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Data-driven Block Ciphers for Fast Telecommunication Systems
by Nikolai Moldovyan Alexander A. MoldovyanThe Most Progressive and Complete Guide to DDO-Based CiphersDevelopers have long recognized that ciphers based on Permutation Networks (PNs) and Controlled Substitution-Permutation Networks (CSPNs) allow for the implementation of a variety of Data Driven Operations (DDOs). These DDOs can provide fast encryption without incurring excessive
Data-driven Decision-making for Product Managers: A Primer to Data Literacy in Product Management (Business Guides on the Go)
by Gabriel SteinhardtThis book is an essential guide for product managers seeking to harness the power of data to drive their product decisions. It is a detailed resource for developing and maintaining data literacy, a core skill for product managers. Through a structured approach supported by practical insights and illustrative examples, readers will learn to prioritize decisions based on quantitative data rather than intuition, understand core data concepts, and analyze and leverage data effectively. Product managers will discover how data can transform decision-making processes, enabling evidence-based selection, prioritization, and resource allocation for product features. By using customer feedback, user behavior data, market research, and performance metrics, product managers can foster a culture that leverages data to create successful products. This introductory primer and reference guide is indispensable for product managers aiming to integrate data-driven methodologies into their practice, ensuring their decisions are informed, strategic, and impactful.
Data-driven Generation of Policies (SpringerBriefs in Computer Science)
by Amy Sliva V. S. Subrahmanian Austin Parker Gerardo I. SimariThis Springer Brief presents a basic algorithm that provides a correct solution to finding an optimal state change attempt, as well as an enhanced algorithm that is built on top of the well-known trie data structure. It explores correctness and algorithmic complexity results for both algorithms and experiments comparing their performance on both real-world and synthetic data. Topics addressed include optimal state change attempts, state change effectiveness, different kind of effect estimators, planning under uncertainty and experimental evaluation. These topics will help researchers analyze tabular data, even if the data contains states (of the world) and events (taken by an agent) whose effects are not well understood. Event DBs are omnipresent in the social sciences and may include diverse scenarios from political events and the state of a country to education-related actions and their effects on a school system. With a wide range of applications in computer science and the social sciences, the information in this Springer Brief is valuable for professionals and researchers dealing with tabular data, artificial intelligence and data mining. The applications are also useful for advanced-level students of computer science.
Data-driven Marketing: Insights aus Wissenschaft und Praxis
by Silvia Boßow-Thies Christina Hofmann-Stölting Heike JochimsState-of-the-art Wissen zum Data-driven Marketing aus Forschung und PraxisFokussiert auf die entscheidenden Aspekte für ein erfolgreiches datengetriebenes MarketingAutoren sind Top-Experten aus der Praxis und der WissenschaftDieses Buch adressiert die entscheidenden Aspekte für ein erfolgreiches, datengetriebenes Marketing: Datenqualität, Datenanalyse, kreative, aber datenschutzkonforme und ethisch vertretbare Datennutzung. Die Herausgeberinnen haben dazu das aktuelle Know-how aus Wissenschaft und Praxis für die strategische und operative Marketingarbeit zusammengetragen. So ist ein wertvoller Impulsgeber und Leitfaden für Marketing-Professionals entstanden, die Ihre Marketingarbeit konsequent datenzentriert und kundenindividuell gestalten wollen. Dabei bleiben auch spezielle Aspekte wie eine visuelle Präsentation von Datenanalyse, der Einfluss der Tonalität einer Website auf die Werbewirksamkeit von Display Advertising und Prinzipien des digitalen Vertrauensaufbaus beim Einsatz von digitalen Kanälen nicht außen vor.Aus dem InhaltStrategischer Einsatz von Daten im Marketing Datenmanagement als Grundlage für MarketingentscheidungenSmarte Insights fürs Marketing (psychografisches Targeting, Programmatic Advertising, Uplift von Werbemaßnahmen, A/B-Testing)Data-driven Marketing in der realen Welt (Geointelligenz Im Outernet, digitale Komponenten bei Messen, Privacy Concerns in the Carsharing Economy)Datenschutz und die ethischen Grenzen der Datennutzung im Data-driven Marketing Mit Beiträgen von Prof. Dr. Silvia Boßow-Thies +++ Prof. Dr. Annette Corves +++ Prof. Dr. Nicole Fabisch +++ Prof. Dr. Lars-Gunnar Frahm +++ Dr. Björn Goerke +++ Prof. Dr. Goetz Greve +++ Prof. Dr. Susanne Hensel-Börner +++ Prof. Dr. Christina Hofmann-Stölting +++ Prof. Dr. Gregor Hopf +++ Luise Jacobs +++ Prof. Dr. Heike Jochims +++ Dr. Gwen Kaufmann +++ Carsten Köster +++ Terence Lutz +++ Prof. Dr. Doreén Pick +++ Dr. Dennis Proppe +++ Mareike Scheibe +++ Prof. Dr. Eva Schön +++ Prof. Dr. Manuel Stegemann +++ Prof. Dr. Thorsten Suwelack +++ Prof. Dr. Kai-Marcus Thäsler +++ Christian Westerkamp +++ Dr. Heike M. Wolters
Data-driven Modelling and Scientific Machine Learning in Continuum Physics (Interdisciplinary Applied Mathematics #60)
