Text analytics and natural language processing are not new concepts. Most knowledge management professionals have been grappling with these technologies for years. From the KM perspective, these technologies share the same fundamental purpose: They help get the right information to employees at the right time.

The Royal Melbourne Institute of Technology (RMIT), in collaboration with NICTA (National ICT Australia) have announced the opening of a joint data analytics lab in Victoria. The lab will be based at RMIT University’s School of Computer Science & Information (CSIT) in Melbourne. NICTA is Australia’s largest ICT organisation, and its Machine Learning Research Group has been independently rated amongst the top five groups of its kind in the world. In a collaboration valued at over A$1 million, NICTA will combine its expertise with RMIT University’s CSIT, which is widely recognised as a leader in data and information management.

Teradata's capabilities make it ideal for handling complex, high-volume workloads, while Snowflake's flexibility offers a scalable cloud solution.

1. iPhone SE 4 Camera Production Set to Begin Ahead of March 2025 Launch, Report Reveals  Analytics Insight
2. iPhone SE 4 leaks: 7 big upgrades  India Today
3. Apple iPhone SE 4 to launch next year, likely to become the cheapest iPhone to support Apple Intelligence...  Moneycontrol
4. iPhone SE 4 Camera Production to Begin Soon Ahead of Anticipated Debut in March 2025: Report  Gadgets 360
5. iPhone SE 4 may spell trouble for iPhone 16 and premium Android phones, here’s why  Hindustan Times

1. Garena Free Fire Max Redeem Codes for Today: November 13, 2024  Analytics Insight
2. Garena Free Fire MAX redeem codes for November 12: Win free diamonds, skins, and more  The Times of India
3. Garena Free Fire MAX Redeem Codes Today, November 13: Win Free Gifts, Skins And Much More  Jagran English
4. Free Fire Mystery Shop: Rewards, duration, and more  Sportskeeda
5. Garena Free Fire MAX redeem codes for November 13, 2024: Win bundles, new outfits, and more rewards...  Moneycontrol

Leading IT services provider L&T Infotech on Tuesday announced acquisition of Pune-based analytics start-up AugmentIQ Data Sciences Ltd for an undisclosed amount.

Revelwood, experts in solutions for the Office of Finance, has partnered with Incorta® to further expand the company's strategic data, analytics and accounting solutions for finance organizations in businesses of all sizes, across all industries. Incorta offers an open data delivery platform powered by smart lakehouse technology. The technology simplifies the data ingestion and delivery approach, giving clients unrivaled data access to deliver fast, accurate insights.

Is big data just for big business? For several years, larger corporations have been gathering informative insights from this next-generation approach to data analysis. But now small businesses are finding ways to leverage this comprehensive data analysis for marketing insights.

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A new free analytics tool introduced on Sept. 10 by the Atlanta-based lending platform Kabbage analyzes the live data of more than 200,000 companies in an effort to give small business owners a way to assess how their businesses are performing in real time. It’s daring to meet the demands of the ever-changing world of small business.

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Our recent migration to GA4 left a lot to be desired and led us to explore for better google analytics alternatives. We tried just about everything out there, including Plausible, Fathom, and several others, all with their own pros and …

Unlock the power of ChatGPT for advanced data analysis with our comprehensive guide. We've even included screenshots.

The post Guide: Using GPT for Digital Marketing Analytics (with examples) appeared first on Portent.

A free version of Urchin, a company Google bought. (official blog post)

Content may be king, but data sits behind the throne and has the king’s ear. 

You want to be informed by data before you make changes to your marketing strategies. This is never truer than in the case of your website, which is a rich source of behavioural analytics and, therefore, a valuable insight into your audience’s interests.

