1. A method comprising: accessing a first schema comprising a first plurality of business entities including a first business entity, the first business entity having a first name in the first schema; accessing a second schema comprising a second plurality of business entities including the first business entity, the first business entity having a second name in the second schema; generating, by one or more processors, from the first schema and the second schema, a merged schema comprising a third plurality of business entities, including a single instance of the first business entity; storing, by the one or more processors, the merged schema in a database; extracting a first sequence of words from the first name of the first business entity; extracting a second sequence of words from the second name of the first business entity; generating candidate phrases for the business entity from the first and second sequences of words; ranking the candidate phrases for the first business entity; analyzing, by the one or more processors, candidate sets of labels for the third plurality of business entities, each candidate set of labels including a label for each business entity of the third plurality of business entities, no two business entities having the same label in the candidate set of labels, the label for the first business entity being selected from the candidate phrases for the first business entity; assigning labels to each business entity of the third plurality of business entities based on the analysis of the candidate sets of labels; receiving data stored using the first schema; converting the received data to the merged schema; and causing presentation of the converted data using the assigned labels.
1. A method comprising: accessing a first schema comprising a first plurality of business entities including a first business entity, the first business entity having a first name in the first schema; accessing a second schema comprising a second plurality of business entities including the first business entity, the first business entity having a second name in the second schema; generating, by one or more processors, from the first schema and the second schema, a merged schema comprising a third plurality of business entities, including a single instance of the first business entity; storing, by the one or more processors, the merged schema in a database; extracting a first sequence of words from the first name of the first business entity; extracting a second sequence of words from the second name of the first business entity; generating candidate phrases for the business entity from the first and second sequences of words; ranking the candidate phrases for the first business entity; analyzing, by the one or more processors, candidate sets of labels for the third plurality of business entities, each candidate set of labels including a label for each business entity of the third plurality of business entities, no two business entities having the same label in the candidate set of labels, the label for the first business entity being selected from the candidate phrases for the first business entity; assigning labels to each business entity of the third plurality of business entities based on the analysis of the candidate sets of labels; receiving data stored using the first schema; converting the received data to the merged schema; and causing presentation of the converted data using the assigned labels. 6. The method of claim 1 , wherein the ranking of the candidate phrases for the first business entity includes ranking the candidate phrases for the first business entity based on an inverse of a frequency of words in each candidate phrase in descriptions of all business entities in the third plurality of business entities.