Data Import
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Data Import

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Important

This can only be done by an Admin.

Manatal allows the mass creation of candidates through the import of CSV or JSON files. This can be particularly useful when performing a data migration to Manatal for example.

Import your Data

  1. Head to the following page. Alternatively, click on "Administration" from your side menu, open the "Data Management" category and then the "Data Import" category then click on "Upload file".

Administration 1.png

Data management 2.png

Data Import 1.png

Data Import 2.png

  1. Select the data set and click "Next".
    Data Import 3.png

  2. Select the file type and click "Next". For a CSV file, continue reading below, for a JSON file follow these instructions.
    Data Import 4.png

CSV File

  1. Select a file to upload, click "Next" and then "Upload". Manatal will analyze the file and extract all the information it contains.

image.png

Data Import 6.png

Data Import 15.png

  1. Map your file's columns according to Manatal's fields.
Important

Fields marked with a red asterisk in the "Field Name" dropdown menu are required in order to proceed.

Info

Unmapped columns will not be imported to the platform.

  • 1. Column Name: Content of the first cell of each column in your CSV file. If the cell has no content, the column name will be "Unnamed: n", where n refers to the column's number.
  • 2. Field Name: Name of the field in Manatal. Match the field name with the relevant column (i.e. match the "Email" column with the "Candidate Email Address" field if you are importing candidates).
  • 3. Field Type: Data type as required by Manatal. Ensure the data contained in each column meets the requirements of each field. Data will fail to be imported to Manatal if it doesn't meet the data type's constraints. Learn more about field type constraints in the table below.
  • 4. Sample Data: Sample data extracted from each columns. Can be used to confirm the column's data corresponds to the Manatal field.

Data Import 7.png

To match a column with a field, simply click on "Select field to map to" next to the column's name, and select the relevant field from the dropdown menu.

Data Import 8.png

Data Import 18.png

Below are all the default Manatal fields that can be mapped and their respective requirements.

Field Name Required Field Type Constraints
Candidate Name Yes Text ≤ 255 char.
Candidate Description No Long text
Candidate Creator No Email Address
Candidate Owner No Email Address
Current Position No Text ≤ 255 char.
Current Company No Text ≤ 255 char.
Years of Experience No Whole Number ≥ 0
Birthdate No Date Format must be YYYY-MM-DD
Candidate Address No Text ≤ 255 char.
Country No Text ≤ 255 char.
City No Text ≤ 255 char.
Candidate Email Address No Email Address
Candidate Phone Number No Text ≤ 255 char.
Skype No Text ≤ 255 char.
Current Salary No Whole Number ≥ 0
Current Currency No ISO Currency Code Must be 3 char, currency code
Expected Salary No Whole Number ≥ 0
Expected Currency No ISO Currency Code Must be 3 char. currency code
Notice Period No Text ≤ 255 char.
Current Work Type No Work Type Either "permanent", "temporary", "contract" or "intern"
Gender No Gender Type Either "male", "female" or "other"
LinkedIn No Text ≤ 255 char.
Github No Text ≤ 255 char.
Stackoverflow No Text ≤ 255 char.
  1. If your file contains data that doesn't have its default Manatal field, it is possible to create "custom fields" by following these instructions. Once created, custom fields become visible in the "Field Name" dropdown menu and can be mapped to columns.

  2. Once you have mapped all the columns that need to be imported, click "Next".
    Data Import 10.png

  3. Select whether you want to be notified via email once the import is complete then click "Upload".
    Data Import 11.png

  4. From here you can resume your work as usual, your file will be processed in the background. To check the import's status, please visit the Data Import History page.

Data Import 12.png

Data Import 13.png

JSON File

  1. Select a file to upload, click "Next" and then "Upload". Manatal will analyze the file and extract all the information it contains.
    image.png

Data Import 14.png

Data Import 16.png

  1. Map your file's columns according to Manatal's fields.
Important

Fields marked with a red asterisk in the "Field Name" dropdown menu are required in order to proceed.

Info

Unmapped columns will not be imported to the platform.

  • 1. Column Name: All the variables contained in your JSON file.
  • 2. Field Name: Name of the field in Manatal. Match the field name with the relevant column (i.e. match the "Email" column with the "Candidate Email Address" field if you are importing candidates).
  • 3. Field Type: Data type as required by Manatal. Ensure the data contained in each column meets the requirements of each field. Data will fail to be imported to Manatal if it doesn't meet the data type's constraints. Learn more about field type constraints in the table below.
  • 4. Sample Data: Sample data extracted for each column. Can be used to confirm the column's data corresponds to the Manatal field.

Data Import 21.png

To match a column with a field, simply click on "Select field to map to" next to the column's name, and select the relevant field from the dropdown menu.

Data Import 19.png

Data Import 20.png

Below are all the default Manatal fields that can be mapped and their respective requirements.

Field Name Required Field Type Constraints
Candidate Name Yes Text ≤ 255 char.
Candidate Description No Long text
Candidate Creator No Email Address
Candidate Owner No Email Address
Current Position No Text ≤ 255 char.
Current Company No Text ≤ 255 char.
Years of Experience No Whole Number ≥ 0
Birthdate No Date Format must be YYYY-MM-DD
Candidate Address No Text ≤ 255 char.
Country No Text ≤ 255 char.
City No Text ≤ 255 char.
Candidate Email Address No Email Address
Candidate Phone Number No Text ≤ 255 char.
Skype No Text ≤ 255 char.
Current Salary No Whole Number ≥ 0
Current Currency No ISO Currency Code Must be 3 char. currency code
Expected Salary No Whole Number ≥ 0
Expected Currency No ISO Currency Code Must be 3 char. currency code
Notice Period No Text ≤ 255 char.
Current Work Type No Work Type Either "permanent", "temporary", "contract" or "intern"
Gender No Gender Type Either "male", "female" or "other"
LinkedIn No Text ≤ 255 char.
Github No Text ≤ 255 char.
Stackoverflow No Text ≤ 255 char.
Languages No List of Text Each item must be unique and ≤ 255 char
Skills No List of Text Each item must be unique and ≤ 255 char
Candidate Tags No List of Text Each item must be unique and ≤ 255 char
Candidate Industry No List of Text Each item must be unique and ≤ 255 char
Experiences No Experiences See more details below
Education No Education See more details below
Notes No Notes See more details below

Experiences

Below are the requirements for the experiences field type and a code snippet.

