KAISERSLAUTERN, Germany, Nov. 13, 2024 — ThinkParQ, the company behind the leading parallel file system BeeGFS, is thrilled to unveil BeeGFS 8, offering advanced capabilities aimed at enhancing performance, flexibility, and […]

The post ThinkParQ Unveils BeeGFS 8 at SC24, Bringing Advanced Data Management Tools to HPC and AI appeared first on HPCwire.

PRZOOM - Newswire (press release) - Tue, 12 Nov 2024 00:00:00 -0500, Leipzig Saxony Germany - eccenca, has announced a partnership with Semantic Partners, a premier consulting company specializing in consulting services for semantic technologies - SemanticPartners.com / eccenca.com

In the era of big data, enterprises have accumulated a large amount of research and development data. Effective management of their precipitated data and safe sharing of data can improve the collaboration efficiency of research and development personnel, which has become the top priority of enterprise development. This paper proposes to use blockchain technology to assist the collaboration efficiency of enterprise R&D personnel. Firstly, the multi-chain blockchain platform is used to realise the data sharing of internal data of enterprise R&D data department, project internal data and enterprise data centre, and then the process of construction of multi-chain structure and data sharing is analysed. Finally, searchable encryption was introduced to achieve data retrieval and secure sharing, improving the collaboration efficiency of enterprise research and development personnel and maximising the value of data assets. Through the experimental verification, the multi-chain structure improves the collaboration efficiency of researchers and data security sharing.

Big data management is a reality for an increasing number of organizations in many areas and represents a set of challenges involving big data modeling, storage and retrieval, analysis and visualization. However, technological resources, people and processes are crucial to facilitate the management of big data in any kind of organization, allowing information and knowledge from a large volume of data to support decision-making. Big data management can be supported by these three dimensions: technology, people and processes. Hence, this article discusses these dimensions: the technological dimension that is related to storage, analytics and visualization of big data; the human aspects of big data; and, in addition, the process management dimension that involves in a technological and business approach the aspects of big data management.

Aim/Purpose: The use of digital technology, such as an electronic records management system (ERMS), has prompted widespread changes across organizations. The organization needs to support its operations with an automation system to improve production performance. This study investigates ERMS’s potentiality to enhance organizational performance in the oil and gas industry. Background: Oil and gas organizations generate enormous electronic records that lead to difficulties in managing them without any system or digitalization procedure. The need to use a system to manage big data and records affects information security and creates several problems. This study supports decision-makers in oil and gas organizations to use ERMS to enhance organizational performance. Methodology: We used a quantitative method by integrating the typical partial least squares (SEM-PLS) approach, including measurement items, respondents’ demographics, sampling and collection of data, and data analysis. The SEM-PLS approach uses a measurement and structural model assessment to analyze data. Contribution: This study contributes significantly to theory and practice by providing advancements in identity theory in the context of big data management and electronic records management. This study is a foundation for further research on the role of ERMS in operations performance and Big Data Management (BDM). This research makes a theoretical contribution by studying a theory-driven framework that may serve as an essential lens to evaluate the role of ERMS in performance and increase its potentiality in the future. This research also evaluated the combined impacts of general technology acceptance theory elements and identity theory in the context of ERMS to support data management. Findings: This study provides an empirically tested model that helps organizations to adopt ERMS based on the influence of big data management. The current study’s findings looked at the concerns of oil and gas organizations about integrating new technologies to support organizational performance. The results demonstrated that individual characteristics of users in oil and gas organizations, in conjunction with administrative features, are robust predictors of ERMS. The results show that ERMS potentiality significantly influences the organizational performance of oil and gas organizations. The research results fit the big ideas about how big data management and ERMS affect respondents to adopt new technologies. Recommendations for Practitioners: This study contributes significantly to the theory and practice of ERMS potentiality and BDM by developing and validating a new framework for adopting ERMS to support the performance and production of oil and gas organizations. The current study adds a new framework to identity theory in the context of ERMS and BDM. It increases the perceived benefits of using ERMS in protecting the credibility and authenticity of electronic records in oil and gas organizations. Recommendation for Researchers: This study serves as a foundation for future research into the function and influence of big data management on ERMS that support the organizational performance. Researchers can examine the framework of this study in other nations in the future, and they will be able to analyze this research framework to compare various results in other countries and expand ERMS generalizability and efficacy. Impact on Society: ERMS and its impact on BDM is still a developing field, and readers of this article can assist in gaining a better understanding of the literature’s dissemination of ERMS adoption in the oil and gas industry. This study presents an experimentally validated model of ERMS adoption with the effect of BDM in the oil and gas industry. Future Research: In the future, researchers may be able to examine the impact of BDM and user technology fit as critical factors in adopting ERMS by using different theories or locations. Furthermore, researchers may include the moderating impact of demographical parameters such as age, gender, wealth, and experience into this study model to make it even more robust and comprehensive. In addition, future research may examine the significant direct correlations between human traits, organizational features, and individual perceptions of BDM that are directly related to ERMS potentiality and operational performance in the future.

