Unusual file formats in your daily document management and editing processes can create immediate confusion over how to edit them. You might need more than pre-installed computer software for efficient and quick document editing. If you need to clean up data in NB or make any other simple alternation in your document, choose a document editor that has the features for you to work with ease. To handle all the formats, such as NB, opting for an editor that actually works well with all types of documents is your best choice.
Try DocHub for effective document management, irrespective of your document’s format. It has powerful online editing tools that streamline your document management process. It is easy to create, edit, annotate, and share any document, as all you need to gain access these features is an internet connection and an functioning DocHub account. Just one document solution is everything required. Do not waste time jumping between various applications for different documents.
Enjoy the efficiency of working with an instrument designed specifically to streamline document processing. See how effortless it is to revise any document, even when it is the first time you have dealt with its format. Sign up an account now and improve your whole working process.
welcome to unit 2 cleaning up raw data in this unit we will look at the raw data again and do some basic formatting and formula exercises to clean up the data so it's ready for us to analyze now we're going to be using some of the Excel skills you learn in class one in terms of formulas and functions to clean up a raw data set that isn't exactly perfect yet for analyzing a lot of times you'll get data from a database or from someone else in your company and it still has like extra characters or is not you know filtered correctly and you just have to kind of quickly massage the data a little bit to make sure it's ready for you to analyze because if you're trying to analyze data that's not correctly formatted or contains incorrect values then that's not going to be useful at all right so we're going to do some quick um it's kind of tidying up with the data before we actually analyze it and this is a very common practice because sometimes when you get data from like a database that comes...