DataPlay Analyzer

DataPlay Analyzer is comprised of two main components: Datasource Manager and Association Mining. Datasource Manager provides a set of comprehensive solutions for managing different types of datasources. Association Mining tool is used for discovering data patterns in large databases based on diverse criteria.

Analyzer connects to DataPlay Cloud for importing new types of datasources and association finding functionality. Using integrated security settings of DataPlay Web Portal, administrators can manage the rights that different users can have when they are connecting Cloud from Analyzer.

Admin users can manage the access to:

  • Datasource Upload/Open
  • Variable Management
  • Data Mining

Datasource Manager

Data management functionalities of Analyzer help to unify different data formats, so that you can treat data in a similar way regardless of its source type. You can create, merge or auto merge categories of a variable into different new variables. You can group variables into different folders with hierarchical structure to proceed with assigning weights and default bases for sorted data. To make the analysis process even more efficient, we have introduced “components” used for grouping variables in accordance with research questions. You will be able to effortlessly traverse through variables of each component using Association Mining tool of Analyzer, and find interesting associations.

Main functionalities of Datasource Manager include:

  • Ability to import data from virtually any format used in the industry in a one-step (IBM Dimensions, SPSS, U-Tab, Excel, MDS)
  • Variable Management: creating new variables by crossing and merging others
  • Default Base Management: creating default bases and assigning to variables
  • Folders Management: creating hierarchical structure of variables
  • Component Management: creating components and adding variables to them (used in Association Mining)
  • Ability to connect analysis results with the rest of the downstream systems by exporting analyzed data in widely accepted formats (PPT, Excel)
  • Ability to automatically update analysis with the new version of the study data

Association Mining

Once you’ve edited your variables, added default bases and weights, created your folders and components, you then can go to Analyzer’s Association Mining to start the getting new insights. All you have to do is to drag and drop folder, component or individual variable in accordance with your research objectives. Users can specify multiple association levels and all of them will be displayed with different status bar. Association Mining also has a powerful result grid filters. You can click on Association filter and select which variables you want to filter. You can also use confidence and support factors’ level to filter only the associations with the strongest relationship among variables. Later on, these associations will be displayed in PPT and Excel Add-Ins to hint the user which associations to use. Quickly skim through this expanded number of result grids or PPT visuals and find patterns you haven’t previously thought about.

Main functionalities of Association Mining include:

  • Mining among components and variables based on Confidence and Support factors
  • Ability to spice up the analysis results with refined filtering on Confidence, Variables and Item Set Levels
  • Management of discovered associations
  • Ability to copy the analysis metadata (variables, components, folders, associations) into the new analysis
  • Ability to share the data in a unified format inside the framework for further processing and visualization