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Gain a solid foundation in database design and implementation with the practical and easy-to-understand approach in DATABASE SYSTEMS: DESIGN, IMPLEMENTATION, AND MANAGEMENT, 12E. Filled with diagrams, illustrations, and tables, this market-leading text provides in-depth coverage of database design. You learn the key to successful database implementation: proper design of databases to fit within a larger strategic view of the data environment. Renowned for its clear, straightforward writing style, this text provides an outstanding balance of theory and practice. You gain the hands-on skills to make you attractive to employers. Updates include the latest coverage of cloud data services and a new chapter on Big Data Analytics and NoSQL, including related Hadoop technologies. In addition, new review questions, problem sets, and cases offer multiple opportunities to test your understanding and develop useful design skills.
A GUIDE TO SQL, Ninth Edition, provides an effective introduction to SQL programming using straightforward instruction, extensive hands-on exercises, and a strong foundation in real-world business applications. The Ninth Edition builds on the longstanding success of this proven text by presenting basic SQL commands in the context of a running case, in which a business uses SQL to manage orders, items, customers, and sales reps. The authors emphasize that fundamental principles and practices apply regardless of the database environment chosen, and they include examples from the latest versions of Oracle (R) and Microsoft (R) Access (R), and SQL Server throughout the text.
Database skills are among the most in-demand IT skills today. Now you can gain a solid foundation in database design and implementation with the practical, easy-to-understand approach in the market-leading DATABASE SYSTEMS: DESIGN, IMPLEMENTATION, AND MANAGEMENT, 13E. Diagrams, illustrations, and tables clarify in-depth coverage of database design. You learn the key to successful database implementation as you study how to properly design databases to fit within the larger strategic data environment. Clear, straightforward writing supports an outstanding balance of theory and practice with hands-on skills today's employers want. Revised SQL coverage offers more SQL examples and simpler explanations that focus on the areas most important for a database career. More coverage of Big Data Analytics and NoSQL, including related Hadoop technologies, now provides a stronger hands-on approach.
Find out what Blockchain is, how it works, and what it can do for you.
Blockchain is the technology behind Bitcoin, the revolutionary 'virtual currency' that's changing the way people do business. While Bitcoin has enjoyed some well-deserved hype, Blockchain may be Bitcoin's most vital legacy. Blockchain For Dummies is the ideal starting place for business pros looking to gain a better understanding of what Blockchain is, how it can improve the integrity of their data, and how it can work to fundamentally change their business and enhance their data security.
Blockchain For Dummies covers the essential things you need to know about this exciting technology's promise of revolutionizing financial transactions, data security, and information integrity. The book covers the technologies behind Blockchain, introduces a variety of existing Blockchain solutions, and even walks you through creating a small but working Blockchain-based application.
Blockchain holds the promise to revolutionize a wide variety of businesses. Get in the know about Blockchain now with Blockchain For Dummies and be ready to make the changes to business that your colleagues and competitors will later wish they'd done.
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The second edition of Database Systems maintains its engaging writing style and brevity; its unique balance between theory and practice and its wealth of examples throughout the text; inspiring student-friendly learning at its best. The international edition provides a solid and practical foundation for the design, implementation and management of database systems. This foundation is built on the notion that, while databases are very practical things, their successful creation depends on understanding the important concepts that define them. The new edition has been updated with all the latest developments and technologies and incorporates a generous number of localised and motivating business vignettes that tie the concepts to real-life situations. This edition is suitable for a first course in databases at undergraduate level and will also provide essential material for conversion postgraduate courses. Providing comprehensive and practical coverage of core database concepts, it is an ideal text not only for those studying database management systems in the context of computer science, but also those on courses in the areas of information systems and business information technology. This textbook also comes packaged with a fully tailored CourseMate and an Instructor's website will also be available to adopters.
