Enterprise search projects start with intentions to provide ?Google for our organization' but too often fail to deliver on that promise. In our experience, these projects fail due to a lack of sustained effort and governance. The commercialization of next-generation search technologies allows you to fulfill this promise if you take a systematic approach to implementation.

Data Stack Evolution: Legacy Challenges and AI Innovation, a global report which included a survey of 775 manufacturing and supply chain IT decision-makers, found that almost three in five (58%) said their data leadership and IT teams work in silo.

when personal Investment is matured, can we show as capital as the amount directly credited into sole propertiorship current account

This week we read Acts 6:1-7, the story of the selection of the first deacons, in light of Ephesians 4:10-13, Exodus 18:19-21, Numbers 17 and Deuteronomy 34:9. We rejoice in the wonder of how authority works in the Church, with every member given the Holy Spirit, while we offer our leaders special honor as they help us on the road to full maturity in Christ.

Background/Aim/Purpose: A commonly implemented software process improvement framework is the capability maturity model integrated (CMMI). Existing literature indicates higher levels of CMMI maturity could result in a loss of agility due to its organizational focus. To maintain agility, research has focussed attention on agile maturity models. The objective of this paper is to find the common research themes and conclusions in agile maturity model research. Methodology: This research adopts a systematic approach to agile maturity model research, using Google Scholar, Science Direct, and IEEE Xplore as sources. In total 531 articles were initially found matching the search criteria, which was filtered to 39 articles by applying specific exclusion criteria. Contribution:: The article highlights the trends in agile maturity model research, specifically bringing to light the lack of research providing validation of such models. Findings: Two major themes emerge, being the coexistence of agile and CMMI and the development of agile principle based maturity models. The research trend indicates an increase in agile maturity model articles, particularly in the latter half of the last decade, with concentrations of research coinciding with version updates of CMMI. While there is general consensus around higher CMMI maturity levels being incompatible with true agility, there is evidence of the two coexisting when agile is introduced into already highly matured environments. Future Research: Future research direction for this topic should include how to attain higher levels of CMMI maturity using only agile methods, how governance is addressed in agile environments, and whether existing agile maturity models relate to improved project success.

Aim/Purpose: This research aims to develop an information technology (IT) maturity model for incident management (IM) process that merges the most known IT frameworks’ practices. Our proposal intends to help organizations overcome the current limitations of multiframework implementation by informing organizations about frameworks’ overlap before their implementation. Background: By previously identifying frameworks’ overlaps it will assist organizations during the multi-framework implementation in order to save resources (human and/or financial). Methodology: The research methodology used is design science research (DSR). Plus, the authors applied semi-structured interviews in seven different organizations to demonstrate and evaluate the proposal. Contribution: This research adds a new and innovative artefact to the body of knowledge. Findings: The proposed maturity model is seen by the practitioners as complete and useful. Plus, this research also reinforces the frameworks’ overlap issue and concludes that some organizations are unaware of their actual IM maturity level; some organizations are unaware that they have implemented practices of other frameworks besides the one that was officially adopted. Recommendations for Practitioners: Practitioners may use this maturity model to assess their IM maturity level before multi-framework implementation. Moreover, practitioners are also incentivized to communicate further requirements to academics regarding multi-framework assessment maturity models. Recommendation for Researchers: Researchers may explore and develop multi-frameworks maturity models for the remaining processes of the main IT frameworks. Impact on Society: This research findings and outcomes are a step forward in the development of a unique overlapless maturity model covering the most known IT frameworks in the market thus helping organizations dealing with the increasing frameworks’ complexity and overlap. Future Research: Overlapless maturity models for the remaining IT framework processes should be explored.

