DataMatch Tool
DataMatch Tool™ enhances the possibilities to do extensive research using databases from different providers.
With the proliferation of electronic databases today, researchers are able to address complex questions using multiple variables. But collecting data from multiple databases brings integration issues that cannot be solved easily. Retrieving data close to a specific date is also a complex task to perform. Company identifiers are often missing or erroneous and company names are written in multiple ways (IBM / International Business Machines / Int’l Bus. Mach.), which makes perfect matching impossible. Legal endings of company names are also often written differently (Incorporated, Limited, Corporation / Inc., Ltd., Corp.) or missing altogether. Available database software on the market such as Microsoft Office Access will only link fields that match perfectly, making it necessary to go trough entries one by one to match relevant information between databases.
Luckily, a group of researchers have developed a convenient software with a powerful algorithm to address this problem. DataMatch Tool™ (DMT™) can rapidly find perfect matches and suggest one or several close matches based on either an identifier or the company names. When only some of the firms bear an identifier, DMT™ can look for those in a first run and pursue its search using the company names. In this case, fuzzy match technology is used to consider misspelling or possible spelling variations as valid matches. A user friendly interface makes it very easy to accept or reject suggestions or to create new matches.
DMT™ is very easy to use. Basically, it compares two files (Table A and Table B) to find matches in one or several fields at a time. Fields to be matched can be of any nature : company names, product descriptions or people names. The tables can be imported from Excel or Access or as plain text files. Typically, Table A contains several records to be matched with other records in a reference table (Table B). In a research context, Table A would represent the sample under study. For instance, the sample might be composed of a group of companies that have been involved in a merger. Depending on the research design, the researcher might need to obtain different types of information such as accounting data or stock market values. The reference table (Table B) would contain this data. Tables A and B can contain any type of data. Three sets of libraries (noise, predefined matches and synonyms) can be customized to enhance the matching power of DMT™.
DMT™ can also help gathering data around or close to a specific date to perform event studies or retrieve data based on relative dates.
For more information, please visit : www.datamatchtool.com
Or contact us at : contact@datamatchtool.com
