We provide a host of
standard exports in our API
to return useful information in bulk. These API exports have the following properties:
The data contained in the API export is a reflection of the data at the time of
the request (i.e., live data).
The output will always be given in the default JSON format of the API.
Most exports use pagination, returning the data piece by piece instead of in bulk.
Especially when working with large amounts of data, the export API requests
can often take some time to complete.
As an alternative to these API exports, we provide a similar host of
file-based exports. These standard file-based output exports are triggered according to a configurable schedule (e.g. daily), transform the data to a desired format (e.g. CSV) and are uploaded to a desired, easily accessible location (e.g. S3). As such, these export integrations have the following advantages:
No time-consuming live generation required: the last export is always readily available on the desired location (i.e. S3, SFTP server).
Below we list the available export types. Some export types are configurable and can be configured in the TechWolf’s Console via the export builder or by your TechWolf representative. If no configuration options are specified, this export type is not configurable. When no configuration is specified by the user, the default settings are used.
Provides an overview of all Employees and their fields, including their current position, organizational unit, and data availability status.
The Employee info export provides an overview of all Employees and their fields.
Currently supported output formats are:
CSV or XLSX:
The CSV or XLSX represents a two-dimensional matrix, containing one row for every
Employee.
Every row has 7 values, and there is a header row present with the
following values, indicating the contents of every column (in order):
Field name
Field description
external_id
The external ID of the Employee in TechWolf.
low_data_availability
Flag indicating whether sufficient data is available for qualitative Skill inference for the given Employee.
active
Flag indicating whether the Employee will be used in matching. This is useful if an Employee is being phased out.
last_updated
Timestamp of the last update to this entity.
assigned_position
The title of the Job the Employee is currently assigned to.
assigned_position_id
The external ID of the Job the Employee is currently assigned to.
organisational_unit_X
The Organisational Unit of the Employee. Column organisational_unit_0 is the top-level Organisational Unit, column organisational_unit_1 the second-level etc.
Currently supported configurations are:
Mask external_id: mask the Employee’s external ID to protect privacy.
Include Custom Properties: the selected Custom properties will be added as a column to every row. If the Employee does not have this Custom Property, the field will be empty.
Provides an overview of all Jobs and their fields, including Job Family information, data availability status, and active status.
The Job info export provides an overview of all Jobs and their fields.
Currently supported output formats are:
CSV or XLSX:
The CSV or XLSX represents a two-dimensional matrix, containing one row for every
Job.
Every row has 7 values, and there is a header row present with the
following values, indicating the contents of every column (in order):
Field name
Field description
external_id
The external ID of the Job in TechWolf.
job_name
The name of the Job in TechWolf.
job_family
The Job Family to which this Job belongs.
job_family_group
The Job Family group to which this Job belongs
low_data_availability
Flag indicating whether sufficient data is available for qualitative Skill inference for the given Job.
active
Flag indicating whether the Job will be used in matching. This is useful when a Job is being phased out.
last_updated
Timestamp of the last update to this entity.
Currently supported configurations are:
Include Custom Properties: the selected Custom properties will be added as a column to every row. If the Job does not have this Custom Property, the field will be empty.
Maps the relationship between Courses and their associated Skills, showing which Skills are taught in each Course.
The Course Skill Profile export provides an overview of all the Skills of
every Course.
Currently supported output formats are:
CSV or XLSX:
The CSV or XLSX represents a two-dimensional matrix, containing one row for every
Skill of every Course, with Courses without Skills not being represented.
Every row has three values, and there is a header row present with the
following values, indicating the contents of every column (in order):
Field name
Field description
course_id
The external ID of the Course with the Skill in TechWolf.
Maps the relationship between Employees and their Skills, including validation states and sources of skill inference.
The Employee Skill Profile export provides an overview of all the Skills of
every Employee.
Currently supported output formats are:
CSV or XLSX:
The CSV or XLSX represents a two-dimensional matrix, containing - besides the header row -
one or more rows for every Skill of every Employee (every Skill has one row for
each of its sources if it has any, and one row otherwise), with Employees without
Skills not being represented.
The matrix has six columns, containing the following fields for every row (in order):
Field name
Field description
employee_id
The external ID of the Employee with the Skill in TechWolf.
skill_id
The external ID of the Skill in TechWolf.
skill
The name of the Skill in TechWolf.
validation_state
The validation state of the Skill; one of “validated”, “suggested”, “rejected”.
skill_source
The event type from which the Skill is inferred for this Employee (e.g. “working_history”).
skill_event_source
The source of the Skill event from which the Skill is inferred (e.g. “Workday” or “Degreed”).
