Technology for collecting and analyzing relational data

Abstract

Purpose of the study. The scientific and educational organizations use traditionally e-mail with Microsoft Excel spreadsheets and Microsoft Word documents for operational data collection. The disadvantages of this approach include the lack of control of the correctness of the data input, the complexity of processing the information received due to non-relational data model, etc. There are online services that enable to organize the collection of data in a relational form. The disadvantages of these systems are: the absence of thesaurus support; a limited set of elements of data input control; the limited control the operation of the input form; most of the systems is shareware, etc. Thus, it is required the development of Internet data collection and analysis technology, which should allow to identify quickly model the data collected and automatically implement data collection in accordance with this model. Materials and methods. The article describes the technology developed and tested for operational data collection and analysis using Faramant system. System operation Faramant is based on a model document, which includes three components: description of the data structure; visualization; logic of form work. All stages of the technology are performed by the user using the browser. The main stage of the proposed technology is the definition of the data model as a set of relational tables. To create a table within the system it’s required to determine the name and a list of fields. For each field, you must specify its name and use the control to the data input and logic of his work. Controls are used to organize the correct input data depending on the data type. Based on a model system Faramant automatically creates a filling form, using which users can enter information. To change the form visualization, you can use the form template. The data can be viewed page by page in a table. For table rows, you can apply different filters. To summarize the information there is a mechanism of data grouping, which provides general data of the number of entries, maximum, minimum, average values for different groups of records. Results. This technology has been tested in the monitoring requirements of the services of additional professional education and the definition of the educational needs of teachers and executives of educational organizations of the Irkutsk region. The survey has involved 2,780 respondents in 36 municipalities. Creating the data model took several hours. The survey was conducted during the month. Conclusion. The proposed technology allows a short time to collect the information in relational form, and then analyze it without the need for programming with flexible assignment of the operating logic for form.