Abstract: Overlay visualizations are implemented utilizing data of a data layer. A table comprises a measure and two or more different dimensions mapping to a same value range. For visualization, the measure for those dimensions may be plotted along a common axis in a same chart. Accordingly, a query executes a UNION of multiple subqueries. A first subquery aggregates the first dimension over the value range, injecting a constant formula field to identify the original first dimension. A second subquery aggregates the second dimension over the value range, again injecting the constant formula field to identify the original second dimension. UNION of these subquery results presents one larger dataset for input to the overlying visualization layer. The constant formula field may be relied upon to differentiate between the combined dimensions on the common axis, allowing association of the measure values with the original dimensions in the displayed plot (e.g., via coloring).

Abstract: A system includes determination of a query context comprising a measure and one or more dimension values of a data source, generation of a query of the data source for the measure over time and aggregated over the one or more dimension values, reception of a result set of the query, providing of the result set to a predictive analysis engine, and reception of forecast data based on the result set, the forecast data comprising forecast values of the measure over time, aggregated over the one or more dimension values.

Abstract: A system includes determination of a query context comprising a measure and one or more dimension values of a data source, generation of a query of the data source for the measure over time and aggregated over the one or more dimension values, reception of a result set of the query, providing of the result set to a predictive analysis engine, and reception of forecast data based on the result set, the forecast data comprising forecast values of the measure over time, aggregated over the one or more dimension values.

Abstract: Embodiments implement contextual styling of chart elements based upon metadata stored in the data layer associated with chart data. In creating a chart for the associated data, a visualization engine references the metadata to render appearance of a chart element according to the relevant metadata. This maintains consistent appearance of chart elements depicting the same data, across different chart types (e.g., bar chart and pie chart). The metadata may be stored in the data layer as a JavaScript Object Notation (JSON) object, together with a corresponding identifier (e.g., representing a unique —story/-page/-chart/-chart element combination). Metadata within the data layer may determine appearance of chart data, chart axes, chart legends, and/or chart borders. The visualization engine may consult precedence rules governing application of different metadata (e.g., as between the appearance of a dimension vs. the appearance of a specific tuple including that dimension).

Abstract: Overlay visualizations are implemented utilizing data of a data layer. A table comprises a measure and two or more different dimensions mapping to a same value range. For visualization, the measure for those dimensions may be plotted along a common axis in a same chart. Accordingly, a query executes a UNION of multiple subqueries. A first subquery aggregates the first dimension over the value range, injecting a constant formula field to identify the original first dimension. A second subquery aggregates the second dimension over the value range, again injecting the constant formula field to identify the original second dimension. UNION of these subquery results presents one larger dataset for input to the overlying visualization layer. The constant formula field may be relied upon to differentiate between the combined dimensions on the common axis, allowing association of the measure values with the original dimensions in the displayed plot (e.g., via coloring).

Abstract: An irrigation controller (101a, 101b) includes a receiver (105a, 105b) and a processor. The processor is configured to facilitate receiving, in accordance with the receiver, an indication of rainfall which is forecast to fall on one or more locations (109a, 109b). Further, the processor is programmed to determine a minimum allowable water level and an optimal water level at the locations (109a, 109b). The processor is also programmed to determine water available at the locations (109a, 109b). In addition, the processor is programmed to determine an amount of water to be delivered so that the water available and the forecast rainfall exceed the minimum allowable water level, and avoid exceeding the optimal water level.