Currently supported configurations are:
Mask employee_id: mask the Employee’s external ID to protect privacy.
Maps the relationship between Jobs and their required Skills, including skill types, validation states, and proficiency levels.
The Job Skill Profile export provides an overview of all the Skills of every
job. Note that only the governed Skill Profiles are taken into account, not the
suggested Skill Profiles.
Currently supported output formats are:
CSV or XLSX:
The CSV or XLSX represents a two-dimensional matrix, containing - besides the header row -
one or more rows for every Skill of every Job (every Skill has one row for each of
its Skill types), with Job without Skills not being represented.
The matrix has five columns, containing the following fields for every row (in order):
Field name
Field description
job_id
The external ID of the Job with the Skill in TechWolf.
skill_id
The external ID of the Skill in TechWolf.
skill
The name of the Skill in TechWolf.
skill_type
The type of the Skill; one of “Job-Specific”, “Family-Specific”.
validation_state
The validation state of the Skill; one of “validated”, “suggested”, “initially_validated”.
proficiency_level
The required Skill proficiency level for this Job as an integer.
critical
Indicates whether the Skill is critical for the Job.
Note that initially validated Skills for Jobs and Job Families are Skills which have been inferred after the first data load (i.e. the first iteration of the Job to Skill mapping). These Skills are used to initially populate the governed Skill profile of the Job or Job Family, but which have not been manually verified like other (normal) validated Skills. The initial validation process for Jobs and/or Job Families is not a required step in creating a Job or Job Family or managing its Skill profile(s). If initial validation was not used during data loading, the associated states can never appear in the data.
Provides comprehensive information about all Skills, including descriptions and their location in the Taxonomy.
The Skill info export provides an overview of all Skills and their description.
For Skills that are part of the Taxonomy, the location in the Taxonomy is also provided.
Currently supported output formats are:
CSV or XLSX:
The CSV or XLSX represents a two-dimensional matrix, containing - besides the header row -
a row for every Skill.
The matrix has ten columns, containing the following fields for every row (in order):
Field name
Field description
skill_id
The external ID of the Skill.
skill_name
The name of the Skill.
skill_description
The description of the Skill.
techwolf_domain
The default Domain provided by TechWolf.
taxonomy_skill_cluster_id
The external ID of the Cluster the Skill belongs to; empty for Skills that are not part of the Taxonomy.
taxonomy_skill_cluster_name
The name of the Cluster the Skill belongs to; empty for Skills that are not part of the Taxonomy
taxonomy_subdomain_id
The external ID of the Subdomain the Skill belongs to; empty for Skills that are not part of the Taxonomy; only relevant for four-level taxonomies, always empty for three-level Taxonomies.
taxonomy_subdomain_name
The name of the Subdomain the Skill belongs to; empty for Skills that are not part of the Taxonomy; only relevant for four-level taxonomies, always empty for three-level Taxonomies.
taxonomy_domain_id
The external ID of the top-level Domain the Skill belongs to; empty for Skills that are not part of the Taxonomy.
taxonomy_domain_name
The name of the top-level Domain the Skill belongs to; empty for Skills that are not part of the Taxonomy.
Shows the match score between Employees and their assigned positions, helping identify Skill gaps.
The Employee Skill Gap export provides an overview of the match score between Employees and their assigned position.
Currently supported output formats are:
CSV or XLSX:
The CSV or XLSX represents a two-dimensional matrix, containing - besides the header row - a row for every Employee-Job match.
The matrix has 3 columns, containing the following fields for every row (in order):
Field name
Field description
employee_id
The external ID of the Employee.
job_id
The external ID of the Job that the Employee is assigned to. If the Employee has no assigned position, the field is left blank.
score
The match score between the Employee and the Job, expressed as a number between 0 and 1. If the Employee has no assigned position, this value is set to 0.0.
Currently supported configurations are:
Mask employee_id: mask the Employee’s external ID to protect privacy.
Provides detailed analysis of Skill gaps between Employees and their positions, including adjacent Skills and alignment scores.
The Skill Gap Explained export provides a detailed information of the match score between Employees and their assigned positions, including adjacent Skills and how closely they align with the required Skills for their assigned position.
