To help you manage corporate data throughout its life cycle, we implement a comprehensive data management program, which includes the following elements:

·        Data Governance

·        Data Architecture

·        Data Integration

·        Data Quality Management

·        Data Storage

·        Metadata Management

·        Data Warehousing, Analytics, and Reporting


Data Quality Standards that We Target


When establishing data management for customers, Schedio scientific guarantees the following data quality characteristics:

·        Consistency

·        Accuracy

·        Completeness

·        Auditability

·        Timeliness

·        Uniqueness


IoT analytics is the application of data analysis tools and procedures to realize value from the huge volumes of data generated by connected Internet of Things devices.  The potential of IoT analytics is often discussed in the Industrial IoT. The IoT makes it possible for organizations to collect and analyze data from sensors on manufacturing equipment, pipelines, weather stations, smart meters, delivery trucks, and other types of machinery. IoT analytics offers similar benefits for the management of data centers and other facilities, as well as retail and healthcare applications.


IoT data can be thought of as a subset and a special case of big data and, as such, consists of heterogeneous streams that must be combined and transformed to yield consistent, comprehensive, current, and correct information for business reporting and analysis. Data integration is complex for IoT data. There are many types of devices, most of which are not designed for compatibility with other systems. Data integration and the analytics that rely on it are two of the biggest challenges to IoT development.