Practical and easy to understand Database Principles: Fundamentals of Design, Implementation, and Management, 10/e, International Edition gives readers a solid foundation in database design and implementation. Filled with visual aids such as diagrams, illustrations, and tables, this market-leading book provides in-depth coverage of database design, demonstrating that the key to successful database implementation is in proper design of databases to fit within a larger strategic view of the data environment. Renowned for its clear, straightforward writing style, the tenth edition has been thoroughly updated to include hot topics such as green computing/sustainability for modern data centers, the role of redundant relationships, and examples of web-database connectivity and code security. In addition, new review questions, problem sets, and cases have been added throughout the book so that readers have multiple opportunities to test their understanding and develop real and useful design skills.
The second edition of Database Principles maintains its engaging writing style and brevity; its unique balance between theory and practice and its wealth of examples throughout the text; inspiring student-friendly learning at its best. The international edition provides a solid and practical foundation for the design, implementation and management of database systems. This foundation is built on the notion that, while databases are very practical things, their successful creation depends on understanding the important concepts that define them. The new edition has been updated with all the latest developments and technologies and incorporates a generous number of localised and motivating business vignettes that tie the concepts to real-life situations. This edition is suitable for a first course in databases at undergraduate level and will also provide essential material for conversion postgraduate courses. Providing comprehensive and practical coverage of core database concepts, it is an ideal text not only for those studying database management systems in the context of computer science, but also those on courses in the areas of information systems and business information technology. This textbook also comes packaged with a fully tailored CourseMate and an Instructor's website will also be available to adopters.
Unravel the mysteries of blockchains Blockchain technologies are disrupting some of the world's biggest industries. Blockchain For Dummies provides a fast way to catch up with the essentials of this quickly evolving tech. Written by an author involved in founding and analyzing blockchain solutions, this book serves to help those who need to understand what a blockchain can do (and can't do). This revised edition walks you through how a blockchainsecurely records data across independent networks. It offers a tour of some of the world's best-known blockchains, including those that power Bitcoin and other cryptocurrencies. It also provides a glance at how blockchain solutions are affecting the worlds of finance, supply chain management, insurance, and governments. Get a clear picture of what a blockchain can do Learn how blockchains rule cryptocurrency and smart contracts Discover current blockchains and how each of them work Test blockchain apps Blockchain has become the critical buzzword in the world of financial technology and transaction security -- and now you can make sense of it with the help of this essential guide.
The goal of Rainer, Introduction to Information Systems 5e is to teach all business majors, especially undergraduate ones, how to use information technology to master their current or future jobs and to help ensure the success of their organization. To accomplish this goal, this text helps students to become informed users; that is, persons knowledgeable about information systems and information technology. The focus is not on merely learning the concepts of IT but rather on applying those concepts to facilitate business processes. The content concentrate on placing information systems in the context of business, so that students will more readily grasp the concepts presented in the text. The theme of this book is What's In IT for Me? This question is asked by all students who take this course. The book will show you that IT is the backbone of any business, whether a student is majoring in Accounting, Finance, Marketing, Human Resources, or Production/Operations Management.
Get up to speed on the nuances of NoSQL databases and what they mean for your organization This easy to read guide to NoSQL databases provides the type of no-nonsense overview and analysis that you need to learn, including what NoSQL is and which database is right for you. Featuring specific evaluation criteria for NoSQL databases, along with a look into the pros and cons of the most popular options, NoSQL For Dummies provides the fastest and easiest way to dive into the details of this incredible technology. You'll gain an understanding of how to use NoSQL databases for mission-critical enterprise architectures and projects, and real-world examples reinforce the primary points to create an action-oriented resource for IT pros. If you're planning a big data project or platform, you probably already know you need to select a NoSQL database to complete your architecture. But with options flooding the market and updates and add-ons coming at a rapid pace, determining what you require now, and in the future, can be a tall task. This is where NoSQL For Dummies comes in! Learn the basic tenets of NoSQL databases and why they have come to the forefront as data has outpaced the capabilities of relational databases Discover major players among NoSQL databases, including Cassandra, MongoDB, MarkLogic, Neo4J, and others Get an in-depth look at the benefits and disadvantages of the wide variety of NoSQL database options Explore the needs of your organization as they relate to the capabilities of specific NoSQL databases Big data and Hadoop get all the attention, but when it comes down to it, NoSQL databases are the engines that power many big data analytics initiatives. With NoSQL For Dummies, you'll go beyond relational databases to ramp up your enterprise's data architecture in no time.
