The financial and analytical reporting functionality includes a set of features intended for converting printed forms into interactive documents which are deeply integrated with the applied solution. In addition to printing reports, users can customize them just as they can customize on-screen forms: they can change report parameters, rebuild reports, expand them by generating additional reports based on the elements of the current report, and more.
Programming tools that allow customized report generation are available for the convenience of advanced users.
Financial and analytical reporting includes the following features:
Queries are used to select data from a database. A query is a request to a system to select specific data from a database, which often includes some data processing: grouping, sorting, or calculating. For example, you can use queries for easy retrieval of turnovers of each item type within each month during a year, or for selecting catalog items by a specific condition.
This is a powerful data presentation and printing tool. It ensures that documents to be printed are prepared correctly and efficiently and is user-friendly with regard to viewing them on the screen.
Data composition system
The data composition system is used to generate reports and display data that has a complex structure and contains an arbitrary set of tables and charts. Its capabilities include the generation of multiple levels of detail within a single report, flexible report customization by end users, and the ability to highlight report data according to user-defined settings.
This provides visual data presentation by geographical distribution. It allows you to create reports that illustrate, for example, turnovers of specific goods in various states. You can also use a geographical schema for displaying any data related to geographical positions, such as travel directions to your office or a vehicle route.
Data analysis and forecast
This is used to implement tools for discovering dependencies that are usually hidden behind large amounts of data. For example, analysis of sales records can produce a list of product groups that are often bought together. This data can be used to recommend products to customers based on their initial choices and the dependencies discovered by this feature.
Charts are used to present data in visual format. They draw the viewer's attention to the dynamics of data change and simplify comparison of data sets. Moreover, some specific chart types can show dependencies that are usually hidden behind large amounts of data.