As organizations' reliance on data increases, the prevalence of data analytics programs in universities likewise increases. However, despite this specialized education, scholars still report a gap between the knowledge and skills students graduate with and those required by industry upon beginning work as an entry-level data analyst. We draw on…

Research data services--support offerings which enable and improve data-intensive research--have garnered sustained attention from library research support service providers for nearly two decades. Libraries have played a leading role in developing research data services, and on most university campuses they provide the largest and most diverse…

Gas Turbine Engines (GTE) have the highest power-to-weight ratio among Internal Combustion Engines (ICE). Its modularity and ability to utilize various types of fuel make it highly recommended in power plants, naval transportation, and, of course, the most equipped in aviation. The lack of GTEs' real data is increasing a recognized need for…

Since 2013, DaSy has tracked the status of Part C and Part B 619 state data systems to understand states' technical assistance needs, provide stakeholders with a national picture of what capacities state data systems have, and to track how those capacities are changing over time. Most recently, in spring of 2021, DaSy collected comprehensive…

With recent advances in artificial intelligence (AI), machine learning (ML) has been identified as particularly useful for organizations seeking to create value from data. However, as ML is commonly associated with technical professions, such as computer science and engineering, incorporating training in the use of ML into non-technical…

Decision-making, a key factor of organizational performance, is based on information retrieved from processing raw data. As businesses and consumers are shifting toward digital channels, more and more data is being generated through digital services and electronic devices. Big Data is argued to have significant benefits to businesses, and yet data…

In order to better grasp the needs of library users and provide them with more accurate knowledge services, combining the characteristics of university libraries, this article applies library small data to personalized recommendation and proposes a small data fusion algorithm model for library personalized recommendation. This model combines the…

Coaching has been widely implemented to support the delivery of evidence-based practices in schools. Although coaching is effective in rigorous research studies, scholars question the effective translation of coaching in authentic schools. Data systems that monitor the fidelity and impact of coaching offer one solution to address three…

Understanding the nature of the "early teacher pipeline," how many and what types of individuals are pursuing a teaching credential, is critically important. Unfortunately, we conclude that the two national data collections that can be used to explore the early teacher pipeline provide an incomplete and contrasting pictures of the supply…

Research information management (RIM) is a rapidly growing area of investment in US research universities. RIM systems that support the collection and use of research outputs metadata have been in place for many years. Globally, the RIM ecosystem is quite mature in locales where national research assessment exercises like the United Kingdom's…

Research Information Management (RIM) is a rapidly growing area of investment in US research universities, comprised of a variety of use cases, stakeholders, and products. This growth has been characteristically decentralized, resulting in silos, multiple systems, and frequent duplication of efforts at many institutions. This report is a two-part…

Background: Knowledge brokering by intermediary organizations includes knowledge distillation processes (e.g., synthesis, translation). Aims and objectives: This article explores how an educational intermediary performs research distillation when creating virtual knowledge reservoirs for educators. Methods: The authors use qualitative data from…

The intensification of data collection practices in schooling -- often due to state accountability requirements -- has resulted in the widespread adoption of commercial student management systems (SMS) in schools. Drawing on a qualitative case study of a New Zealand primary school, this paper investigates its adoption of a commercial SMS, and the…

When the COVID-19 pandemic drove schools online in March 2020, state education leaders were left without access to data needed to understand how best to support students. The pandemic revealed the strengths and limitations of state education data systems while inspiring new strategies for collecting, reporting and using data. In 2021, DataSmith…

This article uses an anonymous 2014-15 school year dataset from the Directorate-General for Statistics of Education and Science (DGEEC) of the Portuguese Ministry of Education as a means to carry out a predictive power comparison between the classic multilinear regression model and a chosen set of machine learning algorithms. A multilinear…