Markets have long been acknowledged to be a superior mechanism for managing resources but until the advent of big data, they largely functioned better in theory than in practice. Now, as ideal markets are within reach because of vastly greater access to information, we are on the verge of a major disruption. As data becomes a more valuable asset than cash, the rules for surviving and thriving are changing. Reinventing Capitalism is a provocative look at how data is reinventing markets and, in so doing, is ushering in an era where the firm is no longer predominant. With richer and more comprehensive information about human wants and needs, an economy powered by data offers the possibility of increased abundance, equality, and resilience. The data-driven markets that will thrive in this environment are far better than firms at organizing human endeavors, meaning that finance driven capitalism is being displaced by its more efficient, more sustainable, and more democratic disruptor: data capitalism.
Get The Ins-and-Outs of SQL and PL/SQL From an Oracle Expert.
Perform database functions quickly and easily using the comprehensive information in this step-by-step guide. Oracle professional Christopher Allen begins with database basics and progresses to plain-language explanations and real-world examples of SQL statements and PL/SQL programs. Youll learn how to manage, query, and manipulate data, use SQL*Plus, create SQL functions, and write practical PL/SQL applications. Review questions, chapter summaries, and hands-on projects will have you understanding and exploiting the powerful features of Oracle Database 10"g" in no time.. . Create tables, rows, records, columns, and fields. Store text, numbers, dates, pictures, and soundfiles in tables and columns. Define, manipulate, retrieve, and delete data, using SQL commands. Select, sort, and filter records with SQL functions and procedures. Write SQL commands to declare variables using anchored types . Use SAVEPOINT and ROLLBACK commands to ensure multilevel undo. Perform time-based and hierarchical data queries. Edit and reuse commands in script files, using the SQL*Plus program . Use PL/SQL views, sequences, procedures, functions, and packages . Use triggers to automate auditing, security, and maintenance tasks. .
The data lake is a daring new approach for harnessing the power of big data technology and providing convenient self-service capabilities. But is it right for your company? This book is based on discussions with practitioners and executives from more than a hundred organizations, ranging from data-driven companies such as Google, LinkedIn, and Facebook, to governments and traditional corporate enterprises. You'll learn what a data lake is, why enterprises need one, and how to build one successfully with the best practices in this book. Alex Gorelik, CTO and founder of Waterline Data, explains why old systems and processes can no longer support data needs in the enterprise. Then, in a collection of essays about data lake implementation, you'll examine data lake initiatives, analytic projects, experiences, and best practices from data experts working in various industries. Get a succinct introduction to data warehousing, big data, and data science Learn various paths enterprises take to build a data lake Explore how to build a self-service model and best practices for providing analysts access to the data Use different methods for architecting your data lake Discover ways to implement a data lake from experts in different industries
Standard SQL guarantees that no matter what the database implementation, the features of the language will be applicable across all platforms.
Data structures are the fundamental building blocks of any computer program, used for storing, representing and manipulating data in a computer. This text presents the basic concepts of data structures as part of the art of writing computer programs. The author concentrates on the fundamentals of what should be done to solve a problem efficiently rather than technical implementation details. The text includes pseudocode and covers all the most common data structures, such as queues, stacks, trees, heaps, and hash tables, along with the basics of searching, sorting, and coding. This book can supplement any undergraduate algorithms or discrete math course and will also be accessible to students and researchers in other quantitative disciplines. No prerequisites beyond introductory programming and basic mathematics are required, and the accessible, conceptual presentation will appeal to undergraduates in many quantitative fields. Carefully designed problem sets with selected solutions will allow students to test their understanding.