Aim/Purpose: The aim of this study is to identify Critical Success Factors (CSF) of Business Intelligence (BI) and provide a framework to classify CSF into layers or perspectives using an enterprise architecture approach, then rank CSF within each perspective and evaluate the importance of each perspective at different BI maturity levels as well. Background: Although the implementation of the BI project has a significant impact on creating analytical and competitive capabilities, the lack of evaluation of CSF holistically is still a challenge. Moreover, the BI maturity level of the organization has not been considered in the BI implementation project. Identifying BI critical success factors and their importance can help the project team to move to a higher maturity level in the organization. Methodology: First, a list of distinct CSF is identified through a literature review. Second, a framework is provided for categorizing these CSF using enterprise architecture. Interviewing is the research method used to evaluate the importance of CSF and framework layers with two questionnaires among experts. The first questionnaire was done by Analytical Hierarchy Process (AHP), a quantitative method of decision-making to calculate the weight of the CSF according to the importance of CSF in each of the framework layers. The second one was conducted to evaluate framework layers at different BI maturity levels using a Likert scale. Contribution: This paper contributes to the implementation of BI projects by identifying a comprehensive list of CSF in the form of a holistic multi-layered framework and ranking the importance of CSF and layers at BI maturity levels. Findings: The most important CSF in BI implementation projects include senior management support, process identification, data quality, analytics quality, hardware quality, security standards, scope management, documentation, project team skills, and customer needs transformation, which received the highest scores in framework layers. In addition, it was observed that as the organization moves to higher levels of maturity, the average importance of strategic business and security perspectives or layers increases. But the average importance of data, applications, infrastructure, and network, the project management layers in the proposed framework is the same regardless of the level of business intelligence maturity. Recommendations for Practitioners: The results of this paper can be used by academicians and practitioners to improve BI project implementation through understanding a comprehensive list of CSF and their importance. This awareness causes us to focus on the most important CSF and have better planning to reach higher levels of maturity according to the maturity level of the organization. Future Research: For future research, the interaction of critical success factors of business intelligence and framework layers can be examined with different methods.

Aim/Purpose: Using the Agile Adoption Framework (AAF), this study aims to examine the agile potential of software development companies in Nepal based on their agile maturity level. In addition, this study also examines the impact of various basic agile practices in determining the maturity level of the agile processes being implemented in the software industry of Nepal. Background: Even if most organizations in the software sector utilize agile development strategies, it is essential to evaluate their performance. Nepal’s software industry did not adopt agile techniques till 2014. The Nepalese industry must always adapt to new developments and discover ways to make software development more efficient and beneficial. The population of the study consists of 1,500 and 2,000 employees of software companies in Nepal implementing agile techniques. Methodology: The sample size considered was 150 employees working in software companies in Nepal. However, only 106 respondents responded after three follow-ups. The sample was collected with purposive sampling. A questionnaire was developed to gain information on Customer Adaptive, Customer Collaboration, Continuous Delivery, Human Centric, and Technical Excellence related to agile practices along with the Agile Maturity Level. Contribution: This research contributes to the understanding of agile practices adopted in software companies in developing countries like Nepal. It also reveals the determinants of the agility of software companies in developing countries. Findings: The results suggest that some of the basic principles of agile have a very significant role in Agile Maturity Level in the Nepali context. In the context of Nepal, human-centered practices have a very high level of correlation, which plays a vital role as a major predictor of the agile maturity level. In addition, Technical Excellence is the variable that has the highest level of association with the Agile Maturity Level, making it the most significant predictor of this quality. Recommendations for Practitioners: As Nepali software companies are mostly offshore or serve outsourcing companies, there is a very thin probability of Nepali developers being able to interact with actual clients and this might be one of the reasons for the Nepali industry not relying on Customer Adaptation and Collaboration as major factors of the Agile methodologies. Continuous Delivery, on the other hand, has a significant degree of correlation with Agile Maturity Level. Human-centric practices have a very high level of correlation as well as being a major predictor in determining the Agile Maturity Level in the context of Nepal. Technical Excellence is the most significant predictor and the variable which has the highest level of correlation with Agile Maturity Level. Practitioners should mainly focus on technical excellence as well as human-centric practices to achieve a higher level of Agile Maturity. Recommendation for Researchers: There has not been any such research in the Nepali context that anyone could rely on, to deep dive into their organizational concerns regarding agile strategies and plans. Researchers will need to focus on a more statistical approach with data-driven solutions to the issues related to people and processes. Researchers will need to cover freelancers as well as academics to get a different perspective on what can be the better practices to achieve a higher level of agile maturity. Impact on Society: This study on Agile work is accessible not only to the software industry but also to the general public. The Agile technique has had a huge impact on society’s project management. It has revolutionized how teams approach project planning, development, and execution. The paper’s findings will further information regarding the Agile methodology, which emphasizes collaboration and communication, fosters teamwork and higher quality work, and promotes the exchange of knowledge, ideas, and the pursuit of common goals. Future Research: Owing to the limitations of this study, it is necessary to analyze agile practices in the Nepalese software sector using additional factors that influence agile maturity. The conclusion that years of agile experience do not serve as a balancing factor for both agile practices and the Agile Maturity Level requires additional research. Whether a software outsourcing firm or not, the organization type had no bearing on the degree of maturity of agile methods; this leaves space for further research.

