Automatic modeling of column and pivot table layout tabular data
Abstract:
A system for modeling tabular data containing column and pivot table formats. Tabular data containing categorical and/or metric data is received and the metric data is determined. A group of identified columns are grouped comprising one or more adjacent columns containing similar metric data. Adjacent columns with unique metric types are not grouped. A number of columns (n) and rows (m) are identified. A table is generated comprising two sub-tables. A first sub-table is populated by metric data of ungrouped columns, repeated n times, containing ungrouped column category labels. A second sub-table with two columns, populated with grouped column category labels, repeated m times, and metric data from the grouped columns respectively. Category labels of the second table are determined via semantic analysis. The generated table, containing (n×m)+1 rows, is communicated to a model library.
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