warehouse and SAP integration |
| data management databases and organizations: In-Memory Data Management Hasso Plattner, Alexander Zeier, 2011-03-08 In the last 50 years the world has been completely transformed through the use of IT. We have now reached a new inflection point. Here we present, for the first time, how in-memory computing is changing the way businesses are run. Today, enterprise data is split into separate databases for performance reasons. Analytical data resides in warehouses, synchronized periodically with transactional systems. This separation makes flexible, real-time reporting on current data impossible. Multi-core CPUs, large main memories, cloud computing and powerful mobile devices are serving as the foundation for the transition of enterprises away from this restrictive model. We describe techniques that allow analytical and transactional processing at the speed of thought and enable new ways of doing business. The book is intended for university students, IT-professionals and IT-managers, but also for senior management who wish to create new business processes by leveraging in-memory computing. |
| data management databases and organizations: Effective Databases for Text & Document Management Shirley A. Becker, 2003-01-01 Focused on the latest research on text and document management, this guide addresses the information management needs of organizations by providing the most recent findings. How the need for effective databases to house information is impacting organizations worldwide and how some organizations that possess a vast amount of data are not able to use the data in an economic and efficient manner is demonstrated. A taxonomy for object-oriented databases, metrics for controlling database complexity, and a guide to accommodating hierarchies in relational databases are provided. Also covered is how to apply Java-triggers for X-Link management and how to build signatures. |
| data management databases and organizations: NoSQL Distilled Pramod J. Sadalage, Martin Fowler, 2013 'NoSQL Distilled' is designed to provide you with enough background on how NoSQL databases work, so that you can choose the right data store without having to trawl the whole web to do it. It won't answer your questions definitively, but it should narrow down the range of options you have to consider. |
| data management databases and organizations: Quality Management and Accreditation in Hematopoietic Stem Cell Transplantation and Cellular Therapy Mahmoud Aljurf, John A. Snowden, Patrick Hayden, Kim H. Orchard, Eoin McGrath, 2021-02-19 This open access book provides a concise yet comprehensive overview on how to build a quality management program for hematopoietic stem cell transplantation (HSCT) and cellular therapy. The text reviews all the essential steps and elements necessary for establishing a quality management program and achieving accreditation in HSCT and cellular therapy. Specific areas of focus include document development and implementation, audits and validation, performance measurement, writing a quality management plan, the accreditation process, data management, and maintaining a quality management program. Written by experts in the field, Quality Management and Accreditation in Hematopoietic Stem Cell Transplantation and Cellular Therapy: A Practical Guide is a valuable resource for physicians, healthcare professionals, and laboratory staff involved in the creation and maintenance of a state-of-the-art HSCT and cellular therapy program. |
| data management databases and organizations: Valuepack Thomas Connolly, 2005-08-01 |
| data management databases and organizations: Design Patterns for Cloud Native Applications Kasun Indrasiri, Sriskandarajah Suhothayan, 2021-05-17 With the immense cost savings and scalability the cloud provides, the rationale for building cloud native applications is no longer in question. The real issue is how. With this practical guide, developers will learn about the most commonly used design patterns for building cloud native applications using APIs, data, events, and streams in both greenfield and brownfield development. You'll learn how to incrementally design, develop, and deploy large and effective cloud native applications that you can manage and maintain at scale with minimal cost, time, and effort. Authors Kasun Indrasiri and Sriskandarajah Suhothayan highlight use cases that effectively demonstrate the challenges you might encounter at each step. Learn the fundamentals of cloud native applications Explore key cloud native communication, connectivity, and composition patterns Learn decentralized data management techniques Use event-driven architecture to build distributed and scalable cloud native applications Explore the most commonly used patterns for API management and consumption Examine some of the tools and technologies you'll need for building cloud native systems |
| data management databases and organizations: MASTER DATA MANAGEMENT AND DATA GOVERNANCE, 2/E Alex Berson, Larry Dubov, 2010-12-06 The latest techniques for building a customer-focused enterprise environment The authors have appreciated that MDM is a complex multidimensional area, and have set out to cover each of these dimensions in sufficient detail to provide adequate practical guidance to anyone implementing MDM. While this necessarily makes the book rather long, it means that the authors achieve a comprehensive treatment of MDM that is lacking in previous works. -- Malcolm Chisholm, Ph.D., President, AskGet.com Consulting, Inc. Regain control of your master data and maintain a master-entity-centric enterprise data framework using the detailed information in this authoritative guide. Master Data Management and Data Governance, Second Edition provides up-to-date coverage of the most current architecture and technology views and system development and management methods. Discover how to construct an MDM business case and roadmap, build accurate models, deploy data hubs, and implement layered security policies. Legacy system integration, cross-industry challenges, and regulatory compliance are also covered in this comprehensive volume. Plan and implement enterprise-scale MDM and Data Governance solutions Develop master data model Identify, match, and link master records for various domains through entity resolution Improve efficiency and maximize integration using SOA and Web services Ensure compliance with local, state, federal, and international regulations Handle security using authentication, authorization, roles, entitlements, and encryption Defend against identity theft, data compromise, spyware attack, and worm infection Synchronize components and test data quality and system performance |