by Krishna GarikipatiThis monograph takes the reader through recent advances in data-driven methods and machine learning for problems in science—specifically in continuum physics. It develops the foundations and details a number of scientific machine learning approaches to enrich current computational models of continuum physics, or to use the data generated by these models to infer more information on these problems. The perspective presented here is drawn from recent research by the author and collaborators. Applications drawn from the physics of materials or from biophysics illustrate each topic. Some elements of the theoretical background in continuum physics that are essential to address these applications are developed first. These chapters focus on nonlinear elasticity and mass transport, with particular attention directed at descriptions of phase separation. This is followed by a brief treatment of the finite element method, since it is the most widely used approach to solve coupled partial differential equations in continuum physics. With these foundations established, the treatment proceeds to a number of recent developments in data-driven methods and scientific machine learning in the context of the continuum physics of materials and biosystems. This part of the monograph begins by addressing numerical homogenization of microstructural response using feed-forward as well as convolutional neural networks. Next is surrogate optimization using multifidelity learning for problems of phase evolution. Graph theory bears many equivalences to partial differential equations in its properties of representation and avenues for analysis as well as reduced-order descriptions--all ideas that offer fruitful opportunities for exploration. Neural networks, by their capacity for representation of high-dimensional functions, are powerful for scale bridging in physics--an idea on which we present a particular perspective in the context of alloys. One of the most compelling ideas in scientific machine learning is the identification of governing equations from dynamical data--another topic that we explore from the viewpoint of partial differential equations encoding mechanisms. This is followed by an examination of approaches to replace traditional, discretization-based solvers of partial differential equations with deterministic and probabilistic neural networks that generalize across boundary value problems. The monograph closes with a brief outlook on current emerging ideas in scientific machine learning.
Data-driven Modelling of Wind Farm Flow Control Strategies
by Nassir Cassamo Jan-Willen van WingerdenThis book presents data-driven algorithms used in the context of wind farm modelling and exploits their relation with concepts from non-linear dynamical system theory. The algortihms include Input Output Dynamic Mode Decomposition and their combination with the Koopman Operator theory. The latter improves on modelling and analysis of the aerodynamic interaction between wind turbines in wind farms and assists in uncovering insights into the existing dynamics and improves models accuracy. The authors introduce the topic of wind farm flow control, illustrating current strategies devised to overcome power losses in wind plants due to the aerodynamic interaction between turbines. Although controlling wind farms as a whole is becoming increasingly important, the high dimensions and governing non-linear dynamics inherent of wind farm systems make the design of numerical optimal controllers computationally expensive. This book describes a possible pathway to circumvent this challenge through reduced order models that can embed the existing non-linearities. The authors make use of high fidelity open-source simulation datasets and developed algorithms to fully show the potential of this approach using visual results. The reader is motivated to use the datasets and algorithms and exploit the potential of the reduced order models.
Data-driven Multivalence in the Built Environment (S.M.A.R.T. Environments)
by Nimish BiloriaThis book sets the stage for understanding how the exponential escalation of digital ubiquity in the contemporary environment is being absorbed, modulated, processed and actively used for enhancing the performance of our built environment. S.M.A.R.T., in this context, is thus used as an acronym for Systems & Materials in Architectural Research and Technology, with a specific focus on interrogating the intricate relationship between information systems and associative material, cultural and socioeconomic formations within the built environment. This interrogation is deeply rooted in exploring inter-disciplinary research and design strategies involving nonlinear processes for developing meta-design systems, evidence based design solutions and methodological frameworks, some of which, are presented in this issue. Urban health and wellbeing, urban mobility and infrastructure, smart manufacturing, Interaction Design, Urban Design & Planning as well as Data Science, as prominent symbiotic domains constituting the Built Environment are represented in this first book in the S.M.A.R.T. series. The spectrum of chapters included in this volume helps in understanding the multivalence of data from a socio-technical perspective and provides insight into the methodological nuances involved in capturing, analysing and improving urban life via data driven technologies.