The Brazilian initiative PPBio (The Program for Research on Biodiversity) launches a new book based on over a decade of experience in implementing the biodiversity monitoring system RAPELD in the Brazilian Amazon. Richly illustrated and written in simple language, the book "Biodiversity and Integrated Environmental Monitoring" addresses the issues that led to the system development, covering topics such as the spatial organization and representation of biological diversity, environmental monitoring, and data management.

Monitoring of biodiversity is not merely an academic endeavor. Although scientific aspects such as representation of biodiversity and biodiversity data integration, management and preservation are of a great importance, it is also essential to think about the political context in which decisions will be made and how to incorporate political stakeholders and decision makers.

"As this important book makes clear questions about biodiversity are far from purely scientific. Biodiversity matters. Our needs to assess it embed in a complex of questions posed by managers, policy makers and those who live in or otherwise benefit from biodiversity.",  explains Dr Stuart L. Pimm in the preface of the book. "So how do we ensure that data collected now will be useful for purposes we cannot yet imagine at some unexpected time in the future? Or provide comparison to some other place that we might survey some day?"

Those and many more questions regarding biodiversity data management and policy involvement are discussed in the new book "Biodiversity and Integrated Environmental Monitoring".

It has been recognized that issues regarding the sustainability and interoperability of data collected by citizens hinder the re-usability and integration of these data across borders. The European Commission’s Joint Research Centre (JRC), is following up on these findings with a detailed study of interoperability arrangements, hosting and data management practices of Citizen Science projects. These activities include a survey designed to capture the state of play with regard to data management practices on the local, national and continental scales. The questions are especially inspired by the recently proposed data management principles of the Group on Earth Observations and those of the Belmont Forum.

Beyond the pure stocktaking and awareness raising, the results should establish a base line for prioritizing follow-up activities and measuring progress. The results will also inform the discussion on the potential roles of the European Commission – and especially the JRC – in Citizen Science.

After discussions with members of the European Citizen Science Association (ECSA) and the international Citizen Science Association (CSA), it was decided to open the scope of the questionnaire to the international community, so that non-EU and globally acting organizations could also benefit from the outcomes.

The survey will be open until 31 August 2015, and the results of the subsequent analysis will be available by the end of September.  We invite all those involved in Citizen Science projects to take the survey in order to provide us with invaluable information and insight into Citizen Science projects and best practice.

Take the Survey! >> https://ec.europa.eu/eusurvey/runner/CSDataManagement

This white paper assesses the significance of OHS data, analyzes current performance in the domain, identifies significant trends, and proposes interventions to address concerns and enhance overall performance.

