Final answer:
Predictive healthcare is the field that will significantly demand data analysts' skills in handling large datasets and making decisions based on relevant data. Other IT trends also involve data analysis to some degree, but predictive healthcare is directly tied to the continual analysis and interpretation of health data to inform patient care and health services.
Step-by-step explanation:
Among the given options, predictive healthcare will require many data analysts who can collect data, decide which data is relevant, and make informed decisions based on that data. Predictive healthcare utilizes vast amounts of data to forecast health issues, manage chronic diseases, and personalize health plans for patients. As a result, it demands a high level of expertise in data analysis to sift through the information and determine predictive patterns.
While edge computing, blockchain technology, and hyper-automation are indeed growing IT trends, they are not as heavily reliant on data analysis for decision-making as predictive healthcare. Edge computing processes data closer to the data source, reducing the need for data transport to a centralized data center. Blockchain technology focuses on secure transaction ledger databases. Hyper-automation combines several components of process automation, integrating tools like artificial intelligence (AI) and machine learning to automate processes but not directly relating to daily tasks of data analysts.In the context of data research, the role of data analysts in predictive healthcare is to apply computer algorithms and statistical analyses to health-related data in order to aid in decision-making processes, thus offering valuable insights into improving patient care and health system efficiency.