Cintra | UK Payroll Data | 40+ Years Historical Data and over 500K Individuals | CIPP Qualified | Salary Benchmarking & Payment History Analytics
# | Location |
Industry |
Job Title |
Employment Start Date |
Salary_2024 |
Salary_2023 |
Salary_2022 |
Salary_2021 |
Salary_2020 |
Salary_2019 |
Salary_2018 |
Salary_2017 |
Salary_2016 |
Salary_2015 |
Salary_2014 |
Salary_2013 |
Salary_2012 |
Salary_2011 |
Salary_2010 |
Salary_2009 |
Salary_2008 |
Salary_2007 |
Salary_2006 |
Salary_2005 |
Salary_2004 |
Salary_2003 |
Salary_2002 |
Salary_2001 |
Salary_2000 |
Salary_1999 |
Salary_1998 |
Salary_1997 |
Salary_1996 |
Salary_1995 |
Salary_1994 |
Salary_1993 |
Salary_1992 |
Salary_1991 |
Salary_1990 |
Bonus_2024 |
Bonus_2023 |
Bonus_2022 |
Bonus_2021 |
Bonus_2020 |
Bonus_2019 |
Bonus_2018 |
Bonus_2017 |
Bonus_2016 |
Bonus_2015 |
Bonus_2014 |
Bonus_2013 |
Bonus_2012 |
Bonus_2011 |
Bonus_2010 |
Bonus_2009 |
Bonus_2008 |
Bonus_2007 |
Bonus_2006 |
Bonus_2005 |
Bonus_2004 |
Bonus_2003 |
Bonus_2002 |
Bonus_2001 |
Bonus_2000 |
Bonus_1999 |
Bonus_1998 |
Bonus_1997 |
Bonus_1996 |
Bonus_1995 |
Bonus_1994 |
Bonus_1993 |
Bonus_1992 |
Bonus_1991 |
Bonus_1990 |
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5 | Xxxxxxx | Xxxxxxx | Xxxxxxx | Xxxxxxx | xxxxxxx | Xxxxxxxxxx | xxxxxxxx | Xxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxx | xxxxxxxx | Xxxxxxxx | xxxxxx | xxxxxxxx | xxxxxx | Xxxxxxxx | xxxxxxxxx | xxxxx | Xxxxxxxxxx | Xxxxxxxxx | Xxxxxxx | xxxxxxxx | Xxxxxxx | Xxxxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | xxxxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxxxx | xxxxxxxxx | xxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxxx | xxxxxxx | Xxxxxxxxxx | Xxxxxxxxx | Xxxxxx | xxxxxxxx | xxxxxxxxxx | xxxxxxxx | Xxxxx | xxxxxxxx | xxxxxxxxxx | xxxxxxxx | Xxxxx | xxxxxxxx | xxxxxx | Xxxxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxx | Xxxxx | Xxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxx | xxxxx | Xxxxx | Xxxxxxxxxx | Xxxxxxx | Xxxxxxxxxx | Xxxxxxxx | xxxxxxx | xxxxxxxx | Xxxxxx |
6 | Xxxxxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxxxxxxx | xxxxx | xxxxxxx | xxxxxxxxx | xxxxxxxxx | xxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxx | Xxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxxx | xxxxx | xxxxx | Xxxxxxxxx | xxxxx | Xxxxx | Xxxxxx | xxxxxxxxxx | Xxxxxxxx | Xxxxxxxx | Xxxxxxxxx | Xxxxxxxxxx | xxxxxx | Xxxxx | Xxxxxxxx | xxxxxx | Xxxxx | Xxxxxx | xxxxxx | xxxxxxxx | Xxxxxxxx | Xxxxxxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxx | xxxxxxxx | Xxxxxxxxx | Xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxxxxx | xxxxxx | xxxxxxxxxx | xxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxx | Xxxxxxxxxx | xxxxx | Xxxxxxxxx | Xxxxxxx | Xxxxxxxxx | Xxxxx |
7 | Xxxxxxxx | xxxxxxxxx | xxxxxxxxxx | xxxxx | xxxxxxxxxx | xxxxxxx | xxxxxxxx | Xxxxx | xxxxx | xxxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxxxx | Xxxxxxxxx | xxxxxxx | Xxxxxxx | Xxxxxxxxxx | Xxxxxxxx | xxxxxx | xxxxxx | Xxxxxx | xxxxxx | xxxxx | Xxxxxxxxx | Xxxxxxxxx | Xxxxxx | Xxxxx | Xxxxxxxxx | Xxxxxx | Xxxxxx | xxxxxx | xxxxx | xxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxx | xxxxxxx | xxxxxxx | Xxxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxxxx | Xxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxxx | xxxxx | xxxxxx | xxxxxx | Xxxxxxxx | xxxxxxx | Xxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxx | Xxxxxx | xxxxxx | Xxxxxxxx | Xxxxx | xxxxx | Xxxxxxxxxx | xxxxxx | xxxxx | xxxxxxx | xxxxx |
