Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
73,171
result(s) for
"Database Management Systems."
Sort by:
Oracle database upgrade, migration & transformation tips & techniques
\"This Oracle Press guide provides best practices for migrating between different operating systems and platforms, transforming existing databases to use different storage or enterprise systems, and upgrading databases from one release to the next. Based on the expert authors' real-world experience, Oracle Database Upgrade, Migration & Transformation Tips & Techniques will help you choose the best migration path for your project and develop an effective methodology. Code examples and detailed checklists are included in this comprehensive resource\"-- Provided by publisher.
Book
Business modeling and data mining
Business Modeling and Data Mining demonstrates how real world business problems can be formulated so that data mining can answer them. The concepts and techniques presented in this book are the essential building blocks in understanding what models are and how they can be used practically to reveal hidden assumptions and needs, determine problems, discover data, determine costs, and explore the whole domain of the problem. This book articulately explains how to understand both the strategic and tactical aspects of any business problem, identify where the key leverage points are and determine where quantitative techniques of analysis -- such as data mining -- can yield most benefit. It addresses techniques for discovering how to turn colloquial expression and vague descriptions of a business problem first into qualitative models and then into well-defined quantitative models (using data mining) that can then be used to find a solution. The book completes the process by illustrating how these findings from data mining can be turned into strategic or tactical implementations.
· Teaches how to discover, construct and refine models that are useful in business situations· Teaches how to design, discover and develop the data necessary for mining · Provides a practical approach to mining data for all business situations· Provides a comprehensive, easy-to-use, fully interactive methodology for building models and mining data· Provides pointers to supplemental online resources, including a downloadable version of the methodology and software tools.
eBook
Benchmarking transaction and analytical processing systems : the creation of a mixed workload benchmark and its application
Systems for Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP) are currently separate. The potential of the latest technologies and changes in operational and analytical applications over the last decade have given rise to the unification of these systems, which can be of benefit for both workloads. Research and industry have reacted and prototypes of hybrid database systems are now appearing. Benchmarks are the standard method for evaluating, comparing and supporting the development of new database systems. Because of the separation of OLTP and OLAP systems, existing benchmarks are only focused on one or the other. With the rise of hybrid database systems, benchmarks to assess these systems will be needed as well. Based on the examination of existing benchmarks, a new benchmark for hybrid database systems is introduced in this book. It is furthermore used to determine the effect of adding OLAP to an OLTP workload and is applied to analyze the impact of typically used optimizations in the historically separate OLTP and OLAP domains in mixed-workload scenarios.
Book
Data Sharing in the Post-Genomic World: The Experience of the International Cancer Genome Consortium (ICGC) Data Access Compliance Office (DACO)
ICGC and the Development of Controlled Access Policies Controlled access mechanisms may be viewed as the product of dual imperatives: 1) the legal and ethical requirements of regulators and research ethics committees, as well as research funders and study participants, to protect the confidentiality of data from re-identification and misuse by third parties; and 2) pressure, largely from within the science community, to protect data-producing investigators from acts of free riding by other members of the community (e.g., by ensuring they are properly acknowledged in publications and that no parasitic patents are deposited on the data by subsequent data users). Early models of databases having a two-tiered open/controlled access system included the database of Genotypes and Phenotypes (dbGaP) at the US National Institutes of Health (http://www.ncbi.nlm.nih.gov/gap), the Wellcome Trust Case Control Consortium (WTCCC) (http://www.wtccc.org.uk/), the Malaria Genomic Epidemiology Network (MalariaGEN) (http://www.malariagen.net/), and the European Genome-phenome Archive (EGA) (https://www.ebi.ac.uk/ega/).
Journal Article
Access® 2013 for dummies
The easy guide to Microsoft Access returns with updates on the latest version! Microsoft Access allows you to store, organize, view, analyze, and share data; the new Access 2013 release enables you to build even more powerful, custom database solutions that integrate with the web and enterprise data sources. Access 2013 For Dummies covers all the new features of the latest version of Accessand serves as an ideal reference, combining the latest Access features with the basics of building usable databases. You'll learn how to create an app from the Welcome screen, get support for your desktop databases, and much more. Includes coverage of all the new features of Access 2013, including the updated interface Shows you how to create and share reports Features special videos and materials created by the authors to help reinforce the lessons included in the book Helps you build data analysis and interface tools for your specific needs Offers plenty of techniques and tips for solving common problems Access 2013 For Dummies provides you with access to the latest version of this database tool.
eBook
Big data, data mining and machine learning
With big data analytics comes big insights into profitability
Big data is big business. But having the data and the computational power to process it isn't nearly enough to produce meaningful results. Big Data, Data Mining, and Machine Learning: Value Creation for Business Leaders and Practitioners is a complete resource for technology and marketing executives looking to cut through the hype and produce real results that hit the bottom line. Providing an engaging, thorough overview of the current state of big data analytics and the growing trend toward high performance computing architectures, the book is a detail-driven look into how big data analytics can be leveraged to foster positive change and drive efficiency.
With continued exponential growth in data and ever more competitive markets, businesses must adapt quickly to gain every competitive advantage available. Big data analytics can serve as the linchpin for initiatives that drive business, but only if the underlying technology and analysis is fully understood and appreciated by engaged stakeholders. This book provides a view into the topic that executives, managers, and practitioners require, and includes:
* A complete overview of big data and its notable characteristics
* Details on high performance computing architectures for analytics, massively parallel processing (MPP), and in-memory databases
* Comprehensive coverage of data mining, text analytics, and machine learning algorithms
* A discussion of explanatory and predictive modeling, and how they can be applied to decision-making processes
Big Data, Data Mining, and Machine Learning provides technology and marketing executives with the complete resource that has been notably absent from the veritable libraries of published books on the topic. Take control of your organization's big data analytics to produce real results with a resource that is comprehensive in scope and light on hyperbole.
eBook
Active In-Database Processing to Support Ambient Assisted Living Systems
As an alternative to the existing software architectures that underpin the development of smart homes and ambient assisted living (AAL) systems, this work presents a database-centric architecture that takes advantage of active databases and in-database processing. Current platforms supporting AAL systems use database management systems (DBMSs) exclusively for data storage. Active databases employ database triggers to detect and react to events taking place inside or outside of the database. DBMSs can be extended with stored procedures and functions that enable in-database processing. This means that the data processing is integrated and performed within the DBMS. The feasibility and flexibility of the proposed approach were demonstrated with the implementation of three distinct AAL services. The active database was used to detect bed-exits and to discover common room transitions and deviations during the night. In-database machine learning methods were used to model early night behaviors. Consequently, active in-database processing avoids transferring sensitive data outside the database, and this improves performance, security and privacy. Furthermore, centralizing the computation into the DBMS facilitates code reuse, adaptation and maintenance. These are important system properties that take into account the evolving heterogeneity of users, their needs and the devices that are characteristic of smart homes and AAL systems. Therefore, DBMSs can provide capabilities to address requirements for scalability, security, privacy, dependability and personalization in applications of smart environments in healthcare.
Journal Article