Join data points across multiple columns and insert characters between each entry
Calculate a running total of values within a column of a table
Automatically remove extra spaces from data points using the Find/Replace object
Clean phone numbers of unwanted characters, such as parentheses or plus signs
Format numbers to round up or down, or to be displayed as currency
Find the Min or Max of a data set to quickly summarize large reports
Use if/else logic to automatically apply data labels or filter out new data as it comes in
Easily calculate a growth rate across a range of numbers
Use Google Geolocation to complete addresses and find zip codes
Extract words from data that has unwanted characters using RegEx
Remove zeros from the beginning, middle, or end of data points using RegEx
Expand or contract US state abbreviations to create addresses
Remove duplicate rows from a table based on criteria that you supply. Choose how many duplicates to keep or merge duplicates.
Combine two data sets by matching across multiple columns for a more accurate join.
Add a column to a table that sums all of the numerical cells in the same row. Useful for tabulating sales numbers or creating a balance sheet.
Summarize data by grouping it into buckets based on one or more categories.
Score prioritize and dedupe leads based on your own criteria to make sure you only get in contact with the highest probability leads at a given company.
Add data to your dataset by pulling in additional data from an external data source.
Compare two lists and remove data from the first that exists in the second in order to prevent overlapping data.
Standardize dates into a single format.
Convert rows with columns into multiple row entries.
Combine two data sets that share at least one common field/column.
Combine two data sets that have all identical columns.
Sort your data based on one or more rules.
Find and replace one or more characters based on a set of rules.
Filter rows based on one or more rules.
Split columns into multiple pieces based on a delimitter.
Split full name fields into their constituent parts (first, last, etc.) while taking into account middle names/initials, prefixes, suffixes, and other quirks.
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