8 | Xxxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxxx | xxxxxxx | xxxxxxxxxx | Xxxxxxxxxx | Xxxxxx | xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxx | Xxxxxxx | Xxxxxx | xxxxxxxx | xxxxx | Xxxxxxxxxx | Xxxxx | xxxxxxx | xxxxxxxx | xxxxxxxx | Xxxxxxxx | xxxxxxx | xxxxxx | Xxxxxxxx | xxxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxxxxx | xxxxxx | Xxxxxxxx | xxxxx | Xxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxxx | Xxxxx | Xxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | Xxxxxx | xxxxxxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | xxxxxxxx | xxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | Xxxxxxxxx | xxxxxxxx | xxxxxxx | xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxxxxx | xxxxxxxxx | Xxxxx | xxxxx | xxxxxxx |
9 | xxxxxxxx | xxxxxx | xxxxxxx | Xxxxx | Xxxxxxxxx | Xxxxxxx | Xxxxxxx | Xxxxxxxx | xxxxxxx | xxxxxxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxx | xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxxxxx | xxxxxxxxx | xxxxxxxxx | Xxxxxx | Xxxxxxx | Xxxxxxxx | xxxxxxx | xxxxxxx | Xxxxxxxx | xxxxxxx | Xxxxxxx | Xxxxxxx | Xxxxxxxxx | Xxxxx | xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxx | Xxxxxx | xxxxxxxx | Xxxxxxxx | Xxxxxxxxxx | Xxxxxxxx | Xxxxxx | xxxxxxxxx | xxxxx | xxxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxx | xxxxxxxxx | Xxxxxxxx | Xxxxxxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxxxx | Xxxxxxxxx | Xxxxxxxx | Xxxxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxxxx | xxxxxxx | Xxxxxx | Xxxxxx | xxxxxxx | Xxxxxxx | Xxxxx | Xxxxxxxxxx | Xxxxxxxxxx | Xxxxxxxx |
10 | Xxxxxxx | Xxxxxxxxx | xxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxx | Xxxxxxx | xxxxxxxx | Xxxxxx | xxxxxxx | xxxxxxxxx | xxxxxxxxxx | xxxxxxx | xxxxxxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxxxxx | Xxxxxx | Xxxxx | Xxxxxxxxx | Xxxxxxxxx | xxxxx | xxxxxxxxxx | xxxxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxx | Xxxxxx | xxxxxxxx | xxxxxx | xxxxxxx | Xxxxxxxxxx | Xxxxxxxxx | xxxxxxxx | Xxxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxxx | Xxxxxxxxxx | Xxxxxxx | xxxxxx | xxxxxxxxx | xxxxxxx | xxxxxx | Xxxxxx | xxxxxxxx | xxxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxx | xxxxxxx | xxxxxxxxx | xxxxxx | Xxxxx | Xxxxxx | Xxxxxxxxxx | xxxxx | xxxxxxxx | xxxxxxxx | Xxxxx | xxxxxxx | xxxxxxx | xxxxxxx | xxxxxxxxxx | xxxxx | Xxxxxxx | xxxxx | Xxxxxxxxx | xxxxx | Xxxxxxx | xxxxxxxx |
... | Xxxxx | Xxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxxx | xxxxxxx | xxxxx | Xxxxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxx | xxxxx | xxxxxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxx | xxxxxxx | Xxxxxxxx | xxxxx | Xxxxxxxx | xxxxxx | xxxxxxxxxx | xxxxx | xxxxxx | xxxxxx | Xxxxx | Xxxxxx | xxxxxxxxx | Xxxxxxxxx | Xxxxxx | xxxxxxxx | xxxxxxxx | xxxxxxx | xxxxxxxxx | Xxxxxxxx | Xxxxxxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxx | xxxxxx | Xxxxx | xxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxx | xxxxx | xxxxxx | xxxxxx | xxxxxxx | Xxxxxx | xxxxxx | Xxxxxxxx | Xxxxxxx | xxxxxxx | Xxxxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | Xxxxxxxxx | Xxxxxxxxxx | Xxxxxxxxxx | xxxxx | Xxxxxx | Xxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxxxx | xxxxxxxxx | Xxxxxxxx | Xxxxxxxx |
Data Dictionary
Attribute | Type | Example | Mapping |
---|---|---|---|
Location
|
String | SE1 | |
Industry
|
String | Legal | |
Job Title
|
String | Accountant | |
Employment Start Date
|
DateTime | 2007-10-02T00:00:00+00:00 | |
Salary_2024
