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Xu Yang, Dec. 2020 Big data analysis requires examining large amounts of data. This is, so discover the hidden patterns, and give the insight to make decisions on the correct business. Companies, because it uses the power of data and technology be a more objective data-driven. Big data of human resources, faced with various problems from big data storage security problems. These issues have been discussed in the next four categories based on the Contextual Data Analyzing Technique (CDAT) using FPGA tool. Data were collected and finally to analysts that are eligible to determine the problems caused by direct analysis, on security issues, and to find the problem. Companies that big data is presented to improve the company's strategy, to the best of time, various opportunities to make the right decisions. Human resources are one of the substantive departments of any company that needs big data benefits in a different process. The main purpose is to describe the big human data analysis method to improve company performance. Also, the problem is, all of the human resources department is that it is facing using big data.
Abir EL Azzaoui, Sushil Kumar Singh, Jong Hyuk Park, Nov. 2020
Nowadays, the world is experiencing a pandemic crisis due to the spread of COVID-19, a novel coronavirus disease. The contamination rate and death cases are expeditiously increasing. Simultaneously, people are no longer relying on traditional news channels to enlighten themselves about the epidemic situation. Alternately, smart cities citizens are relying more on Social Network Service (SNS) to follow the latest news and information regarding the outbreak, share their opinions, and express their feelings and symptoms. In this paper, we propose an SNS Big Data Analysis Framework for COVID-19 Outbreak Prediction in Smart Sustainable Healthy City, where Twitter platform is adopted. Over 10000 Tweets were collected during two months, 38% of users aged between 18 and 29, while 26% are between 30 and 49 years old. 56% of them are males and 44% are females. The geospatial location is USA, and the used language is English. Natural Language Processing (NLP) is deployed to filter the tweets. Results demonstrated an outbreak cluster predicted seven days earlier than the confirmed cases with an indicator of 0.989. Analyzing data from SNS platforms enabled predicting future outbreaks several days earlier, and scientifically reduce the infection rate in a smart sustainable healthy city environment.