Data Point Required Type Constraints
position_name Yes Text ≤ 255 char.
employer Yes Text ≤ 255 char.
started_at Yes Date and Time Format must be YYYY-MM-DDThh:mm:ssZ
ended_at No Date and Time Format must be YYYY-MM-DDThh:mm:ssZ
description No Text

Code snippet:

[
	{
		"position_name": "Content Manager",
		"employer": "Walmart IT",
		"started_at": "2015-03-01",
	},
	{
		"position_name": "Marketing Trainee",
		"employer": "Walmart IT",
		"started_at": "2010-09-15",
		"ended_at": "2010-12-22",
		"description": "mostly made coffee"
	},
	// other experiences
]

Education

Below are the requirements for the education type field and a code snippet.

Data Point Required Type Constraints
school Yes Text ≤ 255 char.
started_at Yes Date and Time Format must be YYYY-MM-DDThh:mm:ssZ
degree No Degree Type Either "high school diploma", "bachelor's degree", "associate's degree", "master's degree" or "doctorate"
ended_at No Date Format must be YYYY-MM-DD
description No Text
specialization No Text ≤ 255 char.

Code snippet:

[
	{
		"school": "St Jasmin Prep school",
		"started_at": "2015-03-01",
	},
	{
		"school": "University of Zephir",
		"degree": "master's degree",
		"started_at": "2010-09-15",
		"ended_at": "2013-06-22",
		"description": "major of promotion",
		"specialization": "Computer Science"
	},
	// other educations
]

Notes

Below are the requirements for the notes type field and a code snippet.

Data Point Required Type Constraints
content Yes Text
created_at No Date and Time Format must be YYYY-MM-DDThh:mm:ssZ
creator No Text Email Address

Code snippet:

[
	{
		"content": "arrived later for first interview"
	},
	{
		"content": "Looks quite smart",
		"creator": "joseph.staline@testy.com",
		"created_at": "2010-09-15",
	},
	// other educations
]

JSON File Example

[
  {
    "name": "Angela Brown",
    "description": "Good profile, Available immediately.",
    "creator": "jane.doe@example.com",
    "owner": "john.doe@example.com",
    "job": "Software Engineer",
    "company": "ABC-corporation",
    "yearofexperience": 3,
    "birthdate": "1988-01-30",
    "skype": "a.brown1988",
    "csalary": 4000,
    "ccurrency": "USD",
    "esalary": 4500,
    "ecurrency": "USD",
    "notice": "Immediately",
    "worktype": "contract",
    "gender": "female",
    "created": "2020-10-10T15:05:00Z",
    "updated": "2020-10-10T15:05:00Z",
    "linkedin": "https://www.linkedin.com/in/angela-brown-a7a542298/",
    "github": "https://github.com/angela.brown1988",
    "stackoverflow": "https://stackoverflow.com/users/9581120/abrown"
  },
  {
    "name": "Christian T. Owen",
    "job": "Aviators",
    "company": "XYZ Airline",
    "yearofexperience": 10,
    "birthdate": "1970-12-09",
    "esalary": 150000,
    "ecurrency": "USD",
    "notice": "30 days (Negotiable)",
    "worktype": "permanent",
    "gender": "male",
    "languages": [
      "English",
      "Spanish",
      "Chinese"
    ],
    "skills": [
      "Multitasking",
      "Decision-making",
      "Leadership",
      "Communication"
    ],
    "industry": [
      "aviation"
    ],
    "experiences": [
      {
        "position": "Pilot Trainer",
        "employer": "Flynow Aitline",
        "started": "2009-05-27",
        "ended": "1995-08-30",
        "description": "3 months training"
      },
      {
        "position": "Pilot Assistant",
        "employer": "Flynow Aitline",
        "started": "2009-10-15"
      }
    ],
    "education": [
      {
        "school": "International Aviation Academy",
        "degree": "Bachelor of Science",
        "started": "2009-05-27",
        "ended": "2005-04-30",
        "description": "Full program of pilot licence and management",
        "specialization": "Professional Pilot"
      },
      {
        "school": "O'Connell university",
        "degree": "MBA",
        "started": "2005-03-18",
        "ended": "2001-08-26"
      }
    ],
    "note": [
      {
        "content": "Please request a resume from the candidate",
        "creator": "john.doe@example.com",
        "created": "2020-10-01"
      }
    ]
  }
]
  1. If your files contains data that doesn't have its default Manatal field, it is possible to create "custom fields" by following these instructions. Once created, custom fields become visible in the "Field Name" dropdown menu and can be mapped to columns.

  2. Once you have mapped all the columns that need to be imported, click "Next".
    Data Import 22.png

  3. Select whether you want to be notified via email once the import is complete then click "Upload".
    Data Import 23.png

  4. From here you can resume your work as usual, your file will be processed in the background. To check the import's status, please visit the Data Import History page.

Data Import 24.png

Data Import 25.png

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