[ Advanced Section | FAQs]
Bloomer mock is great tool for fake random mock data production. There is no limit on record generation. It provides clean intuitive user interface to generate plain data such as EXCEL, CSV, HTML and nested data such as JSON, XML etc.
Features
AI support for values |
Advanced javascript for value generation and manipulation |
No limit on data generation |
Multiple export format supported |
Plain and Nested data support |
Support existing json schema and json data upload |
Around 1.5K pre-defined data keys to choose |
User define data list supported |
JSON EXCEL CSV XML HTML TABLE
Screen Layout
Screen consist of two sections :
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Data Definition : Data definition part is for defining structure of data to be generated.
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Data Preview : Preview screen shows preview of data based on structure defined
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Tip
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Preview pane is removed in mobile view with Preview button dialog box. |
Data Definition
Data definition screen is used to define data structure. Screen is build with tree view which is intuitive for nested and plain data structure. User can define attributes in screen to define the structure.
To generate data user has to define attributes(columns in case of csv), each attribute consist of following -
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Name of Attribute (Column name) : Specify required attribute name for data field. In case of JSON this corresponds to json field name and in case of CSV format attribute name corresponds to column name.
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Value of Attribute (Column value) : Attribute value is randomly set from list of values. Example — name, country code, book title, actors etc.
Attribute values can be picked --
Based on pre-defined list of around 1.5 K categories
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AI based generated list
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User defined list
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Generate through javascript program
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Data Type : Data type define the type of generated data for attribute or column. For most people string data type is sufficient for data production. Other data type give granular control for generation of data for JSON format.
Different data types supported :-
string : Sufficient for most use cases. Example — "West Cherry", "Law", "1", "2", "West Cherry 1.2", "true", "false" etc.
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number : Number data type is specifically used for generation of any number which include integer, decimal etc. Example — 1, 2, 2.6, -2 etc.
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boolean : Boolean data type is used to define either true or false value.
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object : Object data type is used for defining nested attribute(attribute that contains child attributes).
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array : Array data type is used to define list of values. Example — [“West Cherry”, “Law”]
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Control Buttons
Generation screen provide few controls button that help in defining attributes such as add, delete, edit and more button.
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Add — Add button is used to add child attribute -
Edit — Edit button is used to edit selected attribute -
Delete — Delete selected
attribute -
Save — Save currently edited attribute -
More — More button provide extra configuration based on data type
Data Preview
Right pane of screen is data preview pane which shows preview of output data showing 10
records based on the output format and data definition.
For each change in data definition, data preview pane should output of the latest
definition.
Example
Generate CSV with 2 columns - name and age
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name : characters data type
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age : number data type
Steps to generate CSV
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Add 2 attributes to data definition screen. For first attribute set attribute name as name and for second attribute set name as age
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Click on save icon
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Select value for both the attributes by clicking on value selection box
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Selection box list pre-defined values to choose from list of thousand of attributes. For this example let’s choose
Artist → Names
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For age attribute let’s select define custom values. To create custom values click on more icon.
Add minimum and maximum value, in case of age let's select minimum as 10 and maximum as 80 to set random value for age between 10 and 80.
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Preview screen will show preview of 10 records
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Now it’s time to generate the data.
Select number of rows to be generated and data format as CSV. Click on Generate button to generate csv data.
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Below is output of data
