Abstract: Aspects of the present disclosure provide techniques for generating relevant attributes data for benchmark comparison based on geospatial boundaries. According to certain embodiments, based on a geospatial-based query using the coordinates of a company, a first group of companies is found within a first radius of the company. The first group of companies is further queried based on a financial metric within a range of the same metric of the company. If the query results in a statistically significant number of companies in the first group of companies, financial attributes of each of the first group of companies are aggregated to develop a benchmark. If the query results in too few companies, a second geospatial-based query is performed at a second radius greater than the first radius. Further iterations of geospatial-based queries are performed at increasing radii until a statistically significant number of companies is found to develop a benchmark.

Abstract: A data flow design system is presented that includes support for both static elements and dynamic elements. Thus, the data flow design system provides a design environment graphical tool to users to design data flows that leverage both the repeatability of static elements and the adaptability of dynamic elements. Static elements process data that typically do not change over time, while dynamic elements process data that do change. For instance, new data fields are added to an input data source of a data flow. The dynamic elements automatically link the new data fields to mapping fragments of the data flow. Mapping fragments process data based on configuration parameters including expression and filter rules. Users use a user interface of the design environment to view and add mapping fragments, static links, and dynamic links to the data flow.

Abstract: A data flow design system is presented that includes support for both static elements and dynamic elements. Thus, the data flow design system provides a design environment graphical tool to users to design data flows that leverage both the repeatability of static elements and the adaptability of dynamic elements. Static elements process data that typically do not change over time, while dynamic elements process data that do change. For instance, new data fields are added to an input data source of a data flow. The dynamic elements automatically link the new data fields to mapping fragments of the data flow. Mapping fragments process data based on configuration parameters including expression and filter rules. Users use a user interface of the design environment to view and add mapping fragments, static links, and dynamic links to the data flow.