Data integration platforms typically involve several key components:
Data Ingestion: This involves collecting data from various sources such as laboratory instruments, databases, and publications. Data Transformation: Raw data is cleaned, normalized, and transformed into a common format to ensure consistency. Data Storage: Transformed data is stored in a central repository, often utilizing databases or data lakes. Data Access: Researchers can query and retrieve data through user-friendly interfaces and APIs. Data Analysis: Integrated data can be analyzed using statistical tools, machine learning algorithms, and visualization techniques.
