Data systems are computerized systems that store teacher, student and school data and permit users to retrieve as well as analyze the data. They are referred to under many names like student information system (SIS), learning management system decision support system and data warehouse.
Data system design aims to improve the way information is collected, stored and recovered within an organisation. It involves determining which storage and retrieval methods are most effective, developing schemas and models of data and creating secure security. Data system design is about determining which tools and technologies are best for storing, transmitting and processing data.
Big sensor data systems rely on a mix of different data sources from various physical and non-physical sensors, such as mobile and wireless devices such as wearables, telecommunications networks, and public databases. Each of these sources produces the same sensor readings but with their own metrics. The most important thing is to determine a suitable time resolution for the data and the process of aggregation which allows the sensor data to be presented in a single format using the same metric.
To ensure that data analysis is efficient, it is crucial to ensure that the data be properly understood. This is why you need to preprocess which covers all of the activities involved in preparing data for analysis later and transformations, including formatting, combing and replication. Preprocessing can be batch-based or stream-based.