The professional programmer's Deitel(R) guide to Python(R) with introductory artificial intelligence case studies Written for programmers with a background in another high-level language, this book uses hands-on instruction to teach today's most compelling, leading-edge computing technologies and programming in Python-one of the world's most popular and fastest-growing languages. Please read the Table of Contents diagram inside the front cover and the Preface for more details. In the context of 500+, real-world examples ranging from individual snippets to 40 large scripts and full implementation case studies, you'll use the interactive IPython interpreter with code in Jupyter Notebooks to quickly master the latest Python coding idioms. After covering Python Chapters 1--5 and a few key parts of Chapters 6--7, you'll be able to handle significant portions of the hands-on introductory AI case studies in Chapters 11--16, which are loaded with cool, powerful, contemporary examples. These include natural language processing, data mining Twitter(R) for sentiment analysis, cognitive computing with IBM(R) Watson(TM), supervised machine learning with classification and regression, unsupervised machine learning with clustering, computer vision through deep learning and convolutional neural networks, deep learning with recurrent neural networks, big data with Hadoop(R), Spark(TM) and NoSQL databases, the Internet of Things and more. You'll also work directly or indirectly with cloud-based services, including Twitter, Google Translate(TM), IBM Watson, Microsoft(R) Azure(R), OpenMapQuest, PubNub and more. Features 500+ hands-on, real-world, live-code examples from snippets to case studies IPython + code in Jupyter(R) Notebooks Library-focused: Uses Python Standard Library and data science libraries to accomplish significant tasks with minimal code Rich Python coverage: Control statements, functions, strings, files, JSON serialization, CSV, exceptions Procedural, functional-style and object-oriented programming Collections: Lists, tuples, dictionaries, sets, NumPy arrays, pandas Series & DataFrames Static, dynamic and interactive visualizations Data experiences with real-world datasets and data sources Intro to Data Science sections: AI, basic stats, simulation, animation, random variables, data wrangling, regression AI, big data and cloud data science case studies: NLP, data mining Twitter(R), IBM(R) Watson(TM), machine learning, deep learning, computer vision, Hadoop(R), Spark(TM), NoSQL, IoT Open-source libraries: NumPy, pandas, Matplotlib, Seaborn, Folium, SciPy, NLTK, TextBlob, spaCy, Textatistic, Tweepy, scikit-learn(R), Keras and more. Register your product for convenient access to downloads, updates, and/or corrections as they become available.
Each Student Book and ActiveBook have has clearly laid out pages with a range of supportive features to aid learning and teaching: Getting to know your unit sections ensure learners understand the grading criteria and unit requirements. Getting ready for Assessment sections focus on preparation for external assessment with guidance for learners on what to expect. Hints and tips will help them prepare for assessment and sample answers are provided for a range of question types including, short and long answer questions, all with a supporting commentary. Learners can also prepare for internal assessment using this feature. A case study of a learner completing the internal assessment for that unit covering 'How I got started', 'How I brought it all together' and 'What I got from the experience'. Pause Point feature provide opportunities for learners to self-evaluate their learning at regular intervals. Each Pause Point point feature gives learners a Hint or Extend option to either revisit and reinforce the topic or to encourage independent research or study skills. Case Study and Theory into Practice features enable development of problem-solving skills and place the theory into real life situations learners could encounter. Assessment Activity/Practice provide scaffolded assessment practice activities that help prepare learners for assessment. Within each assessment practice activity, a Plan, Do and Review section supports learners' formative assessment by making sure they fully understand what they are being asked to do, what their goals are and how to evaluate the task and consider how they could improve. Dedicated Think Future pages provide case studies from the industry, with a focus on aspects of skills development that can be put into practice in a real work environment and further study.
Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords? In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architecture
This edited volume focuses on the latest and most impactful advancements of multimedia data globally available for environmental and earth biodiversity. The data reflects the status, behavior, change as well as human interests and concerns which are increasingly crucial for understanding environmental issues and phenomena. This volume addresses the need for the development of advanced methods, techniques and tools for collecting, managing, analyzing, understanding and modeling environmental & biodiversity data, including the automated or collaborative species identification, the species distribution modeling and their environment, such as the air quality or the bio-acoustic monitoring. Researchers and practitioners in multimedia and environmental topics will find the chapters essential to their continued studies.
Data is a valuable corporate asset and its effective management can be vital to an organisation's success. This professional guide covers all the key areas of data management, including database development and corporate data modelling. It is business-focused, providing the knowledge and techniques required to successfully implement the data management function. This new edition covers web technology and its relation to databases and includes material on the management of master data.
