Data Dictionary

Dictionary contains explanations and examples of all data fields available in the Glassdoor Reviews dataset.

All personal/company information mentioned within this context is entirely fictional and is solely intended for illustrative purposes.

Data points by category

1. Metadata

2. Review details

3. Ratings

The data points in the example snippets have been rearranged for better grouping. To see where a specific data point stands, check the full data sample here.

---

Metadata

Record metadata

Data point	Description	Data type
meta	Contains metadata about the record	Object
created_at_date	Date when the record was initially scraped	Array of numbers (integer)
created_at_timestamp	Unix timestamp for when the record was first scraped	Float
updated_at_date	Date when the record was last updated	Array of numbers (integer)
updated_at_timestamp	Unix timestamp for when the record was last updated	Float
version_id	Identifier for the dataset version	String
source	Source from which the record was obtained	String
object	Data object type	String
is_deleted	Indicates if the record is available on Glassdoor	Boolean

See a snippet of the dataset for reference:

Meta fields

		"_meta": {
			"source": "glassdoor",
			"object": "review",
			"created_at_date": [
				2021,
				7,
				29
			],
			"created_at_timestamp": 1627576114.978239,
			"updated_at_date": [
				2024,
				5,
				1
			],
			"updated_at_timestamp": 1714587034.936207,
			"version_id": "454126bb",
			"is_deleted": false
		},

Review metadata

Data point	Description	Data type
doc	Dataset starting point	Object
language	Review language	String
company_id	Company identifier in our database	String
source_id	Record identifier on Glassdoor	String
date	Review publish date in ISO 8601 format	String
id	Record identifier in our database	String

See a snippet of the dataset for reference:

Review meta information

"doc": {
"language": "eng",
"company_id": "1116468",
"source_id": "ITZ-RVW54008356",
"date": "2022-05-31T20:54:36.170",
"id": "glassdoor_review_Microsoft-RVW64931797",

Review details

Review author

Data point	Description	Data type
author_location	Author's location	String
author_title	Author's job title	String
author_status	Author's employment status	String
is_current	Indicates whether the review author is currently employed by the company	Boolean
author_employment_length	Author's employment length in years. The field is optional	Integer

See a snippet of the dataset for reference:

Review author

"doc": {
  "author_location": "Los Angeles, CA",
  "author_title": "Sales Specialist",
  "author_status": "REGULAR",
  "is_current": true,
  "author_employment_length": 2,

Review content

Data point	Description	Data type
summary	Summarized review content	String
cons	Disadvantages of working in the company	String
pros	Advantages of working in the company	String
advice_to_management	Advice to the management	String

See a snippet of the dataset for reference:

Review summary

"summary": "Vey stressed",
"cons": "Middling pay for very experienced",
"pros": "Culture, management cares about employees",
"cons": "Middling pay for very experienced",
"advice_to_management": "Maybe add a float manager that can help new managers learn and get caught up so you don\u2019t feel like you are sinking under paperwork while you are learning.",

Ratings

General ratings

Data point	Description	Data type
recommend	Main rating categories the user can mark in their review	Object
rating_ceo	CEO rating (approve/disapprove)	String
rating_business_outlook	Business outlook rating (positive/negative)	String
rating_recommend_to_friend	Indicates if the reviewer would recommend the company as a workplace to a friend	String

See a snippet of the dataset for reference:

Approval of the company

"recommend": {
	"rating_ceo": "NO_OPINION",
	"rating_business_outlook": "NEUTRAL",
	"rating_recommend_to_friend": "POSITIVE"
},

Star ratings

Data point	Description	Data type
star_rating	Various ratings on different aspects provided by Glassdoor (ranging from one to five stars)	Object
overall	Overall rating of the company	Integer/float
culture_values	Rating for the company's culture and values	Integer/float
career_opportunities	Rating for the career opportunities in the company	Integer/float
compensation_benefits	Rating for the compensation and benefits in the company	Integer/float
senior_management	Rating for the company's senior management	Integer/float
work_life_balance	Rating for the work-life balance in the company	Integer/float
diversity_inclusion	Rating for diversity inclusion in the company	Integer/float

See a snippet of the dataset for reference:

Star ratings

"star_rating": {
        "overall": 5,
        "culture_values": 5,
        "career_opportunities": 5,
        "compensation_benefits": 4,
        "senior_management": 4,
        "work_life_balance": 2,
        "diversity_inclusion": 5
      },