International Journal of Engineering and Management Research
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Protecting Sensitive Data in Salesforce – A Multi-Layered Security Approach
Get PDFData security is a paramount concern for organizations across various industries, particularly when it comes to customer relationship management (CRM) platforms like Salesforce. As businesses increasingly rely on Salesforce for managing critical customer data, it is crucial to understand the security measures and best practices necessary to protect sensitive information from unauthorized access, breaches, and data leaks.
This research paper provides a comprehensive review of data security measures and best practices specifically tailored for Salesforce implementations. The objective is to equip organizations and Salesforce administrators with the knowledge and tools needed to establish robust security protocols and mitigate potential risks.
The paper examines the fundamental security features provided by Salesforce, including user authentication, access controls, and data encryption. It explores advanced security capabilities such as identity management, single sign-on (SSO), and multi-factor authentication (MFA), highlighting their role in enhancing data security and user access management.
Additionally, the research delves into the significance of data governance and data classification in maintaining data integrity and privacy. It discusses the implementation of role-based access control (RBAC), data sharing rules, and object-level permissions to ensure that data is accessible only to authorized individuals.
Furthermore, the paper explores best practices for securing data during transit and at rest, covering topics such as Secure Sockets Layer (SSL) encryption, data encryption at rest, and data backup strategies. It also addresses the importance of regularly monitoring and auditing user activity, employing security monitoring tools, and conducting vulnerability assessments and penetration testing.
By comprehensively reviewing the security measures and best practices in Salesforce, this research paper aims to serve as a valuable resource for organizations seeking to fortify their data security posture, protect customer information, and maintain compliance with data protection regulations
Sentiment Analysis using Opinion Mining on Customer Review
Get PDFOpinion mining is the process of discovering user opinions about a subject, a product, or an issue. Sentiment analysis is the process of separating opinions\u27 feelings from those opinions. This work presents a comprehensive review of techniques in sentiment analysis using opinion mining. We start by discussing the basic concepts of opinion mining and then delve into various techniques and approaches used for sentiment analysis. This work focuses on analyzing the user reviews on products from e-commerce websites such as amazon.com and compares products of similar specifications based on the polarity of user reviews for the products calculated using nlp and naive bayes classification
Creating Innovative Healthcare Apps for Dementia Patients and Caregivers
Get PDFThe provision of appropriate care and support to elderly individuals with dementia poses significant challenges, as they often struggle to manage their health conditions due to cognitive limitations and lack of assistance. This research aims to address this problem by developing a user-friendly healthcare system that caters to the unique needs of dementia patients. The system incorporates wearable devices and a mobile app, enabling patients to monitor their health status and communicate with their healthcare team. The primary objective is to track patients\u27 day-to-day activities, meals, exercises, critical situations, and mental health, generating comprehensive reports for doctors to assess their overall well-being. Additionally, the research focuses on leveraging artificial intelligence to enhance patients\u27 moods through personalized audio and video clips, utilizing image processing to detect facial expressions. Machine learning algorithms are employed to provide personalized meal plans based on data collected from IoT devices. Moreover, a warning system is developed to promptly alert both the patient and the nearest hospital in emergency situations using IoT data. The research also emphasizes automating the generation of monthly health reports, which are shared with the patient\u27s doctor for review. By showcasing the potential of these technologies, this research aims to improve the outcomes of dementia patients, enhance healthcare efficiency, and deliver personalized care
A Study on the Online Shopping - Pre and Post Pandemic
Get PDFPrior to the pandemic, online shopping was infrequent. However, when the COVID-19 situation worsened, people were unable to purchase the products they needed since stores were closed and there was only one way to get them: online shopping. As a result, they started buying online, but they soon realized that they had a lot of possibilities, so they progressively went toward it. People continued to shop online and in-store as the situation stabilized. People preferred both online and in-store purchasing, but it was discovered that online shopping surged after the pandemic
High Performing Work System and Emotional Intelligence among Working Women
Get PDFThe study aims to understand how the implementation of HPWS influences the development of emotional intelligence in female employees and how this relationship, through a literature review, empirical analysis, and case studies, this paper provides insights into the significance of integrating HPWS and EI in the workplace, shedding light on strategies to empower working women. As gender disparities persist in contemporary workplaces, the need to comprehend the mechanisms by which HPWS can potentially enhance EI, thereby bolstering the performing and well-being of female employees, has become increasingly imperative. By drawing from a multitude of research approaches, this paper synthesizes and advances our understanding of these multifaceted interconnections and elucidates the symbiotic relationship between HPWS and EI in the context of female employees within the workforce. It underscores the imperative for organizations to adopt strategies that encourage the development of emotional intelligence among women, not only as a means of promoting gender equality but also as a viable pathway to enhance job performing and overall well-being. By integrating a multifaceted research approach, this study contributes to the academic discourse and provides practical guidance for organizations aiming to foster an inclusive and empowered workplace for women