Aim/Purpose: While existing literature has extensively explored factors influencing the success of big data projects and proposed big data maturity models, no study has harnessed machine learning to predict project success and identify the critical features contributing significantly to that success. The purpose of this paper is to offer fresh insights into the realm of big data projects by leveraging machine-learning algorithms. Background: Previously, we introduced the Global Big Data Maturity Model (GBDMM), which encompassed various domains inspired by the success factors of big data projects. In this paper, we transformed these maturity domains into a survey and collected feedback from 90 big data experts across the Middle East, Gulf, Africa, and Turkey regions regarding their own projects. This approach aims to gather firsthand insights from practitioners and experts in the field. Methodology: To analyze the feedback obtained from the survey, we applied several algorithms suitable for small datasets and categorical features. Our approach included cross-validation and feature selection techniques to mitigate overfitting and enhance model performance. Notably, the best-performing algorithms in our study were the Decision Tree (achieving an F1 score of 67%) and the Cat Boost classifier (also achieving an F1 score of 67%). Contribution: This research makes a significant contribution to the field of big data projects. By utilizing machine-learning techniques, we predict the success or failure of such projects and identify the key features that significantly contribute to their success. This provides companies with a valuable model for predicting their own big data project outcomes. Findings: Our analysis revealed that the domains of strategy and data have the most influential impact on the success of big data projects. Therefore, companies should prioritize these domains when undertaking such projects. Furthermore, we now have an initial model capable of predicting project success or failure, which can be invaluable for companies. Recommendations for Practitioners: Based on our findings, we recommend that practitioners concentrate on developing robust strategies and prioritize data management to enhance the outcomes of their big data projects. Additionally, practitioners can leverage machine-learning techniques to predict the success rate of these projects. Recommendation for Researchers: For further research in this field, we suggest exploring additional algorithms and techniques and refining existing models to enhance the accuracy and reliability of predicting the success of big data projects. Researchers may also investigate further into the interplay between strategy, data, and the success of such projects. Impact on Society: By improving the success rate of big data projects, our findings enable organizations to create more efficient and impactful data-driven solutions across various sectors. This, in turn, facilitates informed decision-making, effective resource allocation, improved operational efficiency, and overall performance enhancement. Future Research: In the future, gathering additional feedback from a broader range of big data experts will be valuable and help refine the prediction algorithm. Conducting longitudinal studies to analyze the long-term success and outcomes of Big Data projects would be beneficial. Furthermore, exploring the applicability of our model across different regions and industries will provide further insights into the field.

Digital solutions have substantially contributed to the growth and dissemination of education. The distance education modality has been presented as an opportunity for worldwide students in many types of courses. However, projects of digital educational platforms require different expertise including knowledge areas such as pedagogy, psychology, computing, and digital technologies associated with education that allow the correct development and application of these solutions. To support the evolution of such solutions with satisfactory quality indicators, this research presents a model focused on quality of online educational solutions grounded in an approach aimed to continuous process improvement. The model considers of three maturity levels and six common entities that address the specific practices for planning and developing digital educational solutions, targeting quality standards that satisfy their users, such as students, teachers, tutors, and other people involved in development and use of these kinds of educational solutions.

Children's Geographies; 08/01/2023
(AN 167303406); ISSN: 14733285
Academic Search Premier

The new index advances safety management by providing a scalable, actionable framework based on leading indicators to enhance safety outcomes across global supply chains.

How can you scale an engineering organization when you haven’t already experienced rapid growth? Jean-Denis Greze of Plaid explains how to proactively enhance team capabilities and readiness by “leveling up” through a maturity map.

Business Design. Een up-and-coming discipline. En dat is niet vreemd. De opkomst van Business Design kun je niet los zien van het huidige business klimaat. Technologische en sociale ontwikkelingen volgen elkaar in hoog tempo op. Er is simpelweg geen tijd meer om eindeloos te sleutelen aan producten en diensten voordat ze naar de markt gaan. […]

ABSTRACTIntroduction:Since the health information system (HIS) in public health care services in Serbia was introduced in 2009, it has gradually expanded. However, it is unclear how well the HIS components have developed and the whole system’s stage of maturity.Method:In June–September 2021, a maturity assessment of the Serbian HIS was conducted for the first time using the HIS Stages of Continuous Improvement (SOCI) toolkit. The toolkit measures HIS status across 5 HIS domains: leadership and governance, management and workforce, information and communication technology (ICT), standards and interoperability, and data quality and use. The domains were further divided into 13 components and 39 subcomponents whose maturity stage was assessed on a 5-point Likert scale, indicating the level of development: (1) emerging/ad hoc; (2) repeatable; (3) defined; (4) managed; and (5) optimized. The toolkit was applied in a working group of 32 professionals and experts who were engaged in developing the new national eHealth strategy and action plan.Results:The overall maturity score of the Serbian HIS was 1.6, which indicates a low level. The highest baseline score (2) was given to the standards and interoperability domain, and the lowest (1.1) was given to ICT infrastructure. The remaining 3 domains (leadership and governance, Management and Workforce, and Data Quality and Use) were similarly rated (1.7, 1.7, and 1.6, respectively).Conclusion:A baseline assessment of the maturity level of Serbian HIS indicates that the majority of components are between the emerging/ad hoc stage and repeatable, which represent isolated, ad hoc efforts, with some basic processes in place and existing and accessible policies. This exercise provided an opportunity to address identified weaknesses in the upcoming national eHealth strategy.

