18. A system that allows structured data analysis tools to analyze data in an analysis schema comprising: a core server computer executing at least one software module comprising: ODBC code; JDBC code; code to pre-populate metadata of the structured data analysis tools with tables, columns, attributes, data and metrics from an analysis schema without performing tool customization or application specific setup; and wherein the analysis schema comprises a set of tables that provides structure to unstructured data, wherein at least one of the set of tables comprises master entities, the master entities comprising (i) a group of entities that appear in multiple documents that are the same actual entity, (ii) entities that are spelled differently that are the same actual entity, or (iii) entities that have multiple names that are the same actual entity; wherein unstructured data is read from a source of unstructured data; wherein a copy of the unstructured data is written to a capture schema, wherein the capture schema comprises a set of tables to store the copy of the unstructured data and attributes of the unstructured data; wherein the copy of the unstructured data is sent to one or more transformation tools; wherein a natural-language processing transformation tool parses the copy of the unstructured data to extract sentences from the copy of the unstructured data and then further extract from the extracted sentences sentence-level natural-language processed entities, wherein the sentence-level natural-language processed entities are at least noun phrases; wherein a linguistic processing transformation tool extracts sentence-level linguistically-processed relationships, wherein the sentence-level linguistically-processed relationships comprise associations between the sentence-level natural-language processed entities; wherein the sentence-level natural-language processed entities and the sentence-level linguistically-processed relationships are sent from the one or more transformation tools to a categorization tool; wherein the categorization tool determines categorization data elements present in each extracted sentence, wherein the categorization data elements are based on the sentence-level natural-language processed entities and the sentence-level linguistically-processed relationships, and are placed within predetermined categories, and a confidence level for each categorization data element, wherein the confidence level for each categorization data element combines one or more data points linked to the sentence-level natural-language processed entities and the sentence-level linguistically-processed relationships to create a statistically-oriented calculation of confidence assigned to the categorization data element; wherein the categorization data elements from the categorization tool and the sentence-level natural-language processed entities and the sentence-level linguistically-processed relationships from the one or more transformation tools are written in a structured database schema; wherein the confidence level for at least one of the categorization data elements is output for use in structured data tools; and wherein the one or more data points are selected from the group consisting of: confidence score of value provided by the one or more transformation tools, number of relationships found in the source of unstructured data compared to the size of the source of unstructured data, average number of relationships per kilobyte for relationships of the same type as a selected relationship, number of entities found to be associated with a relationship compared to an average number of entities for relationships in a same hierarchy, number of times similar relationships have been found in the past, number of entities that are grouped together to form a master entity, a number of times an entity occurred in the source of unstructured data compared to the average number of occurrences for entities in the same hierarchy, weighted confidences based on hierarchy of a relationship or entity, measures of data extraction confidence integrated with the system via an analysis schema, measures based on a fullness of a relationship's attributes, measures based on the confluence of a same finding by multiple transformation tools, measures based on the source of the unstructured data, and combinations thereof.
18. A system that allows structured data analysis tools to analyze data in an analysis schema comprising: a core server computer executing at least one software module comprising: ODBC code; JDBC code; code to pre-populate metadata of the structured data analysis tools with tables, columns, attributes, data and metrics from an analysis schema without performing tool customization or application specific setup; and wherein the analysis schema comprises a set of tables that provides structure to unstructured data, wherein at least one of the set of tables comprises master entities, the master entities comprising (i) a group of entities that appear in multiple documents that are the same actual entity, (ii) entities that are spelled differently that are the same actual entity, or (iii) entities that have multiple names that are the same actual entity; wherein unstructured data is read from a source of unstructured data; wherein a copy of the unstructured data is written to a capture schema, wherein the capture schema comprises a set of tables to store the copy of the unstructured data and attributes of the unstructured data; wherein the copy of the unstructured data is sent to one or more transformation tools; wherein a natural-language processing transformation tool parses the copy of the unstructured data to extract sentences from the copy of the unstructured data and then further extract from the extracted sentences sentence-level natural-language processed entities, wherein the sentence-level natural-language processed entities are at least noun phrases; wherein a linguistic processing transformation tool extracts sentence-level linguistically-processed relationships, wherein the sentence-level linguistically-processed relationships comprise associations between the sentence-level natural-language processed entities; wherein the sentence-level natural-language processed entities and the sentence-level linguistically-processed relationships are sent from the one or more transformation tools to a categorization tool; wherein the categorization tool determines categorization data elements present in each extracted sentence, wherein the categorization data elements are based on the sentence-level natural-language processed entities and the sentence-level linguistically-processed relationships, and are placed within predetermined categories, and a confidence level for each categorization data element, wherein the confidence level for each categorization data element combines one or more data points linked to the sentence-level natural-language processed entities and the sentence-level linguistically-processed relationships to create a statistically-oriented calculation of confidence assigned to the categorization data element; wherein the categorization data elements from the categorization tool and the sentence-level natural-language processed entities and the sentence-level linguistically-processed relationships from the one or more transformation tools are written in a structured database schema; wherein the confidence level for at least one of the categorization data elements is output for use in structured data tools; and wherein the one or more data points are selected from the group consisting of: confidence score of value provided by the one or more transformation tools, number of relationships found in the source of unstructured data compared to the size of the source of unstructured data, average number of relationships per kilobyte for relationships of the same type as a selected relationship, number of entities found to be associated with a relationship compared to an average number of entities for relationships in a same hierarchy, number of times similar relationships have been found in the past, number of entities that are grouped together to form a master entity, a number of times an entity occurred in the source of unstructured data compared to the average number of occurrences for entities in the same hierarchy, weighted confidences based on hierarchy of a relationship or entity, measures of data extraction confidence integrated with the system via an analysis schema, measures based on a fullness of a relationship's attributes, measures based on the confluence of a same finding by multiple transformation tools, measures based on the source of the unstructured data, and combinations thereof. 19. The system of claim 18 , wherein the core server computer further comprises pre-built reports, graphs and dashboards.