Aim/Purpose: Business analytics is a cross-functional field that is important to implement for a college and has emerged as a critically important core component of the business curriculum. It is a difficult task due to scheduling concerns and limits to faculty and student resources. This paper describes the process of creating a central video repository to serve as a platform for just in time teaching and the impact on student learning outcomes. Background: Industry demand for employees with analytical knowledge, skills, and abilities requires additional analytical content throughout the college of business curriculum. This demand needs other content to be added to ensure that students have the prerequisite skills to complete assignments. Two pedagogical approaches to address this issue are Just-in-Time Teaching (JiTT) and scaffolding, grounded in the Vygoskian concept of “Zone of Proximal Development. Methodology: This paper presents a case study that applies scaffolding and JiTT teaching to create a video repository to add business analytics instruction to a curriculum. The California Critical Thinking Skills Test (CCTST) and Major Field Test (MFT) scores were analyzed to assess learning outcomes. Student and faculty comments were considered to inform the results of the review. Contribution: This paper demonstrates a practical application of scaffolding and JiTT theory by outlining the process of using a video library to provide valuable instructional resources that support meaningful learning, promote student academic achievement, and improve program flexibility. Findings: A centrally created library is a simple and inexpensive way to provide business analytics course content, augmenting standard content delivery. Assessment of learning scores showed an improvement, and a summary of lessons learned is provided to guide implications. Recommendations for Practitioners: Pedagogical implications of this research include the observation that producing a central library of instructor created videos and assignments can help address knowledge and skills gaps, augment the learning of business analytics content, and provide a valuable educational resource throughout the college of business curriculum. Recommendation for Researchers: This paper examines the use of scaffolding and JiTT theories. Additional examination of these theories may improve the understanding and limits of these concepts as higher education evolves due to the combination of market forces changing the execution of course delivery. Impact on Society: Universities are tasked with providing new and increasing skills to students while controlling the costs. A centrally created library of instructional videos provides a means of delivering meaningful content while controlling costs. Future Research: Future research may examine student success, including the immediate impact of videos and longitudinally using video repositories throughout the curriculum. Studies examining the approach across multiple institutions may help to evaluate the success of video repositories. Faculty acceptance of centrally created video libraries and assignments should be considered for the value of faculty recruiting and use in the classroom. The economic impact on both the university and students should be evaluated.

The phenomenon of cloud computing and related innovations such as Big Data have given rise to many fundamental changes that are evident in information and data. Managing, measuring and developing business value from the plethora of this new data has significant impact on many corporate agendas, particularly in relation to the successful implementation of business intelligence and analytics (BI&A). However, although the influence of Big Data has fundamentally changed the IT application landscape, the metrics for measuring success and in particular, the quality of information, have not evolved. The measurement of information quality and the antecedent factors that influence information has also been identified as an area that has suffered from a lack of research in recent decades. Given the rapid increase in data volume and the growth and ubiquitous use of BI&A systems in organisations, there is an urgent need for accurate metrics to identify information quality.

This paper analyses the adoption of learning analytics to predict at-risk students. A total of 233 research articles between 2004 and 2023 were collected from Scopus for this study. They were analysed in terms of the relevant types and sources of data, targets of prediction, learning analytics methods, and performance metrics. The results show that data related to students' academic performance, socio-demographics, and learning behaviours have been commonly collected. Most studies have addressed the identification of students who have a higher chance of poor academic performance or dropping out of their courses. Decision trees, random forests, and artificial neural networks are the most frequently used techniques for prediction, with ensemble methods gaining popularity in recent years. Classification accuracy, recall, sensitivity, and true positive rate are commonly used as performance metrics for evaluation. The results reveal the potential of learning analytics for informing timely and evidence-based support for at-risk students.

Aim/Purpose: The aim of this research paper is to suggest a comprehensive model that incorporates the technology acceptance model with the task-technology fit model, information quality, security, trust, and managerial support to investigate the intended usage of big data analytics (BDA) in banks and insurance companies. Background: The emergence of the concept of “big data,” prompted by the widespread use of connected devices and social media, has been pointed out by many professionals and financial institutions in particular, which makes it necessary to assess the determinants that have an impact on behavioral intention to use big data analytics in banks and insurance companies. Methodology: The integrated model was empirically assessed using self-administered questionnaires from 181 prospective big data analytics users in Moroccan banks and insurance firms and examined using partial least square (PLS) structural equation modeling. The results cover sample characteristics, an analysis of the validity and reliability of measurement models’ variables, an evaluation of the proposed hypotheses, and a discussion of the findings. Contribution: The paper makes a noteworthy contribution to the BDA adoption literature within the finance sector. It stands out by ingeniously amalgamating the Technology Acceptance Model (TAM) with Task-Technology Fit (TTF) while underscoring the critical significance of information quality, trust, and managerial support, due to their profound relevance and importance in the finance domain. Thus showing BDA has potential applications beyond the finance sector. Findings: The findings showed that TTF and trust’s impact on the intention to use is considerable. Information quality positively impacted perceived usefulness and ease of use, which in turn affected the intention to use. Moreover, managerial support moderates the correlation between perceived usefulness and the intention to use, whereas security did not affect the intention to use and managerial support did not moderate the influence of perceived ease of use. Recommendations for Practitioners: The results suggest that financial institutions can improve their adoption decisions for big data analytics (BDA) by understanding how users perceive it. Users are predisposed to use BDA if they presume it fits well with their tasks and is easy to use. The research also emphasizes the importance of relevant information quality, managerial support, and collaboration across departments to fully leverage the potential of BDA. Recommendation for Researchers: Further study may be done on other business sectors to confirm its generalizability and the same research design can be employed to assess BDA adoption in organizations that are in the advanced stage of big data utilization. Impact on Society: The study’s findings can enable stakeholders of financial institutions that are at the primary stage of big data exploitation to understand how users perceive BDA technologies and the way their perception can influence their intention toward their use. Future Research: Future research is expected to conduct a comparison of the moderating effect of managerial support on users with technical expertise versus those without; in addition, international studies across developed countries are required to build a solid understanding of users’ perceptions towards BDA.

