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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.

Effective data fragmentation is essential in enhancing the performance of distributed database management systems (DDBMS) by strategically dividing extensive databases into smaller fragments distributed across multiple nodes. This study emphasizes horizontal fragmentation and introduces an advanced machine learning algorithm, Red Fox Optimization-based Support Vector Machine (RFO-SVM), designed for optimizing the data fragmentation process. The input database undergoes meticulous pre-processing to address missing data concerns, followed by analysis through RFO-SVM. This algorithm efficiently classifies features and target labels based on class labels. The RFO algorithm optimizes critical SVM parameters, including the kernel, kernel parameter, and boundary parameter, leveraging the accuracy metric. The resulting classified data serves as fragments for the fragmentation process. To ensure precision in fragmentation, a Genetic Algorithm (GA) allocates these fragments to diverse nodes within the DDBMS, optimizing the total allocation cost as the fitness function. The proposed model, implemented in Python, significantly contributes to the efficient fragmentation and allocation of databases in distributed systems, thereby enhancing overall performance and scalability.

The cosmic-ray database, CRDB, has been gathering cosmic-ray data for the community since 2013. We present a new release, CRDB v4.1, providing many new quantities and data sets, with several improvements made on the code and web interface, and with new visualisation tools. CRDB relies on the MySQL database management system, jquery and table-sorter libraries for queries and sorting, and PHP web pages and AJAX protocol for displays. A REST interface enables user queries from command line or scripts. A new (pip-installable) CRDB python library is developed and extensive jupyter notebook examples are provided. This release contains cosmic-ray dipole anisotropy data, high-energy p ¯ / p upper limits, some unpublished LEE and AESOP lepton time series, many more ultra-high energy data, and a few missing old data sets. It also includes high-precision data from the last three years, in particular the hundreds of thousands AMS-02 and PAMELA data time series (time-dependent plots are now enabled). All these data are shown in a gallery of plots, which can be easily reproduced from the public notebook examples. CRDB contains 316,126 data points from 504 publications, in 4111 sub-experiments from 131 experiments.

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/).

Multi-omic integration involves the management of diverse omic datasets. Conducting an effective analysis of these datasets necessitates a data management system that meets a specific set of requirements, such as rapid storage and retrieval of data with varying numbers of features and mixed data-types, ensurance of reliable and secure database transactions, extension of stored data row and column-wise and facilitation of data distribution. SQLite and DuckDB are embedded databases that fulfil these requirements. However, they utilize the structured query language (SQL) that hinders their implementation by the uninitiated user, and complicates their use in repetitive tasks due to the necessity of writing SQL queries. This study offers Omilayers, a Python package that encapsulates these two databases and exposes a subset of their functionality that is geared towards frequent and repetitive analytical procedures. Synthetic data were used to demonstrate the use of Omilayers and compare the performance of SQLite and DuckDB.

Client-Server (C/S) application is always used in the existing Human Resource Management System (HRMS) as the system architecture, which has the problems of complex maintenance and poor compatibility; and cannot use professional database and development system, making the system development difficult and the data security low. To solve the above problems, the overall demand is analyzed, as well as feasibility and key technologies of the enterprise HRMS system. Then a HRMS is designed and developed, based on the user’s key functional requirements and related technologies, which is reasonable and easy to maintain. The system is supported by Browser-Server (B/S) structure, with the current popular Java 2 Platform Enterprise Edition (J2EE) multi-level structure as the overall architecture. The mature Microsoft SQL Server 2008 introduced by Microsoft is used as the database platform. Combined with Model View Controller (MVC) design pattern, this system can be used by users without geographical restrictions and system maintenance. In this system, performance logic and business logic are separated, which makes it convenient for the development and maintenance of the system. The system mainly includes six modules: personnel management, organizational management, recruitment management, training management, salary management and system management, which integrates enterprise information and realizes the functions of easy access and easy query of information database. Its interface is simple, easy to understand, and easy to operate, with low investment, low cost, high safety, good performance and easy maintenance, which help to improve the work efficiency and modern management level of enterprises. In the end, the operation performance of the system is tested. The results show that the throughput of the main functional modules in the system is greater than 100 times/s when dealing with the business, and the success rate of event processing is greater than 99%. The average response time of the business end is less than 0.4 s, and the average response time of the terminal side is less than 0.5 s, which all meet the standards. System CPU occupancy rate can be basically controlled below 30%, and memory usage rate is below 30%. In summary, the system designed here has the basic functions but also to ensure good performance, suitable for enterprise personnel management, organizational management, recruitment management, training management and salary management. The design and development of this system aims to provide technical support for the service quality of enterprise human resource management business, to improve the overall efficiency, promote the pace of enterprise strategic development, and enhance the market competitiveness of enterprises.

The expansion of a telescope network creates a thirst for more data-handling expertise and infrastructure. The expansion of a telescope network creates a thirst for more data-handling expertise and infrastructure.

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.

Recent advancements in data management highlight the increasing focus on large-scale integration and analytics, with the management of duplicate information becoming a more resource-intensive and costly task. Existing SQL and NoSQL systems inadequately address the semantic constraints of set-based data, either by compromising relational fidelity or through inefficient deduplication mechanisms. This paper presents a set-oriented centralized NoSQL database management system (DBMS) that enforces uniqueness by construction, thereby reducing downstream deduplication and enhancing result determinism. The system utilizes in-memory execution with binary serialized persistence, achieving O(1) time complexity for exact-match CRUD operations while maintaining ACID-compliant transactional semantics through explicit commit operations. A comparative performance evaluation against Redis and MongoDB highlights the trade-offs between consistency guarantees and latency. The results reveal that enforced set uniqueness completely eliminates duplicates, incurring only moderate latency trade-offs compared to in-memory performance measures. The model can be extended for fuzzy queries and imprecise data by retrieving the membership function information. This work demonstrates that the set-oriented DBMS design represents a distinct architectural paradigm that addresses data integrity constraints inadequately handled by contemporary database systems.

Cadastral databases have been used for over 20 years, but most contain 2D data. The increasing presence of high-rise buildings with modern architecture complicates the process of determining property rights, restrictions, and responsibilities. It is, therefore, necessary to develop an efficient system for storing and managing multidimensional cadastral data. While there have been attempts to develop 3D cadastral database schemas, a comprehensive solution that meets all the requirements for effective data storage, manipulation, and retrieval has not yet been presented. This study aims to analyse the literature on 3D cadastral databases to identify approaches and technologies for storing and managing these data. Based on a systematic literature review integrated with a snowballing methodology, 108 documents were identified. During the analysis of the related documents, different parameters were extracted, including the conceptual data model, query type, and evaluation metrics, as well as the database management system (DBMS) used and technologies for visualisation, data preparation, data transformation, and the ETL (extract, transform, and load) process. The study emphasised the importance of adhering to database design principles and identified challenges associated with conceptual design, DBMS selection, logical design, and physical design. The study results provide insights for selecting the appropriate standards, technologies, and DBMSs for designing a 3D cadastral database system.