It is often hard to find a platform that may deal with all your corporate demands or will provide you with suitable instruments to deal with document creation and approval. Choosing a software or platform that combines important document creation instruments that streamline any process you have in mind is critical. Even though the most in-demand file format to use is PDF, you require a comprehensive solution to handle any available file format, including xml.
DocHub ensures that all your document creation needs are taken care of. Revise, eSign, turn and merge your pages according to your requirements with a mouse click. Work with all formats, including xml, efficiently and quickly. Regardless of what file format you start working with, it is possible to convert it into a required file format. Preserve a lot of time requesting or looking for the correct document type.
With DocHub, you do not need extra time to get accustomed to our interface and editing process. DocHub is surely an easy-to-use and user-friendly platform for any individual, even all those with no tech background. Onboard your team and departments and transform document managing for your company forever. clean zip code in xml, generate fillable forms, eSign your documents, and have things done with DocHub.
Benefit from DocHub’s substantial function list and easily work with any document in any file format, including xml. Save time cobbling together third-party solutions and stay with an all-in-one platform to boost your everyday processes. Start your cost-free DocHub trial subscription today.
so were going to look at basically using FME for purely attribute data here and in the first case were going to look at address clean up so the problem that Andrew had is that he was working for campaign electoral campaign in France and the data came in and he had to put it into the nation builder program and it is a very defined schema and he have to have everything in the right order and the attributes were all over the place and they were kind of mixed up so the problem was how do you define how do you relate a specific data value to a schema column or name and and associate that so what we did here is we just used a few simple transformers we just used a string search or attribute splitter an attribute manager and based upon those things and using a regular expression we were able to first find a key pattern within the data within the strings themselves so what we did is found the postal code pattern in there and then what we did is applied that pattern to a pattern that we knew