Integrations of Data Warehousing, Data Mining and Database Technologies: Innovative Approaches, Taniar, Taniar David, Chen Li
Автор: Michael H Brackett Название: Data Resource Integration: Understanding & Resolving a Disparate Data Resource ISBN: 1935504231 ISBN-13(EAN): 9781935504238 Издательство: Gazelle Book Services Рейтинг: Цена: 102950.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Are you struggling with a disparate data resource? Are there multiple existences of the same business fact scattered throughout the data resource? Are those multiple existences out of synch with each other? Do you have difficulty finding the data you need to support business activities? Do the data you find have poor quality? If the answer to any of these questions is Yes, then you need this book to guide you toward creating an integrated data resource. Most public and private sector organisations have a disparate data resource that was created over many years. That disparate data resource contains multiple existences of business facts that are out of synch with each other, are of poor quality, and are difficult to locate. The traditional approach to dealing with a disparate data resource is to perform periodic and temporary data integration to support a specific application or business activity. Those piecemeal data integration efforts may meet a current need, but seldom solve the underlying problems with a disparate data resource, and sometimes make the situation worse. This book explains how to go about understanding and resolving a disparate data resource and creating a comparate data resource that fully meets an organisations current and future business information demand. It builds on "Data Resource Simplexity", which described how to stop the burgeoning data disparity. It explains the concepts, principles, and techniques for understanding a disparate data resource within the context of a common data architecture, and resolving that disparity with minimum impact on the business. Like "Data Resource Simplexity", Michael Brackett draws on five decades of data management experience building and managing data resources, and resolving disparate data resources in both public and private sector organisations. He leverages theories, concepts, principles, and techniques from a wide variety of disciplines, such as human dynamics, mathematics, physics, chemistry, and biology, and applies them to the process of understanding and resolving a disparate data resource. He shows you how to approach and resolve a disparate data resource, and build a comparate data resource that fully supports the business.
Автор: Masri David Название: Developing Data Migrations and Integrations with Salesforce: Patterns and Best Practices ISBN: 1484242084 ISBN-13(EAN): 9781484242087 Издательство: Springer Рейтинг: Цена: 60550.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Migrate your data to Salesforce and build low-maintenance and high-performing data integrations to get the most out of Salesforce and make it a 'go-to' place for all your organization's customer information.When companies choose to roll out Salesforce, users expect it to be the place to find any and all Information related to a customer—the coveted Client 360° view. On the day you go live, users expect to see all their accounts, contacts, and historical data in the system. They also expect that data entered in other systems will be exposed in Salesforce automatically and in a timely manner. This book shows you how to migrate all your legacy data to Salesforce and then design integrations to your organization's mission-critical systems. As the Salesforce platform grows more powerful, it also grows in complexity. Whether you are migrating data to Salesforce, or integrating with Salesforce, it is important to understand how these complexities need to be reflected in your design. Developing Data Migrations and Integrations with Salesforce covers everything you need to know to migrate your data to Salesforce the right way, and how to design low-maintenance, high-performing data integrations with Salesforce. This book is written by a practicing Salesforce integration architect with dozens of Salesforce projects under his belt. The patterns and practices covered in this book are the results of the lessons learned during those projects. What You’ll LearnKnow how Salesforce’s data engine is architected and whyUse the Salesforce Data APIs to load and extract dataPlan and execute your data migration to SalesforceDesign low-maintenance, high-performing data integrations with SalesforceUnderstand common data integration patterns and the pros and cons of eachKnow real-time integration options for SalesforceBe aware of common pitfallsBuild reusable transformation code covering commonly needed Salesforce transformation patternsWho This Book Is For Those tasked with migrating data to Salesforce or building ongoing data integrations with Salesforce, regardless of the ETL tool or middleware chosen; project sponsors or managers nervous about data tracks putting their projects at risk; aspiring Salesforce integration and/or migration specialists; Salesforce developers or architects looking to expand their skills and take on new challenges