Aim/Purpose: This study utilized a comprehensive framework to investigate the adoption of Business Analytics (BA) and its effects on performance in commercial banks in Jordan. The framework integrated the Technological-Organizational-Environmental (TOE) model, the Diffusion of Innovation (DOI) theory, and the Resource-Based View (RBV). Background: The recent trend of utilizing data for business operations and decision-making has positively impacted organizations. Business analytics (BA) is a leading technique that generates valuable insights from data. It has gained considerable attention from scholars and practitioners across various industries. However, guidance is lacking for organizations to implement BA effectively specific to their business contexts. This research aims to evaluate factors influencing BA adoption by Jordanian commercial banks and examine how its implementation impacts bank performance. The goal is to provide needed empirical evidence surrounding BA adoption and outcomes in the Jordanian banking sector. Methodology: The study gathered empirical data by conducting an online questionnaire survey with senior and middle managers from 13 commercial banks in Jordan. The participants were purposefully selected, and the questionnaire was designed based on relevant and well-established literature. A total of 307 valid questionnaires were collected and considered for data analysis. Contribution: This study makes a dual contribution to the BA domain. Firstly, it introduces a research model that comprehensively examines the factors that influence the adoption of BA. The proposed model integrates the TOE framework, DOI theory, and RBV theory. Combining these frameworks allows for a comprehensive examination of BA adoption in the banking industry. By analyzing the technological, organizational, and environmental factors through the TOE framework, understanding the diffusion process through the DOI theory, and assessing the role of resources and capabilities through the RBV theory, researchers and practitioners can better understand the complex dynamics involved. This integrated approach enables a more nuanced assessment of the factors that shape BA adoption and its subsequent impact on business performance within the banking industry. Secondly, it uncovers the effects of BA adoption on business performance. These noteworthy findings stem from a rigorous analysis of primary data collected from commercial banks in Jordan. By presenting a holistic model and delving into the implications for business performance, this research offers valuable insights to researchers and practitioners alike in the field of BA. Findings: The findings revealed that various technological (data quality, complexity, compatibility, relative advantage), organizational (top management support, organizational readiness), and environmental (external support) factors are crucial in shaping the decision to adopt BA. Furthermore, the study findings demonstrated a positive relationship between BA adoption and performance outcomes in Jordanian commercial banks. Recommendations for Practitioners: The findings suggest that Jordanian commercial banks should enforce data quality practices, provide clear standards, invest in data quality tools and technologies, and conduct regular data audits. Top management support is crucial for fostering a data-driven decision-making culture. Organizational readiness involves having the necessary resources and skilled personnel, as well as promoting continuous learning and improvement. Highlighting the benefits of BA helps overcome resistance to technological innovation and encourages adoption by demonstrating improved decision-making processes and operational efficiency. Furthermore, external support is crucial for banks to adopt Business Analytics (BA). Banks should partner with experienced vendors to gain expertise and incorporate best practices. Vendors also provide training and technical support to overcome technological barriers. Compatibility is essential for optimal performance, requiring managers to modify workflows and IT infrastructure. Complexity, including data, organizational, and technical complexities, is a major obstacle to BA adoption. Banks should take a holistic approach, focusing on people, processes, and technology, and prioritize data quality and governance. Building a skilled team, fostering a data-driven culture, and investing in technology and infrastructure are essential. Recommendation for Researchers: The integration of the TOE framework, the DOI theory, and the RBV theory can prove to be a powerful approach for comprehensively analyzing the various factors that influence BA adoption within the dynamic banking industry. Furthermore, this combined framework enables us to gain deeper insights into the subsequent impact of BA adoption on overall business performance. Impact on Society: Examining the factors influencing BA adoption in the banking industry and its subsequent impact on business performance can have wide-ranging societal implications. It can promote data-driven decision-making, enhance customer experiences, strengthen fraud detection, foster financial inclusion, contribute to economic growth, and trigger discussions on ethical considerations. Future Research: To further advance future research, there are several avenues to consider. One option is to broaden the scope by including a larger sample size, allowing for a more comprehensive analysis. Another possibility is to investigate the impact of BA adoption on various performance indicators beyond the ones already examined. Additionally, incorporating qualitative research methods would provide a more holistic understanding of the organizational dynamics and challenges associated with the adoption of BA in Jordanian commercial banks.

