Abstract: Systems and methods include reception of an object instance representing a date dimension member and comprising a key value, a user interface representation of the date dimension member, key values of ancestor date dimension members, and user interface representations of the one or more ancestor date dimension members, display of the user interface representation and the user interface representations of the ancestor date dimension members, reception of a request to cast the date dimension member to a higher granularity, and, in response to the request, generation of a second object instance representing a second date dimension member comprising key values of a second one or more of the ancestor date dimension members and user interface representations of the second one or more of the ancestor date dimension members, and display of the user interface representations of the second one or more of the ancestor date dimension members.

Abstract: Systems and methods include reception of an object instance representing a date dimension member and comprising a key value, a user interface representation of the date dimension member, key values of ancestor date dimension members, and user interface representations of the one or more ancestor date dimension members, display of the user interface representation and the user interface representations of the ancestor date dimension members, reception of a request to cast the date dimension member to a higher granularity, and, in response to the request, generation of a second object instance representing a second date dimension member comprising key values of a second one or more of the ancestor date dimension members and user interface representations of the second one or more of the ancestor date dimension members, and display of the user interface representations of the second one or more of the ancestor date dimension members.

Abstract: The present disclosure involves systems, software, and computer implemented methods for ranking time dimensions. One example method includes receiving a request for an insight analysis for a dataset that includes a value dimension and a set of multiple date dimensions. Each date dimension is converted into a time series and a value quality factor is determined for each time series that represents a level of data quality for the time series. A time series informative factor is determined for each time series that represents how informative the time series is within a specified time window. An insight score is determined, for each time dimension, based on the determined value quality factors and the determined time series informative factors. The insight score for the time dimension is provided, for at least some of the time dimensions.

Abstract: The present disclosure involves systems, software, and computer implemented methods for ranking time dimensions. One example method includes receiving a request for an insight analysis for a dataset that includes a value dimension and a set of multiple date dimensions. Each date dimension is converted into a time series and a value quality factor is determined for each time series that represents a level of data quality for the time series. A time series informative factor is determined for each time series that represents how informative the time series is within a specified time window. An insight score is determined, for each time dimension, based on the determined value quality factors and the determined time series informative factors. The insight score for the time dimension is provided, for at least some of the time dimensions.