Data systems are computerized systems which store information about students, teachers, and schools. They permit users to access the data and manage it, as well as analyze it. They are known by many names, including learning management system (LMS), student information system (SIS), decision support system, data warehouse and more.
The purpose of design of a data system is to improve the way the information within an organization is collected, stored, retrieved and analyzed. It involves determining which storage and retrieval methods are most efficient, constructing schemas and models for data and establishing a robust security. Data system design is about determining which tools and technologies are ideal for storing, sending and processing data.
Big sensor data systems are based on a collection different sources of data, such as wireless and mobile devices as well as Telecommunications networks, wearables and public databases. Each of these sources produces an array of sensor readings, each having its own metric values. The key challenge is to find a resolution that works for the data, and also an aggregate method that lets the sensor data to be presented in a single form using the same metric.
In order to enable efficient data analysis, it is essential to ensure that the data can be understood and interpreted correctly. Preprocessing is a process which encompasses all the activities that prepare the data for analysis and transformations like formatting or combination, as well as replication. Preprocessing can be batch or stream based.