In the context of asthma severity prediction, this study delves into the feature importance of various symptoms and demographic attributes. Leveraging a comprehensive dataset encompassing symptom occurrences across varying severity levels, this investigation employs visualisation techniques, such as stacked bar plots, to illustrate the distribution of symptomatology within different severity categories. Additionally, correlation coefficient analysis is applied to quantify the relationships between individual attributes and severity levels. Moreover, the study harnesses the power of random forest and the Gini importance methodology, essential tools in feature importance analytics, to discern the most influential predictors in asthma severity prediction. The experimental results bring to light compelling associations between certain symptoms, notably 'runny-nose' and 'nasal-congestion', and specific severity levels, elucidating their potential significance as pivotal predictive indicators. Conversely, demographic factors, encompassing age groups and gender, exhibit comparatively weaker correlations with symptomatology. These findings underscore the pivotal role of individual symptoms in characterising asthma severity, reinforcing the potential for feature importance analysis to enhance predictive models in the realm of asthma management and bioinformatics.

Aim/Purpose: As online video lectures rapidly gain popularity in formal and informal learning environments, one of their main challenges is student retention. This study investigates the influence of adding interactivity to online video lectures on students’ attention span. Background: Interactivity is perceived as increasing the attention span of learners and improving the quality of learning. However, interactivity may be regarded as an interruption, which distracts students. Furthermore, adding interactive elements to online video lectures requires additional investment of various resources. Therefore, it is important to investigate the impact of adding interactivity to online video lectures on the attention span of learners. Methodology: This study employed a learning analytics approach, obtained data from Google Analytics, and analyzed data of two Massive Open Online Courses (MOOCs) that were developed by the Open University of Israel in order to make English for academic purposes (EAP) courses freely accessible. Contribution: The paper provides important insights, based on quantitative empirical research, on: integrating interactive elements in online videos; the impact of video length; and differences between two groups of advanced and basic learners. Furthermore, it demonstrates how learning analytics may be used for improving instructional design. Findings: The findings suggest that interactivity may increase the attention span of learners, as measured by the average online video lecture viewing completion percentage, before and after the addition of interactivity. However, when the lecture is longer than about 15 minutes, the completion percentages decrease, even after adding interactive elements. Recommendations for Practitioners: Adding interactivity to online video lectures and controlling their length is expected to increase the attention span of learners. Recommendation for Researchers: Learning analytics is a powerful quantitative methodology for identifying ways to improve learning processes. Impact on Society: Providing practical insights on mechanisms for increasing the attention span of learners is expected to improve social inclusion. Future Research: Discovering further best practices to improve the effectiveness of online video lectures for diverse learners.

Aim/Purpose: Sharing ideas generated in a Business Intelligence (BI) Applications class to upgrade an Information System in to an Informing System. Background: Course Registration is the essential university’s business process in a university that follows a liberal-arts education model. Almost all categories of users are involved, including students, individual faculties and departments, and administration. A typical Information System, designed to support this process, allows departments to schedule selected courses for a particular time slot and location, and allows students to choose courses to study for the semester. Methodology: The course project is to design a BI application. Domain knowledge is essential for such projects and course registration was the natural choice for this class. The assignment includes (1) identifying the categories of stakeholders; (2) identifying the information needs of different categories; (3) identifying available information sources; (4) identifying how is possible to acquire the additional data; and (5) designing the Extract-Transform-Load (ETL) process and interface scenarios in a way to inform clients. Contribution: Contributions are in two directions: (1) pedagogy - involving students in such a project motivates creativity, also enforcing students to think in cost-benefit framework may lead to creation of really effective and efficient solutions; (2) practice - implementation of some of the ideas could be with low cost, but with high impact. Findings: Exploring BI techniques may increase the informing value of existing Information Systems. Recommendations for Practitioners: Careful analysis of information needs and the way information is used, combined with deep domain knowledge and understanding the value provided by Data Mining techniques, is the way to initiate a process of transforming an Retrieval Information System to better inform clients. Recommendation for Researchers : Combining pedagogy with practice allows one to overcome routine thinking and may lead to effective solutions. This needs further structuring and research on outcomes. Impact on Society Transforming Information towards Informing Systems has a significant impact by allowing users to make rational data driven decisions in an efficient way. Future Research: The future of this project is implementation of developed ideas and assessment of the results. Impact on Society : Transforming Information towards Informing Systems has a significant impact by allowing users to make rational data driven decisions in an efficient way. Future Research: The future of this project is implementation of developed ideas and assessment of the results.