Data-driven Organization Design
by Rupert MorrisonData is changing the nature of competition. Making sense of it is tough. Taking advantage of it is tougher. There is a business opportunity for organizations to use data and analytics to transform business performance. Organizations are by their nature complex. They are a constantly evolving system made up of objectives, processes designed to meet those objectives, people with skills and behaviours to do the work required, and all of this organised in a governance structure. It is dynamic, fluid and constantly moving over time. Using data and analytics you can connect all the elements of the system to design an environment for people to perform; an organization which has the right people, in the right place, doing the right things, at the right time. Only when everyone performs to their potential, do organizations have a hope of getting and sustaining a competitive edge. Data-driven Organization Design provides a practical framework for HR and Organization design practitioners to build a baseline of data, set objectives, carry out fixed and dynamic process design, map competencies, and right-size the organization. It shows how to collect the right data, present it meaningfully and ask the right questions of it. Whether looking to implement a long term transformation, large redesign, or a one-off small scale project, this book will show you how to make the most of your organizational data and analytics to drive business performance.
Data-driven Retailing: A Non-technical Practitioners' Guide (Management for Professionals)
by Louis-Philippe KerkhoveThis book provides retail managers with a practical guide to using data. It covers three topics that are key areas of innovation for retailers: Algorithmic Marketing, Logistics, and Pricing. Use cases from these areas are presented and discussed in a conceptual and comprehensive manner. Retail managers will learn how data analysis can be used to optimize pricing, customer loyalty and logistics without complex algorithms.The goal of the book is to help managers ask the right questions during a project, which will put them on the path to making the right decisions. It is thus aimed at practitioners who want to use advanced techniques to optimize their retail organization.
Data-ism: Inside the Big Data Revolution
by Steve LohrCoal, iron ore and oil were the fuel of the Industrial Revolution. Today's economies and governments are powered by something far less tangible: the explosive abundance of digital data.Steve Lohr, the New York Times' chief technology reporter, charts the ascent of Data-ism, the dominating philosophy of the day in which data is at the forefront of everything and decisions of all kinds are based on data analysis rather than experience and intuition. Taking us behind the scenes and introducing the DOPs (Data Oriented-People), the key personalities behind this revolution, he reveals how consuming the bits and bytes of the masses is transforming the nature of business and governance in unforeseen ways. But what are losing in the process and what new dangers await?
Data-ism: The Revolution Transforming Decision Making, Consumer Behavior, and Almost Everything Else
by Steve Lohr“Lohr uses his Pulitzer Prize-winning reporting skills to dig into and explain the power, pervasiveness, and potential downside of big data.” —Library JournalIn Data-ism, New York Times reporter Steve Lohr explains how big-data technology is ushering in a revolution in proportions that promise to be the basis of the next wave of efficiency and innovation across the economy. But more is at work here than technology. Big data is also the vehicle for a point of view, or philosophy, about how decisions will be—and perhaps should be—made in the future. Lohr investigates the benefits of data while also examining its dark side.Data-ism is about this next phase, in which vast Internet-scale data sets are used for discovery and prediction in virtually every field. It shows how this new revolution will change decision making—by relying more on data and analysis, and less on intuition and experience—and transform the nature of leadership and management. Focusing on young entrepreneurs at the forefront of data science as well as on giant companies such as IBM that are making big bets on data science for the future of their businesses, Data-ism is a field guide to what is ahead, explaining how individuals and institutions will need to exploit, protect, and manage data to stay competitive in the coming years. With rich examples of how the rise of big data is affecting everyday life, Data-ism also raises provocative questions about policy and practice that have wide implications for everyone.The age of data-ism is here. But are we ready to handle its consequences, good and bad?
Data-oriented Development with AngularJS
by Manoj WaikarThis book helps beginner-level AngularJS developers organize AngularJS applications by discussing important AngularJS concepts and best practices. If you are an experienced AngularJS developer but haven't written directives or haven't created custom HTML controls before, then this book is ideal for you.
