The basics
Connecting your data
- Uploading data to Datashift
- Proper data format for uploading
- Working with different file types
- Types of data Datashift can read
Working with projects
Working with data
- Datafile options
- Adding and deleting data
- Linking datafiles together
- Appending datafiles together
- Re-loading data
- Making data update in real-time
- Downloading individual datafiles
- Renaming datafiles
- Data headers
- Adding meta data
- Performing calculations on your data
- Working with alerts
Working with dashboards
Working with your team
Types of data Datashift can read
Datashift supports 5 different data types:
- Date
Use to store data as a date, or a date/time pair if a single column contains both date and time. Example: April 18, 2015 15:30. - Time
Stores data as time. - String
A set of alphanumeric characters represented as text. Example: 123 My Street Name, Weather Station 7, Water Temperature. - Number
Stores data as a number. Examples: 23, 0.453, -7. - Boolean
Represents a data type with only two possible values: true or false.
Tip: When uploading your data, Datashift will automatically identity the data type for each column in your file. These settings can be changed if labelled incorrectly.