Currently supported output formats are:
CSV or XLSX:
The CSV or XLSX represents a two-dimensional matrix, containing - besides the header row - a row for every Skill for every Employee-Job match.
The matrix has six columns, containing the following fields for every row (in order):
Field name
Field description
employee_id
The external ID of the Employee.
job_id
The external ID of the Job that the Employee is assigned to.
status
The current status of the match (e.g., “present”, “missing”).
skill_id
The external ID of the required Skill.
adjacent_skill_id
The external ID of the most similar adjacent Skill that the Employee has.
adjacency_score
The adjacency score between the required Skill and the adjacent Skill, expressed as a number between 0 and 1.
Currently supported configurations are:
Mask employee_id: mask the Employee’s external ID to protect privacy.
Shows potential matches between Employees and Jobs within the organization, with match scores.
The internal mobility export provides an overview of potential matches between Employees and Jobs within the organisation, with their match score.
It contains both the best matching Employees for each Job and the best matching Jobs for each Employee.
Currently supported output formats are:
CSV or XLSX:
The CSV or XLSX represents a two-dimensional matrix, containing - besides the header row - a row for every Employee-Job match.
The matrix has 3 columns, containing the following fields for every row (in order):
Field name
Field description
employee_id
The external ID of the Employee.
job_id
The external ID of the Job within the organisation.
score
The match score between the Employee and the Job, expressed as a number between 0 and 1.
Currently supported configurations are:
Mask employee_id: mask the Employee’s external ID to protect privacy.
Provides detailed analysis of potential matches between Employees and Jobs, including Skill-level comparisons.
The internal mobility explained export provides an overview of potential matches between Employees and Jobs within the organisation, including adjacent Skills and how closely they align with the required Skills for the job.
This export contains both the best matching Employees for each Job and the best matching Jobs for each Employee.
Currently supported output formats are:
CSV or XLSX:
The CSV or XLSX represents a two-dimensional matrix, containing - besides the
header row - a row for every Skill of every Employee-Job match.
The matrix has 6 columns, containing the following fields for every row (in order):
Field name
Field description
employee_id
The external ID of the Employee.
job_id
The external ID of the Job within the organization.
status
The current status of the Internal Mobility match (e.g., “present”, “missing”).
skill_id
The external ID of the required Skill.
adjacent_skill_id
The external ID of the most similar adjacent Skill that the Employee has.
adjacency_score
The adjacency score between the required Skill and the adjacent Skill, expressed as a number between 0 and 1.
Currently supported configurations are:
Mask employee_id: mask the Employee’s external ID to protect privacy.
Shows the best suited Employees for every Job within the organization, with match scores.
The Matching Employees for Job export provides an overview of the best suited Employees for every Job within the organization, with their match score.
Currently supported output formats are:
CSV or XLSX:
The CSV or XLSX represents a two-dimensional matrix, containing - besides the header row - a row for every Employee-Job match.
The matrix has 3 columns, containing the following fields for every row (in order):
Field name
Field description
employee_id
The external ID of the Employee.
job_id
The external ID of the Job within the organisation.
score
The match score between the Employee and the Job, expressed as a number between 0 and 1.
Currently supported configurations are:
Mask employee_id: mask the Employee’s external ID to protect privacy.
Set the score_min_threshold: only include Employees with a match score above this threshold, higher values mean stricter matching. When not set, the default is used.
Set the max_matches_per_entity: limit how many matching Employees are shown for each Job. Higher numbers give you more options but significantly increases data size. When not set, the default limit is used.
Filters: add custom filters on Custom Properties to further refine the results. We currently support 3 types of filters:
Custom Property filter: filter out all Employees for which the given Custom Property does not match the condition defined by an operator and a value.
Custom Property equal filter: filter out all Employees for which the Custom Property is not equal to the Custom Property of the Job.
Custom Property is in filter: filter out all Employees for which the list Custom Property does not contain the Custom Property of the Job.
Provides detailed analysis of the best suited Employees for every Job within the organization, including Skill-level comparisons.
The Matching Employees for Job Explained export provides an overview of the best suited Employees for every Job within the organization, including adjacent Skills and how closely they align with the required Skills for the job.
Currently supported output formats are:
CSV or XLSX:
The CSV or XLSX represents a two-dimensional matrix, containing - besides the
header row - a row for every Skill of every Employee-Job match.
