Abstract: A query of time series data stored in a database is received that specifies at least one value. The database includes (i) an index table specifying groups of segments of compressed time series data with corresponding ranges each having a lowest value and a highest value, and (ii) a segments table specifying individual segments of compressed time series data. Thereafter, using the index table, at least one group for which the specified at least one value falls within the corresponding range is identified. The segments table is then queried for the segments corresponding to the identified at least one group to generate a new segments table specifying at least one segment. Next, the at least one segment specified by the new segments table is decompressed. Data responsive to the query within the decompressed at least one segment is then identified using the specified at least one value.

Abstract: A query of time series data stored in a database is received that specifies at least one value. The database includes (i) an index table specifying groups of segments of compressed time series data with corresponding ranges each having a lowest value and a highest value, and (ii) a segments table specifying individual segments of compressed time series data. Thereafter, using the index table, at least one group for which the specified at least one value falls within the corresponding range is identified. The segments table is then queried for the segments corresponding to the identified at least one group to generate a new segments table specifying at least one segment. Next, the at least one segment specified by the new segments table is decompressed. Data responsive to the query within the decompressed at least one segment is then identified using the specified at least one value.

Abstract: A query of time series data stored in a database is received that specifies at least one value. The database includes (i) an index table specifying groups of segments of compressed time series data with corresponding ranges each having a lowest value and a highest value, and (ii) a segments table specifying individual segments of compressed time series data. Thereafter, using the index table, at least one group for which the specified at least one value falls within the corresponding range is identified. The segments table is then queried for the segments corresponding to the identified at least one group to generate a new segments table specifying at least one segment. Next, the at least one segment specified by the new segments table is decompressed. Data responsive to the query within the decompressed at least one segment is then identified using the specified at least one value.

Abstract: Companies provide a set of default personalized dynamic email addresses for both individuals and groups. The embodiments may be implemented as an extension to existing email servers, which are coupled to an existing enterprise information system. When receiving an email sent to a personalized dynamic email address, an address resolver component is used to access the definition of the email address, query for the respective recipient(s), and replace the recipient(s) in the email message. Users have the possibility to define further personalized dynamic email addresses using, for example, a web interface. The embodiments may be smoothly integrated into an existing communication infrastructure of companies without the need to change existing systems.

Abstract: A query of time series data stored in a database is received that specifies at least one value. The database includes (i) an index table specifying groups of segments of compressed time series data with corresponding ranges each having a lowest value and a highest value, and (ii) a segments table specifying individual segments of compressed time series data. Thereafter, using the index table, at least one group for which the specified at least one value falls within the corresponding range is identified. The segments table is then queried for the segments corresponding to the identified at least one group to generate a new segments table specifying at least one segment. Next, the at least one segment specified by the new segments table is decompressed. Data responsive to the query within the decompressed at least one segment is then identified using the specified at least one value.

Abstract: Companies provide a set of default personalized dynamic email addresses for both individuals and groups. The embodiments may be implemented as an extension to existing email servers, which are coupled to an existing enterprise information system. When receiving an email sent to a personalized dynamic email address, an address resolver component is used to access the definition of the email address, query for the respective recipient(s), and replace the recipient(s) in the email message. Users have the possibility to define further personalized dynamic email addresses using, for example, a web interface. The embodiments may be smoothly integrated into an existing communication infrastructure of companies without the need to change existing systems.

Abstract: In one embodiment the present invention includes a computer-implemented method comprising receiving energy information indicating an excess or deficiency of available energy for consumption by an energy consumer during a particular time period, generating energy utilization scenarios, where each energy utilization scenario models how energy is consumed by energy utilization systems under control of the energy management application over the time period, generating cost data based on each of the one or more energy utilization scenarios; and generating reconfiguration instructions to reconfigure one or more of the energy utilization systems to increase or decrease energy use by the energy consumer.

Abstract: According to an example implementation, at least one non-transitory computer-readable storage medium may include instructions stored thereon. When executed by at least one processor, the instructions may be configured to cause a computing system to select at least one function type to approximate an interval of data points within a time series, the at least one function type being less than all of a plurality of functions available to approximate the interval, while the first function type will approximate the interval of data points within a maximum allowable error, add data points from the time series to the interval, and when the first function type will no longer approximate the interval with the added data points within the maximum allowable error, select a function of a different type or a function of a different term from the plurality of functions to approximate the interval with the added data points.