Abstract: Methods and system are disclosed that relate to optimizing search for data. In one aspect, an attribute vector may include unique value identifiers and be associated with a dictionary structure. For a unique value identifiers stored in an attribute vector and associated with the dictionary structure, start address and end address associated with the unique value identifiers is computed. Based on the computation, a range of positional addresses associated with the unique value identifiers may be generated and stored in a data structure. Upon receiving a request to search for data, the range of positional addresses in which the unique value identifiers may be searched is determined. Based on the determination, a database search engine optimizes the search for data in the attribute vector.

Abstract: Methods and system are disclosed that generate an execution schedule to optimize a transformation of business. In one aspect, from multiple tables residing in multiple databases and storing business data associate with multiple business management systems, dependencies between the tables may be determined based on attributes associated with the tables. When execution time for transforming business data exists, a decrease time algorithm or a critical path algorithm may be executed to generate execution schedule and to calculate processor idle times during the transformation of business data. Based on the calculated processor idle times, whether or not to execute a local optimization algorithm may be determined. Based on the determination, execution schedule that optimize the transformation of business data may be generated. The transformation of business data may be executed based to the generated execution schedule that optimizes a time consumed for transforming the business data in the tables.

Abstract: Methods and system are disclosed that relate to optimizing search for data. In one aspect, an attribute vector may include unique value identifiers and be associated with a dictionary structure. For a unique value identifiers stored in an attribute vector and associated with the dictionary structure, start address and end address associated with the unique value identifiers is computed. Based on the computation, a range of positional addresses associated with the unique value identifiers may be generated and stored in a data structure. Upon receiving a request to search for data, the range of positional addresses in which the unique value identifiers may be searched is determined. Based on the determination, a database search engine optimizes the search for data in the attribute vector.

Abstract: Methods and system are disclosed that generate an execution schedule to optimize a transformation of business. In one aspect, from multiple tables residing in multiple databases and storing business data associate with multiple business management systems, dependencies between the tables may be determined based on attributes associated with the tables. When execution time for transforming business data exists, a decrease time algorithm or a critical path algorithm may be executed to generate execution schedule and to calculate processor idle times during the transformation of business data. Based on the calculated processor idle times, whether or not to execute a local optimization algorithm may be determined. Based on the determination, execution schedule that optimize the transformation of business data may be generated. The transformation of business data may be executed based to the generated execution schedule that optimizes a time consumed for transforming the business data in the tables.