In recent years, China's advanced light sources have entered a period of rapid construction and development. As modern X-ray detectors and data acquisition technologies advance, these facilities are expected to generate massive volumes of data annually, presenting significant challenges in data management and utilization. These challenges encompass data storage, metadata handling, data transfer and user data access. In response, the Data Organization Management Access Software (DOMAS) has been designed as a framework to address these issues. DOMAS encapsulates four fundamental modules of data management software, including metadata catalogue, metadata acquisition, data transfer and data service. For light source facilities, building a data management system only requires parameter configuration and minimal code development within DOMAS. This paper firstly discusses the development of advanced light sources in China and the associated demands and challenges in data management, prompting a reconsideration of data management software framework design. It then outlines the architecture of the framework, detailing its components and functions. Lastly, it highlights the application progress and effectiveness of DOMAS when deployed for the High Energy Photon Source (HEPS) and Beijing Synchrotron Radiation Facility (BSRF).

Most scientific facilities produce large amounts of heterogeneous data at a rapid pace. Managing users, instruments, reports and invoices presents additional challenges. To address these challenges, EMhub, a web platform designed to support the daily operations and record-keeping of a scientific facility, has been introduced. EMhub enables the easy management of user information, instruments, bookings and projects. The application was initially developed to meet the needs of a cryoEM facility, but its functionality and adaptability have proven to be broad enough to be extended to other data-generating centers. The expansion of EMHub is enabled by the modular nature of its core functionalities. The application allows external processes to be connected via a REST API, automating tasks such as folder creation, user and password generation, and the execution of real-time data-processing pipelines. EMhub has been used for several years at the Swedish National CryoEM Facility and has been installed in the CryoEM center at the Structural Biology Department at St. Jude Children's Research Hospital. A fully automated single-particle pipeline has been implemented for on-the-fly data processing and analysis. At St. Jude, the X-Ray Crystallography Center and the Single-Molecule Imaging Center have already expanded the platform to support their operational and data-management workflows.

The capabilities of data are expanding and revolutionizing with each passing day. It is important for technology business leaders to stay updated on the top data trends and use data more efficiently to improve their existing business models.

Confluent chief Jay Kreps says compliance can be challenging and lead to scrutiny of data movements. “Streaming technology enables the real-time synchronization of data, connecting all these disparate sources. An apt analogy is that of a central nervous system. The capability to unify data streams from different organizational segments empowers better decision making and the creation of personalized customer experiences,” he said.

Moisey Levit is recognized for over 15 years of professional experience in his industry

Tracy Mae Sowa-Wagner is the Director of Clinical Data Management for Caidya

eQuorum Announces Release of Version 12.1

Beyond Key's Snowflake Consulting Services: Empowering Businesses with Data Excellence - A Game-Changer in Data Management and Analytics.

Miroslav Lozinsky lends years of expertise to his work with Allight Solutions LLC

Tamer H. Chowdhury recognized for 25 years assisting in data management for clinical trials

RobobAI Chief Technology Officer Dave Curtis shares how large organizations can accelerate growth potential with data

FonePaw WhatsApp Transfer:Transfer WhatsApp Data Between Android and iOS

Caldic will work with Syniti to help future-proof its data landscape and optimize data quality

Arcitecta extends its reach to the museum and cultural asset market

Versium's Dedupe allows users to compare data points across various fields

Pat Helland talks to host Akshay Manchale about Data Management at scale in a Microservices world. Pat talks about trends in managaging data in a distributed microservices world, immutability, idempotence, inside and outside data, descriptive...

Requirements for data management in the telecommunication management network

Requirements for distributed ledger technology-based power grid data management

No matter what your brand's level of marketing maturity is, SAS can help you move from data to insight to action with rich functionality for adaptive planning, journey activation and an embedded real-time decision engine – all fueled by powerful analytics and artificial intelligence (AI) capabilities. Let's begin with a [...]

SAS Customer Intelligence 360: Introduction to marketing data management was published on Customer Intelligence Blog.

Decision makers need to analyze, exchange, and disseminate statistical information effectively in today’s data-driven world. See how Statistical Data and Metadata eXchange (SDMX) standards are helping create robust data links across the globe.