A Review of the Role of Understory Technologies for Carbon Neutrality
Get PDFCarbon emissions are considered the main cause of global warming. The mainstream scientific community has reached a consensus on this, which stimulates international political responses and promotes research on carbon emissions and their reduction in the economics community. At the 75th session of the UN General Assembly, President Xi Jinping solemnly promised that China will strive to peak its carbon emissions by 2030 and achieve carbon neutrality by 2060. Carbon emission reduction has received more attention. At the same time, the under-forest economy is regarded as a new growth point for carbon emission reduction. This paper focuses on reviewing the history of carbon emissions, the development of carbon emission reduction in China, and the economic analysis of China\u27s carbon emission reduction policies. China\u27s carbon emission reduction policy has been implemented for more than ten years, especially the carbon trading pilot policy, which has been implemented for seven years. Are state efforts effective? What is the current state of the carbon emission reduction market? What is the role of understory economy in reducing carbon emissions? The article also answers the above points
Design and Analysis of Geographical Attendance Tracking System
Get PDFIn today\u27s digital age, the need for an educational system is growing in our country as well as in our cities. Currently, all data processing is done manually (based on documentation). This process is also very time consuming and difficult.
So because of this, we are creating a new efficient system by using software, which will be easy and beneficial to see the performance of employee. We take the input through Excel and process it. Therefore, the main objective of this project is to reduce all the paper work. And creating more attractive report in less time.
This software managing an onsite & offsite employee’s is huge challenge for any administration. Tagging your onsite & offsite employee’s attendance from any location is difficult to organization. So we are implement GEO-ATS is an app and web portal that ensure onsite & offsite employee’s management
Impact of Future Price on Spot Price of Indian Stock Market
Get PDFThis paper examines the impact of future trading on spot price volatility by using regression Analysis. The main objective of this paper is to investigate whether the existence of future markets in India has improved the rate at which new information is impounded into spot prices and have any persistence effect. The results gathered from the study indicate that even though it has been in operation for a short period of time, the futures market in India has significantly increased the rate at which new information is transmitted into spot prices and that it has reduced the persistence of information and volatility in underlying spot market resulting in improved efficiency. The results of this study have also some important implications for policy makers discussed in the final section of this paper
Fake News Detection Using Machine Learning: An Exhaustive Review
Get PDFFake news can have serious consequences, from influencing elections to spreading harmful misinformation. Machine learning can be used to help combat the spread of fake news by analyzing large amounts of data and identifying patterns that may indicate the presence of false or misleading information. Here are the steps that can be taken to perform fake news analysis using machine learning. Data Collection, Data Preprocessing, Feature Extraction, Model Training, Model Evaluation, and Model Deployment. That is the reason today we need a PC fake wise based model that can identify any phony news before it is posted. All web-based media stages have worked towards this path, however, in some places it appears to be that their model is deficient to catch such phony news. Since some web-based media organizations have attempted to choose whether the news is phony or not based on some predefined datasets. Furthermore, a few organizations have looked through just the watchwords of the news that the news is phony. This demonstrates that we need a model that depends on the old dataset, and the current news dataset and watchwords. Alongside this, focus on the circumstance, spot, and kind of information, while these things are not dealt with in the current models. So I might want to remember this load of boundaries for my model to assist with distinguishing counterfeit news. On the off chance that we perceive Fake News as the ideal opportunity, we can make the perfect strides at the perfect time. PC based models are not generally exact, so the model ought to likewise have the office to contrast and genuine news. Assuming news is contrasted and current information, 76% of phony news can be distinguished simultaneously. Accordingly, the model ought to likewise have the office of the relative survey
A Review Paper on Software Defect Prediction Based on Rule Mining
Get PDFSoftware defect prediction is an important task in software engineering, aimed at identifying and mitigating software defects before they become major problems. Rule mining is a technique used to discover interesting patterns and relationships in data, and can be applied to software defect prediction by analyzing past data on software development and testing. This abstract discusses the process of software defect prediction based on rule mining, including data collection, data pre-processing, feature extraction, rule mining, model evaluation, and model deployment. By accurately predicting the likelihood of defects occurring in future software releases, developers can take proactive measures to prevent defects from occurring, thereby improving software quality and reducing the time and resources spent on fixing bugs