Автор: Jovan Pehcevski Название: Database & Data Warehousing Technologies ISBN: 1680944649 ISBN-13(EAN): 9781680944648 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 160770.00 T Наличие на складе: Невозможна поставка. Описание: Data Warehouse is a type of data organization on which decision-making systems are based. The data storage in a data warehouse system typically needs to fully cover one or more business areas (e.g., procurement, sales), and the data in the data warehouse needs to be comprehensive, meaning that it should be fully integrated with the internal data organization. These data records must include a longer period of time (five, ten or more years) because this longer time periodical analysis is very significant for every business. Smaller data warehouses that include data from only one business area are called sectorial warehouses, or data marts.The data warehouse is designed for managers, but also for everyone performing various analytical tasks, such as monitoring and reporting operations based on different business rules and carried out by placing directed queries and analysis of the results obtained; analysis and diagnosis jobs based on skills, performing an iterative analysis and discovery of the information needed; and planning and simulation operations based on knowledge, performing modeling and execution of a drafted model. The usual system design splits the database and the data warehouse, where the database is concerned with transactions and queries, while the warehouse enables analytical reports and a decision support system. Since the data warehouse is oriented towards business analysis, its storage does not need to be promptly updated as is the case with the data in the associated relational database. Today, with hardware advancements and the advanced design of database management systems, the database and the data warehouse can be stored on the same data server (in the same data center). Such database management systems can separately handle the transactions and the analytical reports. The main users of data warehouse systems are big businesses (banks, telecoms, big retailers, e-commerce portals) and their potential use cases include consumers’ behavior prediction, product recommendations, fraud detection, future trends envisioning etc. Data warehouses are also used in medical/genomic research studies, since biomedical questions are usually complex, and numerous valuables and heterogeneous data are increasingly available to answer these questions. Data warehouses have also been applied to public institutions that offer e-government services, processing spatial data mostly collected from Geographical Information Systems (GIS). This edition covers topics from data warehouse technology aspects, as well as applications of data warehouses in the business sector, bio-medical domain and the public sector. Section 1 focuses on data warehouse technology, describing data warehouse design using process-oriented requirement analysis, data registration of domain names in the data warehouse construction task, comparative study of data warehouse design approaches, base analysis techniques in data qualities framework for data warehouses, and critical factors influencing the adoptions of a data warehouse. Section 2 focuses on data warehouse applications in the business sector, describing essential elements to support decision-making process in industries, data warehouse design for the detection of fraud in the supply chain, data load manifestation in process chains in SAP business warehouse, and big data usage in the marketing information system. Section 3 focuses on data warehouse applications in the bio-medical domain, describing building a health care data warehouse for cancer diseases, building an osteoporosis data warehouse in the osteoporosis community, complex queries on an integrative genomic and proteomic data warehouse, Truncatulix – a data warehouse for the legume community, and approaches to access biological data sources. Section 4 focuses on data warehouse applications in the public sector, describing data warehouse for leishmaniosis in Marrakech City, data warehouse technology and application in data center design for e-government, data warehouse use of geographic information system for ornamentals, and gossip management at universities using the big data warehouse model.
Автор: David W. Hyndman Название: Subsurface Hydrology - Data Integration for Properties and Processes ISBN: 0875904378 ISBN-13(EAN): 9780875904375 Издательство: Wiley Рейтинг: Цена: 124550.00 T Наличие на складе: Поставка под заказ. Описание: Published by the American Geophysical Union as part of the Geophysical Monograph Series, Volume 171.
Groundwater is a critical resource and the PrinciPal source of drinking water for over 1.5 billion people. In 2001, the National Research Council cited as a "grand challenge" our need to understand the processes that control water movement in the subsurface. This volume faces that challenge in terms of data integration between complex, multi-scale hydrologie processes, and their links to other physical, chemical, and biological processes at multiple scales.
Subsurface Hydrology: Data Integration for Properties and Processes presents the current state of the science in four aspects:
Approaches to hydrologie data integration
Data integration for characterization of hydrologie properties
Data integration for understanding hydrologie processes
Meta-analysis of current interpretations
Scientists and researchers in the field, the laboratory, and the classroom will find this work an important resource in advancing our understanding of subsurface water movement.
