Clean first name in INFO smoothly

Aug 6th, 2022
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How to Clean first name in INFO

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hi everyone on this channel I create videos packed with lots of great information this video is the second in a new series about using Microsoft Excel so if youd like to learn more about excel subscribe to my channel sometimes I get a list of names that are formatted such that theres a first name a space and then the last name and thats fine but sometimes I want to sort the names by last name and its difficult to do when theyre formatted like that so Im going to teach you how to take the list of names separate it out between the first name and the last name and then put it back together such that we have the last name a comma and then the first name lets get started by highlighting the names of the people were going to visit the data tab and then were going to select text to columns when Excel looks at our data you can automatically determine that between the words theres a space so by default in this situation its going to select delimited so at this point lets just click

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Data cleansing, or cleaning, is simply the process of identifying and fixing any issues with a data set. The objective of data cleaning is to fix any data that is incorrect, inaccurate, incomplete, incorrectly formatted, duplicated, or even irrelevant to the objective of the data set.
How to clean data Step 1: Remove duplicate or irrelevant observations. Remove unwanted observations from your dataset, including duplicate observations or irrelevant observations. Step 2: Fix structural errors. Step 3: Filter unwanted outliers. Step 4: Handle missing data. Step 5: Validate and QA.
How to clean data Step 1: Remove duplicate or irrelevant observations. Remove unwanted observations from your dataset, including duplicate observations or irrelevant observations. Step 2: Fix structural errors. Step 3: Filter unwanted outliers. Step 4: Handle missing data. Step 5: Validate and QA.
Delete one or more names On the Formulas tab, in the Defined Names group, click Name Manager. In the Name Manager dialog box, click the name that you want to change. Select one or more names by doing one of the following: To select a name, click it. Click Delete. Click OK to confirm the deletion.
Data cleaning is correcting errors or inconsistencies, or restructuring data to make it easier to use. This includes things like standardizing dates and addresses, making sure field values (e.g., Closed won and Closed Won) match, parsing area codes out of phone numbers, and flattening nested data structures.
Those are: Data validation. Formatting data to a common value (standardization / consistency) Cleaning up duplicates. Filling missing data vs. erasing incomplete data. Detecting conflicts in the database.
Data cleaning is a process by which inaccurate, poorly formatted, or otherwise messy data is organized and corrected. For example, if you conduct a survey and ask people for their phone numbers, people may enter their numbers in different formats.
What are the Types of Dirty Data and How do you Clean Them? Insecure Data. Data security and privacy laws are being established left and right, imposing financial penalties on businesses that dont follow these laws to the letter. Inconsistent Data. Too Much Data. Duplicate Data. Incomplete Data. Inaccurate Data.

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