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Data systems are computerized systems which collect information about students teachers, and schools. They permit users to access the data and analyze it. They also manage the data and monitor it. They are known by many names including learning management system, student information system (SIS), decision support system Data warehouse, decision support system and many more.
Data system design seeks to improve the way information is gathered, stored, and retrieved within an organisation. It involves determining which methods for retrieval and storage are most efficient, constructing schemas and models for data as well as constructing robust security. Data system design also includes identifying the best tools and technologies for storing, processing and delivering information.
Big sensor data systems rely on a set of diverse data sources derived from a variety of sensors that are physical and not, including wireless and mobile devices and wearables, telecommunication networks, and public databases. Each of these sources produce a set sensor readings with their individual metric values. The primary challenge is to find a suitable time resolution for the data, and the process of aggregation that allows the sensor data to be presented in a single form using a common metric.
To enable efficient data analysis, it’s necessary to ensure that data can be understood and processed correctly. This is why you need to preprocess, which encompasses all the steps involved in preparing data for subsequent analysis and transformations, including formatting, combination and replication. Preprocessing is either batch-based or stream-based.