Our Product
Data
Viewer
In the DYNATREK user base, data is defined using terms that users employ in their daily tasks, such as "customer number," "sales revenue," and "number of contacts this term." Users can create a variety of content by combining these items using a tool called DYNATREK Viewer. This tool allows them to produce standard reports and charts, among other outputs.
The content created in the DYNATREK Viewer can be embedded into other web system screens. Additionally, by clicking on the DYNATREK screen, it can display another business system screen. This means that the content produced can be "integrated into daily operations.
Data Dictionbary
In the DYNATREK's data dictionary layer, it's possible to register details about how user-layer provided terms like "customer number," "sales revenue," and "number of contacts this term" relate to specific items in which system, and how they are calculated. DYNATREK dynamically converts the logic registered in the data dictionary layer into SQL (a database query language) for each user search. This allows DYNATREK to behave as if the database is directly present there.
In many companies, this knowledge often becomes tacit knowledge for power users. Bridging the gap between "business terms" and "system terms" is perhaps the most crucial role that DYNATREK plays.
Additionally, the data dictionaries registered in DYNATREK can always be documented or databased, playing a significant role in visualizing business know-how.
Virtual
Database
In DYNATREK, actual databases are searched via a virtual database where the types and formats of information that users utilize are defined. The virtual database is purely logical, holding various definitions and rules. The actual data is constructed virtually and in real-time based only on the required data at execution time. Therefore, there's no need for data reconfiguration tasks as you would in a data warehouse, and there's no data generation delay, allowing users to retrieve the latest live data. The virtual database consists of two layers: the user layer and the model transformation layer.
User Model Layer The user layer receives search commands from users and returns search result data corresponding to those commands. As this layer is purely logical and defined from a data usage perspective, it can be structured in a concise and understandable manner that aligns with business frameworks and terminologies, independent of the actual database's data structure.
Model Transformation Layer The model transformation layer has the function of converting the logical model of the user layer and the physical structure of the data source. Based on the search command from users, it searches for the necessary data from multiple data sources, performing a series of processes to process and edit the data according to the information defined in the user layer.