Data systems are computerized systems which keep information about students, schools, and educators. They allow users to retrieve the data and manage it, as well about his as analyze it. These systems are known by many names like student information system (SIS) learning management system, decision support system, and data warehouse.
The purpose of data system design is to improve the way that information within an organization is collected to be stored, retrieved, and examined. It involves determining which methods for retrieval and storage are the most efficient, creating data models and schemas and establishing a robust security. Data system design also involves identifying the best tools and technologies to use for processing, storing and delivering information.
Big sensor data systems are based on a collection different data sources, including wireless and mobile devices, as well as Telecommunications networks, wearables and public databases. Each of these sources produces an array of sensor readings, each with their own metric values. The main challenge is to find a time resolution that can be used for the data, and an algorithm for aggregation that lets the sensor data to be represented in a single way using the same metric.
To ensure efficient data analysis, it’s necessary to ensure that data is understood and interpreted correctly. Preprocessing is a method that covers all the steps that prepare data for analysis and transformations like formatting as well as combination and replication. Preprocessing can be either batch or stream based.