| data management databases and organizations: Database Technologies: Concepts, Methodologies, Tools, and Applications Erickson, John, 2009-02-28 This reference expands the field of database technologies through four-volumes of in-depth, advanced research articles from nearly 300 of the world's leading professionals--Provided by publisher. |
| data management databases and organizations: Readings in Database Systems Joseph M. Hellerstein, Michael Stonebraker, 2005 The latest edition of a popular text and reference on database research, with substantial new material and revision; covers classical literature and recent hot topics. Lessons from database research have been applied in academic fields ranging from bioinformatics to next-generation Internet architecture and in industrial uses including Web-based e-commerce and search engines. The core ideas in the field have become increasingly influential. This text provides both students and professionals with a grounding in database research and a technical context for understanding recent innovations in the field. The readings included treat the most important issues in the database area--the basic material for any DBMS professional. This fourth edition has been substantially updated and revised, with 21 of the 48 papers new to the edition, four of them published for the first time. Many of the sections have been newly organized, and each section includes a new or substantially revised introduction that discusses the context, motivation, and controversies in a particular area, placing it in the broader perspective of database research. Two introductory articles, never before published, provide an organized, current introduction to basic knowledge of the field; one discusses the history of data models and query languages and the other offers an architectural overview of a database system. The remaining articles range from the classical literature on database research to treatments of current hot topics, including a paper on search engine architecture and a paper on application servers, both written expressly for this edition. The result is a collection of papers that are seminal and also accessible to a reader who has a basic familiarity with database systems. |
| data management databases and organizations: Smarter Modeling of IBM InfoSphere Master Data Management Solutions Jan-Bernd Bracht, Joerg Rehr, Markus Siebert, Rouven Thimm, IBM Redbooks, 2012-08-09 This IBM® Redbooks® publication presents a development approach for master data management projects, and in particular, those projects based on IBM InfoSphere® MDM Server. The target audience for this book includes Enterprise Architects, Information, Integration and Solution Architects and Designers, Developers, and Product Managers. Master data management combines a set of processes and tools that defines and manages the non-transactional data entities of an organization. Master data management can provide processes for collecting, consolidating, persisting, and distributing this data throughout an organization. IBM InfoSphere Master Data Management Server creates trusted views of master data that can improve applications and business processes. You can use it to gain control over business information by managing and maintaining a complete and accurate view of master data. You also can use InfoSphere MDM Server to extract maximum value from master data by centralizing multiple data domains. InfoSphere MDM Server provides a comprehensive set of prebuilt business services that support a full range of master data management functionality. |
| data management databases and organizations: Database Transaction Models for Advanced Applications Ahmed K. Elmagarmid, 1992-04 This collection offers the reader a broad survey of the role of transaction processing in advanced computer applications. It contains an introduction to traditional transaction technology, and comprehensive descriptions of commercial systems and research projects. This volume will help anyone interested in keeping up with database applications and the potential for transaction processing systems to address the needs of OLTP, CAD, CASE, computer aided publishing, heterogeneous databases, active databases, communications, systems and other areas. For researchers, managers, software developers, professionals in the data processing fields, or anyone interested in a coherent overview of this new and fast growing area of computer science. |
| data management databases and organizations: Database Management Systems Raghu Ramakrishnan, Johannes Gehrke, 2000 Database Management Systems provides comprehensive and up-to-date coverage of the fundamentals of database systems. Coherent explanations and practical examples have made this one of the leading texts in the field. The third edition continues in this tradition, enhancing it with more practical material. The new edition has been reorganized to allow more flexibility in the way the course is taught. Now, instructors can easily choose whether they would like to teach a course which emphasizes database application development or a course that emphasizes database systems issues. New overview chapters at the beginning of parts make it possible to skip other chapters in the part if you don't want the detail. More applications and examples have been added throughout the book, including SQL and Oracle examples. The applied flavor is further enhanced by the two new database applications chapters. |
| data management databases and organizations: Management Information Systems Kenneth C. Laudon, Jane Price Laudon, 2004 Management Information Systems provides comprehensive and integrative coverage of essential new technologies, information system applications, and their impact on business models and managerial decision-making in an exciting and interactive manner. The twelfth edition focuses on the major changes that have been made in information technology over the past two years, and includes new opening, closing, and Interactive Session cases. |