Data: New Trajectories in Law (New Trajectories in Law)
by Robert HerianThis book explores the phenomenon of data – big and small – in the contemporary digital, informatic and legal-bureaucratic context. Challenging the way in which legal interest in data has focused on rights and privacy concerns, this book examines the contestable, multivocal and multifaceted figure of the contemporary data subject. The book analyses "data" and "personal data" as contemporary phenomena, addressing the data realms, such as stores, institutions, systems and networks, out of which they emerge. It interrogates the role of law, regulation and governance in structuring both formal and informal definitions of the data subject, and disciplining data subjects through compliance with normative standards of conduct. Focusing on the ‘personal’ in and of data, the book pursues a re-evaluation of the nature, role and place of the data subject qua legal subject in on and offline societies: one that does not begin and end with the inviolability of individual rights but returns to more fundamental legal principles suited to considerations of personhood, such as stewardship, trust, property and contract. The book’s concern with the production, use, abuse and alienation of personal data within the context of contemporary communicative capitalism will appeal to scholars and students of law, science and technology studies, and sociology; as well as those with broader political interests in this area.
DataFlow Supercomputing Essentials: Algorithms, Applications and Implementations (Computer Communications and Networks)
by Nemanja Trifunovic Veljko Milutinovic Milos Kotlar Marko Stojanovic Igor Dundic Zoran BabovicThis informative text/reference highlights the potential of DataFlow computing in research requiring high speeds, low power requirements, and high precision, while also benefiting from a reduction in the size of the equipment. The cutting-edge research and implementation case studies provided in this book will help the reader to develop their practical understanding of the advantages and unique features of this methodology. This work serves as a companion title to DataFlow Supercomputing Essentials: Algorithms, Applications and Implementations, which reviews the key algorithms in this area, and provides useful examples. Topics and features: reviews the library of tools, applications, and source code available to support DataFlow programming; discusses the enhancements to DataFlow computing yielded by small hardware changes, different compilation techniques, debugging, and optimizing tools; examines when a DataFlow architecture is best applied, and for which types of calculation; describes how converting applications to a DataFlow representation can result in an acceleration in performance, while reducing the power consumption; explains how to implement a DataFlow application on Maxeler hardware architecture, with links to a video tutorial series available online. This enlightening volume will be of great interest to all researchers investigating supercomputing in general, and DataFlow computing in particular. Advanced undergraduate and graduate students involved in courses on Data Mining, Microprocessor Systems, and VLSI Systems, will also find the book to be a helpful reference.
DataFlow Supercomputing Essentials: Research, Development and Education (Computer Communications and Networks)
by Dejan Markovic Jakob Salom Veljko Milutinovic Dragan Veljovic Nenad Korolija Luka PetrovicThis informative text/reference highlights the potential of DataFlow computing in research requiring high speeds, low power requirements, and high precision, while also benefiting from a reduction in the size of the equipment. The cutting-edge research and implementation case studies provided in this book will help the reader to develop their practical understanding of the advantages and unique features of this methodology. This work serves as a companion title to DataFlow Supercomputing Essentials: Algorithms, Applications and Implementations, which reviews the key algorithms in this area, and provides useful examples. Topics and features: reviews the library of tools, applications, and source code available to support DataFlow programming; discusses the enhancements to DataFlow computing yielded by small hardware changes, different compilation techniques, debugging, and optimizing tools; examines when a DataFlow architecture is best applied, and for which types of calculation; describes how converting applications to a DataFlow representation can result in an acceleration in performance, while reducing the power consumption; explains how to implement a DataFlow application on Maxeler hardware architecture, with links to a video tutorial series available online. This enlightening volume will be of great interest to all researchers investigating supercomputing in general, and DataFlow computing in particular. Advanced undergraduate and graduate students involved in courses on Data Mining, Microprocessor Systems, and VLSI Systems, will also find the book to be a helpful reference.
