Each part is around 100 words, total is 200 words.
Part 1:
What Big Data trends in the field of personal health are more exciting to you? why?
In the field of personal health, I would say there are three (3) trends, which I find the most exciting. First, Patient-Oriented Care, or the concept of treating patients based on their personalized profile, medical history, and needs, will revolutionize the way health care is provided. Also, the Patient Monitoring is going to be improved, with the use of monitoring devices that would analyze the health and well-being of the patient in real-time. Finally, Electronic Health Records will pave the way for future breakthroughs in healthcare, with the big data being efficiently organized and stored in large databases. (Mobifilia 2020)
What new Big Data trends in the field of sports do you think will impact the sport and audiences the most? why?
There are three (3) ways that big data will impact the sports industry and its audiences. First, recruitment of college athletes can be improved, using profiles of potential athletes from across the nation. Also, big data can be used to provide addition details for concussion patients, as to whether injury reduction strategies are working. Finally, fan experiences can be enhanced, from stocking the merchandise stands at a stadium, to directing traffic after fans are leaving the game. (Matthews 2019)
How, do you think, the music industry can benefit from the application of Big Data technology?
Big data has benefited the music industry in several ways. Big data can be used by music publishers to analyze the number and types of music being downloaded. As well, the data can provide context for each listener, in regards to which streaming applications they used, and what preferences they have. In addition, AI systems can be integrated, to create playlists that can match the listeners mood and taste based on their current situation. (Delgado 2018)
Part 2:
Big Data can be leveraged in multiple ways to assist health care providers and patients. Electronic Health Records can be leveraged by AI and other data mining algorithms to pro-actively identify risk factors for certain diseases like congestive heart failure (Carol McDonald 2017). Additionally, data from IoT devices such as wearables and activity trackers can be used to deliver precision medicine for patients like tracking vital signs and medicine regimens and insulin activity (Manuel 2017). Big Data analytics can also be used to deliver precision medicine for patients by combining data available in EHR’s with other attributes like financial, operational and genomic data to match treatments with outcomes (Ragupathi 2014).
Big Data analytics in sports can help improve both the player and the fan experience. Data Analytics applied to videos and IoT devices like the wearables could allow the coaches and the teams to identify and track player movements and positions throughout multiple games. These could allow teams and players to develop effective strategies to tackle opponents (Ricky 2019). Teams could also leverage social media analytics to monitor fan sentiment in real time during games and develop more effective marketing strategies to engage them. Data analytics applied to items like e-tickets and fingerprint scanning etc can allow teams to effectively map and predict fan movements allowing them to decide ticket pricing and staffing for individual games (Ricky 2019).
Music industry has been dealing with falling revenues and unlicensed consumption of music. Big Data analytics can be employed to monitor and verify the consumption of music over online and broadcast channels to recoup lost revenues (Utopia 2019). Analytics could also be employed to develop effective marketing campaigns that targets the right group of consumers for each artist and genre of music (Utopia 2019). Social media analytics can help artists and performers to evolve their music to match current consumer tastes.
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