Synology has officially introduced its Enterprise Solution Blueprint in India for the first time, marking a significant step in the company’s efforts to expand into the Indian enterprise market. The announcement comes as Synology reports impressive growth, with business sector revenue

Over the last few months, we’ve been making substantial improvements to the ARIA-AT app, from backend database work to performance improvements, to making the app generally nicer to use. One of these improvements is the ability to view the Data Management Page without being logged in. The Data Management page allows visitors to view the […]

IEEE Computer Society

Poor data quality and integration can cause a marketing mess.

I-ON Communications developed a simple and user-friendly spreadsheet-like interface that lets you organize an entire phone address book with just a few clicks.

Businesses typically use data for all sort of things, from inventory management to analysing figures for salaries and everything else. It is data that drives businesses and the way it is handled governs their ROI.

Fluree platform was selected to provide secure communications using an encrypted, distributed, blockchain-backed graph database shared between partners

A method and computer-readable storage media are provided for rearranging data in physical memory units. In one embodiment, a method may include monitoring utilization counters. The method may further include, comparing the utilization counters for a match with an instance in a first table containing one or more instances when data may be rearranged in the physical memory units. The table may further include where the data should be relocated by a rearrangement. The method may also include, continuing to monitor the utilization counters if a match is not found with an instance in the first table. The method may further include, rearranging the data in the physical memory units if a match between the utilization counters and an instance in the first table is found.

The techniques described herein implement an operating system that can reliably process time sensitive information in non real-time manner. Thus, the operating system described herein is capable of processing an instance of time sensitive input during a time period after the instance of time sensitive input is received (e.g., at a future point in time). To accomplish this, the techniques timestamp each instance of time sensitive input when it is received at a device. The techniques then store the timestamped instance of time sensitive input in a temporary queue, and make the timestamped instance available to the operating system at a time period after the time period when it is received, as indicated by the timestamp. Additional techniques described herein prioritize the activation of a driver configured to receive the time sensitive information during a boot sequence or a reboot sequence.

A disk array device comprises a first storage unit that stores encrypted user data, a second storage unit that is different from the first storage unit and locks and stores configuration information including a first encrypted authentication key that unlocks the encrypted user data, a management unit that includes a decoder that decodes the first encrypted authentication key and a control unit that unlocks the locked configuration information using a second authentication key, the management unit managing data using the first and second authentication keys. the management unit includes a configuration information recovery portion that unlocks the locked configuration information by using the second authentication key and recovers the configuration information during booting and a user data unlocking portion that decodes the first encrypted authentication key included in the configuration information and unlocks the encrypted user data stored in the first storage unit by using the first decoded authentication key.

Surprise! The data team does more than you think to implement certain legislative actions.

The post Why data management protocols are key to implementing legislative actions appeared first on The Data Roundtable.

Nancy Rausch shares 4 examples of the role data management techniques play in responding to COVID-19.

The post The role of data management techniques during COVID-19: 4 examples appeared first on The Data Roundtable.

A new report from Navigant Research released this week says that revenue from device and data management technologies could grow from approximately $14.8 billion in 2018 to more than $22.1 billion in 2027 at a compound annual growth rate (CAGR) of 4.6%.

A new report from Navigant Research released this week says that revenue from device and data management technologies could grow from approximately $14.8 billion in 2018 to more than $22.1 billion in 2027 at a compound annual growth rate (CAGR) of 4.6%.

A new report from Navigant Research released this week says that revenue from device and data management technologies could grow from approximately $14.8 billion in 2018 to more than $22.1 billion in 2027 at a compound annual growth rate (CAGR) of 4.6%.

Company: Golden Opportunities Private Limited
Experience: 4 to 10
location: Bengaluru / Bangalore, Hyderabad / Secunderabad
Ref: 24826365
Summary: We have an immediate opening in one of the Best MNC's in India for the Role of "Clinical Data Management" for Hyderabad and Bengaluru Location having the largest....

Company: Golden Opportunities Private Limited
Experience: 3 to 12
location: Mumbai
Ref: 24825731
Summary: Graduates with 3+ years of relevant experience in Employee Data Management from International BPO operations only.

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