TomTom Mapping Data to Power End-to-End Analytics Platform

Security professionals examine the evolution of analytics in security applications.

BriefCam, the leader in innovative AI-driven video analytics solutions, is showcasing version 2023 M1 of its comprehensive video analytics platform at ISC West.

How do we move video analytics beyond descriptive to prescriptive? From gathering potential questions to providing solutions? The answer is more than just analytics — it is data intelligence. 

3xLOGIC, a provider of integrated and intelligent security and business solutions, will debut its recently launched edge based deep learning analytics cameras at ISC West 2024, Booth #23059.

How can leading indicators and analytics be used to mitigate risk and reduce employee injuries and illnesses?

The company is launching a cloud platform that leverages computer vision, AI, and video analytics to quickly and accurately detect, classify, and verify potential threats.

These devices that allow end-users and integrators to quickly bring up and configure on-site hardware, and then deploy a wide range of video analytics solutions using Lumeo’s customizable video analytics platform.

This collaboration expands Comcast Smart Solutions’ existing video analytics expertise while giving clients more flexibility to choose the right smart video solution, according to the announcement.

Comcast Smart Solutions is also providing ongoing data analysis and has a dedicated team for support.

Industry insiders explain how advanced video analytics technology is transforming central monitoring stations, enhancing public safety, and improving collaboration with law enforcement and emergency responders.

With the growth of video content across various industries, Lumeo said the ability to efficiently analyze and derive insights from this data is crucial.

By combining thermal analytics, geospatial capabilities and AI-enabled solutions, integrators can now achieve real-time, proactive and reliable outdoor security.

Built for extreme weather and environmental conditions, the new Aero PTZ cameras support up to 4K resolution and feature AI-driven analytics.

The white paper addresses key challenges in cultivated meat production.

In the recent 2-3 years, an increasing number of malls and retail chains have adopted real-time video analytics and facial recognition to enhance security, customer experience and footfall analysis.

Some of these technologies are showcased this week at the NRF Protect Conference in Long Beach, California.

Banks invest in data analytics and AI technologies to enhance customer experience, optimize decision-making, and prevent financial fraud. They focus on platform models, identity analytics, and fraud detection to improve services and security, aiming to capture the customer's financial journey for insights into their buying process.

The company is among the biggest stock market winners of the generative AI boom, with its shares more than doubling in value this year.

G&B has deployed over 80 RPA bots to automate manual processes across the value chain. This has resulted in productivity improvement, reduction in errors and improvement of employee experience.

One of the primary ways data and analytics are influencing the FMCG industry is through demand forecasting and inventory management. By analyzing historical sales data, market trends, and external factors like seasonality and economic indicators, FMCG companies can optimize their production and supply chain processes.

In an interview with ETCIO, Ravi Vijayaraghavan, SVP & Chief Data & Analytics Officer, Flipkart shares how the homegrown e-commerce giant leverages data science to drive customer experience and seller profitability.

Technology replaces error-prone manual record keeping and monitors energy and utilities parameters, improving efficiency and productivity.

The TheiaVu E-Series is a standalone vision inspection system that collects measurements of features of many types of baked goods, such as buns, rolls, English muffins, doughnuts, cookies, and more.

KPM Analytics has announced three new instrument configurations for its Unity Scientific SpectraStar product line.

KPM Analytics, Inc., a Union Park Capital portfolio company, announced it has acquired Bruins Instruments, a German-based manufacturer of high-resolution near-infrared reflectance and transmission analyzers.

By now, you may have heard that by July 2023, Google Analytics is shutting down for good, as Google replaces the analytics service with GA4. Why is this happening, and what does it mean for tracking my website analytics?

New Career Pathways for Girls