The matrix has 6 columns, containing the following fields for every row (in order):
Field name
Field description
employee_id
The external ID of the Employee.
job_id
The external ID of the Job within the organization.
status
The current status of the Internal Mobility match (e.g., “present”, “missing”).
skill_id
The external ID of the required Skill.
adjacent_skill_id
The external ID of the most similar adjacent Skill that the Employee has.
adjacency_score
The adjacency score between the required Skill and the adjacent Skill, expressed as a number between 0 and 1.
Currently supported configurations are:
Mask employee_id: mask the Employee’s external ID to protect privacy.
Set the score_min_threshold: only include Employees with a match score above this threshold, higher values mean stricter matching. When not set, the default is used.
Set the max_matches_per_entity: limit how many matching Employees are shown for each Job. Higher numbers give you more options but significantly increases data size. When not set, the default limit is used.
Filters: add custom filters on Custom Properties to further refine the results. We currently support 3 types of filters:
Custom Property filter: filter out all Employees for which the given Custom Property does not match the condition defined by an operator and a value.
Custom Property equal filter: filter out all Employees for which the Custom Property is not equal to the Custom Property of the Job.
Custom Property is in filter: filter out all Employees for which the list Custom Property does not contain the Custom Property of the Job.
Shows the best suited Jobs for every Employee within the organization, with match scores.
The Matching Jobs for Employee export provides an overview of the best suited Jobs for every Employee within the organization, with their match score.
Currently supported output formats are:
CSV or XLSX:
The CSV or XLSX represents a two-dimensional matrix, containing - besides the header row - a row for every Employee-Job match.
The matrix has 3 columns, containing the following fields for every row (in order):
Field name
Field description
employee_id
The external ID of the Employee.
job_id
The external ID of the Job within the organisation.
score
The match score between the Employee and the Job, expressed as a number between 0 and 1.
Currently supported configurations are:
Mask employee_id: mask the Employee’s external ID to protect privacy.
Set the score_min_threshold: only include Jobs with a match score above this threshold, higher values mean stricter matching. When not set, the default is used.
Set the max_matches_per_entity: limit how many matching Jobs are shown for each Employee. Higher numbers give you more options but significantly increases data size. When not set, the default limit is used.
Filters: add custom filters on Custom Properties to further refine the results. We currently support 3 types of filters:
Custom Property filter: filter out all Jobs for which the given Custom Property does not match the condition defined by an operator and a value.
Custom Property equal filter: filter out all Jobs for which the Custom Property is not equal to the Custom Property of the Employee.
Custom Property is in filter: filter out all Jobs for which the list Custom Property does not contain the Custom Property of the Employee.
Provides detailed analysis of the best suited Jobs for every Employee within the organization, including Skill-level comparisons.
The Matching Jobs for Employee Explained export provides an overview of the best suited Jobs for every Employee within the organization, including adjacent Skills and how closely they align with the required Skills for the job.
Currently supported output formats are:
CSV or XLSX:
The CSV or XLSX represents a two-dimensional matrix, containing - besides the
header row - a row for every Skill of every Employee-Job match.
The matrix has 6 columns, containing the following fields for every row (in order):
Field name
Field description
employee_id
The external ID of the Employee.
job_id
The external ID of the Job within the organization.
status
The current status of the Internal Mobility match (e.g., “present”, “missing”).
skill_id
The external ID of the required Skill.
adjacent_skill_id
The external ID of the most similar adjacent Skill that the Employee has.
adjacency_score
The adjacency score between the required Skill and the adjacent Skill, expressed as a number between 0 and 1.
Currently supported configurations are:
Mask employee_id: mask the Employee’s external ID to protect privacy.
Set the score_min_threshold: only include Jobs with a match score above this threshold, higher values mean stricter matching. When not set, the default is used.
Set the max_matches_per_entity: limit how many matching Jobs are shown for each Employee. Higher numbers give you more options but significantly increases data size. When not set, the default limit is used.
Filters: add custom filters on Custom Properties to further refine the results. We currently support 3 types of filters:
Custom Property filter: filter out all Jobs for which the given Custom Property does not match the condition defined by an operator and a value.
Custom Property equal filter: filter out all Jobs for which the Custom Property is not equal to the Custom Property of the Employee.
Custom Property is in filter: filter out all Jobs for which the list Custom Property does not contain the Custom Property of the Employee.
Shows the configuration of peer groups and their member companies.
The Market info export provides an overview of the different peer groups that are configured, and which companies are in each peer group.