Database Benchmarking and Stress Testing: An Evidence-Based Approach to Decisions on Architecture and Technology
by Bert ScalzoProvide evidence-based answers that can be measured and relied upon by your business. Database administrators will be able to make sound architectural decisions in a fast-changing landscape of virtualized servers and container-based solutions based on the empirical method presented in this book for answering “what if” questions about database performance.Today’s database administrators face numerous questions such as: What if we consolidate databases using multitenant features? What if we virtualize database servers as Docker containers? What if we deploy the latest in NVMe flash disks to speed up IO access?Do features such as compression, partitioning, and in-memory OLTP earn back their price? What if we move our databases to the cloud?As an administrator, do you know the answers or even how to test the assumptions?Database Benchmarking and Stress Testing introduces you to database benchmarking using industry-standard test suites such as the TCP series of benchmarks, which are the same benchmarks that vendors rely upon. You’ll learn to run these industry-standard benchmarks and collect results to use in answering questions about the performance impact of architectural changes, technology changes, and even down to the brand of database software. You’ll learn to measure performance and predict the specific impact of changes to your environment. You’ll know the limitations of the benchmarks and the crucial difference between benchmarking and workload capture/reply. This book teaches you how to create empirical evidence in support of business and technology decisions. It’s about not guessing when you should be measuring. Empirical testing is scientific testing that delivers measurable results. Begin with a hypothesis about the impact of a possible architecture or technology change. Then run the appropriate benchmarks to gather data and predict whether the change you’re exploring will be beneficial, and by what order of magnitude. Stop guessing. Start measuring. Let Database Benchmarking and Stress Testing show the way.What You'll LearnUnderstand the industry-standard database benchmarks, and when each is best usedPrepare for a database benchmarking effort so reliable results can be achievedPerform database benchmarking for consolidation, virtualization, and cloud projectsRecognize and avoid common mistakes in benchmarking database performanceMeasure and interpret results in a rational, concise manner for reliable comparisonsChoose and provide advice on benchmarking tools based on their pros and consWho This Book Is ForDatabase administrators and professionals responsible for advising on architectural decisions such as whether to use cloud-based services, whether to consolidate and containerize, and who must make recommendations on storage or any other technology that impacts database performance
Database Computing for Scholarly Research: Case Studies Using the Online Cultural and Historical Research Environment (Quantitative Methods in the Humanities and Social Sciences)
by Sandra R. Schloen Miller C. ProsserThis book discusses in detail a series of examples drawn from scholarly projects that use the OCHRE database platform (Online Cultural and Historical Research Environment). These case studies illustrate the wide range of data that can be managed with this platform and the wide variety of problems solved by OCHRE’s item-based graph data model. The unique features and design principles of the OCHRE platform are explained and justified, helping readers to imagine how the system could be used for their own data.Data generated by studies in the humanities and social sciences is often semi-structured, fragmented, highly variable, and subject to many interpretations, making it difficult to represent adequately in a conventional database. The authors examine commonly used methods of data management in the humanities and offer a compelling argument for a different approach that takes advantage of powerful computational techniques for organizing scholarly information.This book is a challenge to scholars in the humanities and social sciences, asking them to expect more from technology as they pursue their research goals. Written jointly by a software engineer and a research scholar, each with many years of experience in applying database methods to diverse kinds of scholarly data, it shows how scholars can make the most of their existing data while going beyond the limitations of commonly used software tools to represent their objects of study in a more accurate, nuanced, and flexible way.
Database Concepts (Eighth Edition)
by David M. Kroenke David J. Auer Scott L. Vandenberg Robert C. YoderFor undergraduate database management students or business professionals <P><P>Here’s practical help for understanding, creating, and managing small databases—from two of the world’s leading database authorities. Database Concepts gives undergraduate database management students and business professionals alike a firm understanding of the concepts behind the software, using Access 2016 to illustrate the concepts and techniques. Three projects run throughout the text, to show students how to apply the concepts to real-life business situations. The text provides flexibility for choosing the software instructors want to use in class; allows students to work with new, complete databases, including Wedgewood Pacific, Heather Sweeney Designs, and Wallingford Motors; and includes coverage for some of the latest information on databases available.
Database Design Using Entity-Relationship Diagrams
by Sikha Saha Bagui Richard Walsh EarpEssential 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.
Database Design Using Entity-Relationship Diagrams (Foundations of Database Design)
by Sikha BaguiEntity-relationship (E-R) diagrams are time-tested models for database development well-known for their usefulness in mapping out clear database designs. Also commonly known is how difficult it is to master them. With this comprehensive guide, database designers and developers can quickly learn all the ins and outs of E-R diagramming to become experts.