| data management databases and organizations: Cloud Database Development and Management Lee Chao, 2013-07-26 Although today’s job market requires IT professionals to understand cloud computing theories and have hands-on skills for developing real-world database systems, there are few books available that integrate coverage of both. Filling this void, Cloud Database Development and Management explains how readers can take advantage of the cloud environment to develop their own fully functioning database systems without any additional investment in IT infrastructure. Filled with step-by-step instructions, examples, and hands-on projects, the book begins by providing readers with the required foundation in database systems and cloud-based database development tools. It supplies detailed instructions on setting up data storage on Windows Azure and also explains how readers can develop their own virtual machines with Windows Server 2012 as the guest operating system. The book’s wide-ranging coverage includes database design, database implementation, database deployment to the cloud environment, SQL Database, Table Storage service, Blob Storage service, Queue Storage service, and database application development. The text deals with all three aspects of database design: conceptual design, logical design, and physical design. It introduces the SQL language, explains how to use SQL to create database objects, and introduces the migration of the database between Windows Azure and the on-premises SQL Server. It also discusses the management tasks that keep both SQL Database and Windows Azure running smoothly. Detailing how to design, implement, and manage database systems in the cloud, the book provides you with tools that can make your cloud database development much more efficient and flexible. Its easy-to-follow instructions will help you develop the hands-on skills needed to store and manage critical business information and to make that data available anytime through the Internet. |
Contents
key resource for modern organizations. It is a critical input to managerial tasks. Because managers need high-quality information to manage change in a turbulent, global environment, many …
Data Management Databases And Organizations
1. What is the optimal balance between cloud-based and on-premise data management solutions? The optimal balance depends on specific organizational needs, security requirements, and …
Data Management Databases And Organizations (book)
1. What is the optimal balance between cloud-based and on-premise data management solutions? The optimal balance depends on specific organizational needs, security requirements, and …
Data Management Databases And Organizations
Data Management Databases And Organizations [PDF] Data management databases are specialized systems designed to handle vast amounts of structured and unstructured data. These systems …
The evolution of Data Management A practitioner’s perspective
It all boils down to data management – having a suitable data architecture to meet the needs of the organization backed by a data driven business culture. In this e-book, we review the changes we …
THE ROLE OF DATABASE MANAGEMENT SYSTEM (DBMS) IN …
database management system (DBMS) is a software tool that makes it possible to organize data in a database. Within an organization, the. development of the database is typically controlled by …
Data Management Databases And Organizations (book)
Data Management Databases And Organizations [PDF] Management of data has never been more critical for organizations of any size. This book discusses the technical aspects of database …
Trends in Data Management - DATAVERSITY
DATAVERSITY’s 2022 Trends in Data Management Report ofers insights about the directions and concerns businesses have as Data Management continues to evolve. The overall structure and …
What is Data Management and Why is it Important? - TechTarget
Effective data management is a crucial piece of deploying the IT systems that run business applications and provide analytical information to help drive operational decision-making and …
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data Management of data has never been more critical for organizations of any size This book discusses the technical aspects of database design and implementation as well as the why and …
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Data Management Databases And Organizations [PDF] Data management databases are specialized systems designed to handle vast amounts of structured and unstructured data. These systems …
Data Management Databases And Organizations
implementation of enterprise data management practices; including widely adopted practices, methods and techniques, functions, roles, deliverables and metrics; Establishing a common …
Contents
key resource for modern organizations. It is a critical input to managerial tasks. Because managers need high-quality information to manage change in a turbulent, global environment, …
Data Management Databases And Organizations
1. What is the optimal balance between cloud-based and on-premise data management solutions? The optimal balance depends on specific organizational needs, security …
Data Management Databases And Organizations (book)
1. What is the optimal balance between cloud-based and on-premise data management solutions? The optimal balance depends on specific organizational needs, security …
Data Management Databases And Organizations
Data Management Databases And Organizations [PDF] Data management databases are specialized systems designed to handle vast amounts of structured and unstructured data. …
The evolution of Data Management A practitioner’s …
It all boils down to data management – having a suitable data architecture to meet the needs of the organization backed by a data driven business culture. In this e-book, we review the …
THE ROLE OF DATABASE MANAGEMENT SYSTEM (DBMS) IN …
database management system (DBMS) is a software tool that makes it possible to organize data in a database. Within an organization, the. development of the database is typically controlled …
Data Management Databases And Organizations (book)
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Trends in Data Management - DATAVERSITY
DATAVERSITY’s 2022 Trends in Data Management Report ofers insights about the directions and concerns businesses have as Data Management continues to evolve. The overall …
What is Data Management and Why is it Important?
Effective data management is a crucial piece of deploying the IT systems that run business applications and provide analytical information to help drive operational decision-making and …
Data Management Databases And Organizations
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Data Management Databases And Organizations
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Data Management Databases And Organizations (2024)
Data Management Databases And Organizations [PDF] Trends like cloud-native databases, AI-driven data management, and the rise of edge computing require organizations to adopt agile …
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1. What is the optimal balance between cloud-based and on-premise data management solutions? The optimal balance depends on specific organizational needs, security …
Data Management Databases And Organizations (PDF)
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Data Management Databases And Organizations
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Data Management Databases And Organizations
implementation of enterprise data management practices; including widely adopted practices, methods and techniques, functions, roles, deliverables and metrics; Establishing a common …