The diagnosis of maturity-onset diabetes of the young (MODY), a monogenic form of diabetes mellitus caused by a mutation in a single gene, is often uncertain until genetic testing is performed. We report a 13-yr-old Korean boy who was initially diagnosed with type 2 diabetes (T2DM). MODY was suspected because of his nonobese body habitus and family history of multiple affected members. Targeted panel sequencing of all MODY-related genes was performed using the NextSeq 550Dx platform (Illumina). Sanger sequencing was performed using blood samples from the parents, siblings, and other relatives. A frameshift variant in the 3' region of the last exon of PDX1 was detected in the patient and his family members with diabetes. PP1_Moderate criterion was applied and this variant was confirmed to be the genetic cause of diabetes in the family and classified as likely pathogenic. The study highlights the importance of genetic testing for nonobese, early-onset diabetic patients with multiple affected family members. Increased awareness and aggressive genetic testing for MODY are needed.

'Hina Khan is bossy.''Sapna is playing a smart game.''Hiten has maintained his class and dignity.'

National Bureau of Economic Research

Austin Burton announced last week he's transferring from UCLA to Purdue. He'll be a graduate transfer with two years of eligibility.

Would you like to know how planets effect you without even knowing your horoscope?

Inspirational Messages of Love, Hope & Faith That Will Take You On An Enlightening Journey To Discovering The Gift of Tapping Into Your Spirit and Awakening Your SOUL!

Enterprise search projects start with intentions to provide ?Google for our organization' but too often fail to deliver on that promise. In our experience, these projects fail due to a lack of sustained effort and governance. The commercialization of next-generation search technologies allows you to fulfill this promise if you take a systematic approach to implementation.

Where unit-linked policies mature and fund value is to be paid in lumpsum, Life Insurers may offer staggered settlement option to policyholders. This onetime option is regardless of whether such option exists or not in the specific product.

Here at last is the complete bible for those who never wish to grow up. A massive collection of all the useless tricks, facts and gags that make life worth living.

Austin Burton announced last week he's transferring from UCLA to Purdue. He'll be a graduate transfer with two years of eligibility.

Preterm infants are at a high risk for retinopathy of prematurity (ROP). Several postnatal factors are well known to be associated with ROP. However, the relationships between antenatal or maternal risk factors and ROP are poorly understood.

This study used a large cohort database to study the influence of maternal gestational hypertension and preeclampsia on ROP in preterm infants. The results showed that preeclampsia, but not gestational hypertension, was associated with a reduced risk of ROP in preterm births. (Read the full article)

Extreme prematurity is a well-established cause of cognitive and motor impairment. There is some evidence that late prematurity and modifiable maternal attributes may negatively influence scholastic achievement, including standardized test performance.

We found that preterm birth significantly increases risk of first-grade failure rate even when the birth is just a few weeks before term gestation. Low maternal education status compounds the effect of prematurity. (Read the full article)

Previous studies examining developmental outcomes associated with late preterm and early term birth have shown mixed results. Many of these studies did not fully take into account the role of the social environment in child development.

Social factors, not late preterm or early term birth, were the strongest predictors of poor developmental outcomes at 2 to 3 and 4 to 5 years. The influence of mild prematurity may lose strength beyond the neonatal period. (Read the full article)

It is known that trisomy 21 decreases the risk of (nonocular) angiogenic-mediated disorders, such as solid tumors. It is not known whether trisomy 21 decreases the risk of ocular angiogenic-mediated disorders such as retinopathy of prematurity.

This study shows that trisomy 21 decreases the risk of retinopathy of prematurity (ROP), thus unmasking a potentially identifiable genetic component to ROP risk. This study paves the way for the future development of a laboratory-based ROP screening tool. (Read the full article)

The STOP-ROP Multicenter Study Group
Feb 1, 2000; 105:295-310
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