The first book to present the common mathematical foundations of big data analysis across a range of applications and technologies. Today, the volume, velocity, and variety of data are increasing rapidly across a range of fields, including Internet search, healthcare, finance, social media, wireless devices, and cybersecurity. Indeed, these data are growing at a rate beyond our capacity to analyze them. The tools-including spreadsheets, databases, matrices, and graphs-developed to address this challenge all reflect the need to store and operate on data as whole sets rather than as individual elements. This book presents the common mathematical foundations of these data sets that apply across many applications and technologies. Associative arrays unify and simplify data, allowing readers to look past the differences among the various tools and leverage their mathematical similarities in order to solve the hardest big data challenges. The book first introduces the concept of the associative array in practical terms, presents the associative array manipulation system D4M (Dynamic Distributed Dimensional Data Model), and describes the application of associative arrays to graph analysis and machine learning. It provides a mathematically rigorous definition of associative arrays and describes the properties of associative arrays that arise from this definition. Finally, the book shows how concepts of linearity can be extended to encompass associative arrays. Mathematics of Big Data can be used as a textbook or reference by engineers, scientists, mathematicians, computer scientists, and software engineers who analyze big data.
Markets have long been acknowledged to be a superior mechanism for managing resources but until the advent of big data, they largely functioned better in theory than in practice. Now, as ideal markets are within reach because of vastly greater access to information, we are on the verge of a major disruption. As data becomes a more valuable asset than cash, the rules for surviving and thriving are changing. Reinventing Capitalism is a provocative look at how data is reinventing markets and, in so doing, is ushering in an era where the firm is no longer predominant. With richer and more comprehensive information about human wants and needs, an economy powered by data offers the possibility of increased abundance, equality, and resilience. The data-driven markets that will thrive in this environment are far better than firms at organizing human endeavors, meaning that finance driven capitalism is being displaced by its more efficient, moresustainable, and more democratic disruptor: data capitalism.
Databases are often viewed as the end product rather than as a tool in the work place. This book has been written to address this need, using straightforward examples and assessing different ways of storing information. It is a practical guide to collecting data and using Microsoft Access to transform it into useful information. Written for both Business Studies students and professionals, it adopts a functional approach which teaches theory by practical example. 'Jargon buster' sidebars explain the terminology related to database theory, while the revision questions at the end of each unit aid comprehension. This straightforward approach means that the text is ideal for self-study.
Delivering concise, cutting-edge coverage, CONCEPTS OF DATABASE MANAGEMENT, 8e uses real-world cases, examples, and illustrations to give students a thorough understanding of such critical issues as database design, data integrity, concurrent updates, data security, and more. Completely updated to Microsoft Access 2013 standards, the text presents SQL in a database-neutral environment and covers all major topics, including E-R diagrams, normalization, and database design. It provides detailed coverage of the relational model (including QBE and SQL), normalization and views, database administration and management, and more. Advanced topics covered include distributed databases, data warehouses, stored procedures, triggers, data macros, and Web Apps. Ideal for an introductory database course in an information systems, business, or CIS program, CONCEPTS OF DATABASE MANAGEMENT, 8e can be used in varying disciplines by instructors who want database coverage without using a trade book or a large academic book.
Learn how easy it is to apply sophisticated statistical and machine learning methods to real-world problems when you build on top of the Google Cloud Platform (GCP). This hands-on guide shows developers entering the data science field how to implement an end-to-end data pipeline, using statistical and machine learning methods and tools on GCP. Through the course of the book, you'll work through a sample business decision by employing a variety of data science approaches. Follow along by implementing these statistical and machine learning solutions in your own project on GCP, and discover how this platform provides a transformative and more collaborative way of doing data science. You'll learn how to: Automate and schedule data ingest, using an App Engine application Create and populate a dashboard in Google Data Studio Build a real-time analysis pipeline to carry out streaming analytics Conduct interactive data exploration with Google BigQuery Create a Bayesian model on a Cloud Dataproc cluster Build a logistic regression machine-learning model with Spark Compute time-aggregate features with a Cloud Dataflow pipeline Create a high-performing prediction model with TensorFlow Use your deployed model as a microservice you can access from both batch and real-time pipelines
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