Автор: Ralph Hughes Название: Agile Data Warehousing for the Enterprise ISBN: 0123964644 ISBN-13(EAN): 9780123964649 Издательство: Elsevier Science Рейтинг: Цена: 41530.00 T Наличие на складе: Поставка под заказ. Описание:
Building upon his earlier book that detailed agile data warehousing programming techniques for the Scrum master, Ralph's latest work illustrates the agile interpretations of the remaining software engineering disciplines:
Requirements management benefits from streamlined templates that not only define projects quickly, but ensure nothing essential is overlooked.
Data engineering receives two new "hyper modeling" techniques, yielding data warehouses that can be easily adapted when requirements change without having to invest in ruinously expensive data-conversion programs.
Quality assurance advances with not only a stereoscopic top-down and bottom-up planning method, but also the incorporation of the latest in automated test engines.
Use this step-by-step guide to deepen your own application development skills through self-study, show your teammates the world's fastest and most reliable techniques for creating business intelligence systems, or ensure that the IT department working for you is building your next decision support system the right way.
Learn how to quickly define scope and architecture before programming starts
Includes techniques of process and data engineering that enable iterative and incremental delivery
Demonstrates how to plan and execute quality assurance plans and includes a guide to continuous integration and automated regression testing
Presents program management strategies for coordinating multiple agile data mart projects so that over time an enterprise data warehouse emerges
Use the provided 120-day road map to establish a robust, agile data warehousing program
Автор: Cox, Andrew Verbaan, Eddy Название: Exploring research data management ISBN: 178330278X ISBN-13(EAN): 9781783302789 Издательство: Facet Рейтинг: Цена: 88000.00 T Наличие на складе: Невозможна поставка. Описание: Exploring Research Data Management is an accessible introduction to RDM with engaging tasks for the reader to follow and build their knowledge. It will be useful reading for all students studying librarianship and information management.
Автор: David Griol Barres, Zoraida Callejas Carrion, Ramon Lopez-Cozar Delgado Название: Technologies for Inclusive Education: Beyond Traditional Integration Approaches ISBN: 1466625309 ISBN-13(EAN): 9781466625303 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 170010.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: By providing students with the opportunities to receive a high quality education regardless of their social or cultural background, inclusive education is a new area that goes beyond traditional integration approaches. These approaches hope to provide the educative system with the ability to adapt to the diversity of its students.Technologies for Inclusive Education: Beyond Traditional Integration Approaches introduces the basic concepts, current research guidelines and future perspectives on the current state of these approaches. This book aims to make inclusive education a reality in the future by highlighting technological advances in applied e-learning, cognitive learning and education multimedia. Novel approaches to human-computer interaction are essential to make these contents available for every student regardless of their disabilities and learning styles.
Автор: Jones Herbert Название: Data Science for Business: Predictive Modeling, Data Mining, Data Analytics, Data Warehousing, Data Visualization, Regression Analysis, Database ISBN: 1647483263 ISBN-13(EAN): 9781647483265 Издательство: Неизвестно Рейтинг: Цена: 27580.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Data science has a huge impact on how companies conduct business, and those who don`t learn about this revolutionaryfield could be left behind. You see, data science will help you make better decisions, know what products and services to release, and how to provide better service to your customers.
Автор: Wei Lee Woon; Zeyar Aung; Alejandro Catalina Feli? Название: Data Analytics for Renewable Energy Integration. Technologies, Systems and Society ISBN: 3030043029 ISBN-13(EAN): 9783030043025 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book constitutes the revised selected papers from the 6th ECML PKDD Workshop on Data Analytics for Renewable Energy Integration, DARE 2018, held in Dublin, Ireland, in September 2018.The 9 papers presented in this volume were carefully reviewed and selected for inclusion in this book and handle topics such as time series forecasting, the detection of faults, cyber security, smart grid and smart cities, technology integration, demand response, and many others.
Автор: Hu & Kaabouch Название: Big Data Management, Technologies, And Applications ISBN: 1466646993 ISBN-13(EAN): 9781466646995 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 170010.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Due to the tremendous amount of data generated daily from fields such as business, research, and sciences, big data is everywhere. Therefore, alternative management and processing methods have to be created to handle this complex and unstructured data size.Big Data Management, Technologies, and Applications discusses the exponential growth of information size and the innovative methods for data capture, storage, sharing, and analysis for big data. With its prevalence, this collection of articles on big data methodologies and technologies are beneficial for IT workers, researchers, students, and practitioners in this timely field.
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