A peer group consists of a list of companies used to create external market Skill Profiles for Jobs.
Currently supported output formats are:
CSV or XLSX:
The CSV or XLSX represents a two-dimensional matrix, containing one row for every company of every peer group.
Every row has two values, and there is a header row present with the following values,
indicating the contents of every column (in order):
Shows the Skills required by companies in different peer groups for each Job.
The Market Skill Profiles export provides an overview of all Skills required by the companies in the different
peer groups, for every Job.
Currently supported output formats are:
CSV or XLSX:
The CSV or XLSX represents a two-dimensional matrix,
containing one row for every market Skill of every Job-peer group combination,
with Job-peer group combinations without market Skills not being represented.
The matrix has four columns, containing the following fields for every row (in order)
Field name
Field description
job_id
The external ID of the Job with the Skill in TechWolf.
Shows alignment scores between Jobs and their peer group market Skill Profiles, in both directions.
The Market Comparison export provides an overview of alignment scores between Jobs and their peer group market Skill Profiles, including both Job to market (how well the Job covers peer requirements) and market to Job (how well peers cover Job requirements) alignment scores.
Currently supported output formats are:
CSV or XLSX:
The CSV or XLSX represents a two-dimensional matrix, containing one row for every Job-peer group combination.
The matrix has four columns, containing the following fields for every row (in order):
Field name
Field description
job_id
The external ID of the Job in TechWolf.
peer_group
The name of the peer group in TechWolf.
job_to_peer_score
The Job to market alignment score, indicating how well the Job Skill Profile covers the Skill requirements of the peer Skill Profile.
peer_to_job_score
The market to Job alignment score, indicating how well the peer Skill Profile covers the Skill requirements of the Job Skill Profile.
Provides detailed analysis of alignment between Jobs and peer group Skill Profiles, including Skill-level comparisons.
The Market Comparison Explained export provides detailed alignment analysis between Jobs and their peer group market Skill Profiles, including comprehensive breakdowns of how well Job Skill Profiles match peer requirements and vice versa, with detailed Skill-level comparisons and gap analysis.
Currently supported output formats are:
CSV or XLSX:
The CSV or XLSX represents a two-dimensional matrix, containing one row for every Skill of every Job-peer group combination.
The matrix has eight columns, containing the following fields for every row (in order):
Field name
Field description
job_id
The external ID of the Job in TechWolf.
peer_group
The name of the peer group in TechWolf.
skill_id
The external ID of a Skill in TechWolf, that is present in the Job Skill Profile and/or peer Skill profile.
skill_status
The current status of the Skill in the profile (e.g., “literal_overlap”, “peer_skill_covered_by_adjacent_job_skill”, “job_skill_covered_by_adjacent_peer_skill”, “peer_skill_missing_in_job_profile”, “job_skill_missing_in_peer_profile”). Indicates whether the Skill is present in both the Job and peer Skill Profile, sufficiently covered by an adjacent Skill, or missing in one of the Skill Profiles.
job_adjacent_skill_id
The external ID of the most similar adjacent Skill in the Job Skill Profile.
peer_adjacent_skill_id
The external ID of the most similar adjacent Skill in the peer Skill Profile.
job_adjacency_score
The adjacency score between the Skill and the adjacent Job Skill.
peer_adjacency_score
The adjacency score between the Skill and the adjacent peer Skill.
We support the use of Amazon S3 buckets as the
location the above-mentioned output integrations can be shared. These buckets
are owned and managed by TechWolf, but will be made accessible to you to fetch
the export files.
Export output files will be located on your bucket, named techwolf-X (with ‘X’
being your company name or abbreviation), under the output/exports directory.
The names of the files can be configured per file type, but the names must
always contain the date at which they were created in one of the supported date
formats. For compatibility reasons, names cannot contain semicolons (’:’) or
periods (’.’).
We also support the use of a private SFTP server to share the above-mentioned
output integrations. You are free to set up and manage an SFTP server on your end,
and you may specify the destinition folder where the integration files should be stored.
To establish the connection with your SFTP server, please provide the following details:
Host (servername or IP address)
Username for authentication
We support two authentication methods:
Password authentication: You provide the password associated with the specified username.
Key-based authentication: We will generate and store a private SSH key securely within our system
and provide you with the corresponding public SSH key. You will need to install this public key on
your SFTP server (e.g., in the authorized_keys file) to enable access.