Database Design and Relational Theory: Normal Forms and All That Jazz
by C. J. DateCreate database designs that scale, meet business requirements, and inherently work toward keeping your data structured and usable in the face of changing business models and software systems.This book is about database design theory. Design theory is the scientific foundation for database design, just as the relational model is the scientific foundation for database technology in general. Databases lie at the heart of so much of what we do in the computing world that negative impacts of poor design can be extraordinarily widespread. This second edition includes greatly expanded coverage of exotic and little understood normal forms such as: essential tuple normal form (ETNF), redundancy free normal form (RFNF), superkey normal form (SKNF), sixth normal form (6NF), and domain key normal form (DKNF). Also included are new appendixes, including one that provides an in-depth look into the crucial notion of data consistency. Sequencing of topics has been improved, and many explanations and examples have been rewritten and clarified based upon the author’s teaching of the content in instructor-led courses. This book aims to be different from other books on design by bridging the gap between the theory of design and the practice of design. The book explains theory in a way that practitioners should be able to understand, and it explains why that theory is of considerable practical importance. Reading this book provides you with an important theoretical grounding on which to do the practical work of database design. Reading the book also helps you in going to and understanding the more academic texts as you build your base of knowledge and expertise. Anyone with a professional interest in database design can benefit from using this book as a stepping-stone toward a more rigorous design approach and more lasting database models.What You Will LearnUnderstand what design theory is and is notBe aware of the two different goals of normalizationKnow which normal forms are truly significant Apply design theory in practice Be familiar with techniques for dealing with redundancy Understand what consistency is and why it is crucially important Who This Book Is ForThose having a professional interest in database design, including data and database administrators; educators and students specializing in database matters; information modelers and database designers; DBMS designers, implementers, and other database vendor personnel; and database consultants. The book is product independent.
Database Design and Relational Theory: Normal Forms and All That Jazz
by C. J. DateWhat makes this book different from others on database design? Many resources on design practice do little to explain the underlying theory, and books on design theory are aimed primarily at theoreticians. In this book, renowned expert Chris Date bridges the gap by introducing design theory in ways practitioners can understand—drawing on lessons learned over four decades of experience to demonstrate why proper database design is so critical in the first place.Every chapter includes a set of exercises that show how to apply the theoretical ideas in practice, provide additional information, or ask you to prove some simple theoretical result. If you’re a database professional familiar with the relational model, and have more than a passing interest in database design, this book is for you.Questions this book answers include:Why is Heath’s Theorem so important?What is The Principle of Orthogonal Design?What makes some JDs reducible and others irreducible?Why does dependency preservation matter?Should data redundancy always be avoided? Can it be?Databases often stay in production for decades, and careful design is critical for avoiding subtle errors and processing problems over time. If they’re badly designed, the negative impacts can be incredibly widespread. This gentle introduction shows you how to use important theoretical results to create good database designs.
Database Design, Application Development, and Administration (Fifth Edition)
by Mannino Michael V. ManninoThis course has two teaching challenges - good database design and a skills-development approach. This text contains worked examples along with projects that need manipulation of sample databases. Entity relationship diagrams are also included, as well as a software design tool, ER-Assistant.
Database Design, Application Development, and Administration (Sixth Edition)
by Michael ManninoMannino provides with a foundation to understand database technology supporting enterprise computing needs. The text is ideal for new students of database management, who need to understand the fundamental concepts of database management and the relational data model, followed by a mastery of skills in database design and database application development. This textbook provides tools to help students understand relational databases and acquire skills to solve basic and advanced problems in query formulation, data modeling, normalization, application data requirements, and customization of database applications.
Database Development For Dummies (For Dummies Ser.)
by Allen G. TaylorFrom ATMs to the personal finance, online shopping to networked information management, databases permeate every nook and cranny of our highly-connected, information-intensive world. Databases have become so integral to the business environment that, nowadays, it’s next to impossible to stay competitive without the assistance of some sort of database technology—no matter what type or size of business you run. But developing your own database can be very tricky. In fact, whether you want to keep records for a small business or run a large e-commerce website, developing the right database system can be a major challenge. Which is where this friendly guide comes in. From data modeling methods and development tools to Internet accessibility and security, Database Development For Dummies shows you, step-by-step, everything you need to know about building a custom system from the ground up. You’ll discover how to: Model data accurately Design a reliable functional database Deliver robust relational databases on time and on budget Build a user-friendly database application Put your database on the Web In plain English, author Allen Taylor acquaints you with the most popular data modeling methods, and he shows you how to systematically design and develop a system incorporating a database and one or more applications that operate on it. Important topics he explores include: Understanding database architecture and how it has evolved Recognizing how database technology affects everyday life Using a structured approach to database development Creating an appropriate data model Developing a reliable relational design Understanding the complexities you’re likely to encounter in designing a database and how to simplify them Implementing your design using Microsoft Access 2000, SQL Server and other powerful database development tools Keeping your database secure Putting your database on the Internet Today’s powerful, low-cost database development tools make it possible for virtually anybody to create their own database. Get Database Development For Dummies and discover what it takes to design, develop and implement a sophisticated database system tailored to you and your company’s current and future data storage and management needs.