|
Integer | 95285 | |
Salary_2023
|
Integer | 116304 | |
Salary_2022
|
Integer | 48432 | |
Salary_2021
|
Integer | 103476 | |
Salary_2020
|
Float | 46308.0 | |
Salary_2019
|
Float | 72262.0 | |
Salary_2018
|
Float | 116803.0 | |
Salary_2017
|
Float | 34221.0 | |
Salary_2016
|
Float | 38372.0 | |
Salary_2015
|
Float | 36465.0 | |
Salary_2014
|
Float | 83075.0 | |
Salary_2013
|
Float | 57563.0 | |
Salary_2012
|
Float | 70058.0 | |
Salary_2011
|
Float | 66084.0 | |
Salary_2010
|
Float | 56768.0 | |
Salary_2009
|
Float | 48122.0 | |
Salary_2008
|
Float | 67350.0 | |
Salary_2007
|
Float | 63175.0 | |
Salary_2006
|
|||
Salary_2005
|
|||
Salary_2004
|
|||
Salary_2003
|
|||
Salary_2002
|
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Salary_2001
|
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Salary_2000
|
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Salary_1999
|
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Salary_1998
|
|||
Salary_1997
|
|||
Salary_1996
|
|||
Salary_1995
|
|||
Salary_1994
|
|||
Salary_1993
|
|||
Salary_1992
|
|||
Salary_1991
|
|||
Salary_1990
|
|||
Bonus_2024
|
Float | 8902.0 | |
Bonus_2023
|
Float | 10224.0 | |
Bonus_2022
|
|||
Bonus_2021
|
Float | 9144.0 | |
Bonus_2020
|
Float | 8748.0 | |
Bonus_2019
|
|||
Bonus_2018
|
|||
Bonus_2017
|
|||
Bonus_2016
|
|||
Bonus_2015
|
|||
Bonus_2014
|
|||
Bonus_2013
|
|||
Bonus_2012
|
|||
Bonus_2011
|
|||
Bonus_2010
|
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Bonus_2009
|
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Bonus_2008
|
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Bonus_2007
|
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Bonus_2006
|
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Bonus_2005
|
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Bonus_2004
|
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Bonus_2003
|
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Bonus_2002
|
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Bonus_2001
|
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Bonus_2000
|
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Bonus_1999
|
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Bonus_1998
|
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Bonus_1997
|
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Bonus_1996
|
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Bonus_1995
|
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Bonus_1994
|
|||
Bonus_1993
|
|||
Bonus_1992
|
|||
Bonus_1991
|
|||
Bonus_1990
|
Attribute | Type | Example | Mapping |
---|---|---|---|
String | Address | ||
String | eg. Education | Company Industry | |
Float | eg. £25,000 | Job Compensation | |
Float | eg. £5,000 | Job Compensation | |
String | eg. Cleaner | Job Title |
Description
Country Coverage
Volume
40 | Years Industry Experience |
2 million | Live Employee Records |
5 million | Historical Employee Records |
Pricing
Suitable Company Sizes
Quality
Delivery
Use Cases
Categories
Related Searches
Related Products
Frequently asked questions
What is Cintra UK Payroll Data 40+ Years Historical Data and over 500K Individuals CIPP Qualified Salary Benchmarking & Payment History Analytics?
Want to understand what has happened to salaries in various industries over time? Want to make sure that you are paying people fairly and have given them the right amount of pay rises (and not too much)? Then Cintra’s payroll dataset is for you.
What is Cintra UK Payroll Data 40+ Years Historical Data and over 500K Individuals CIPP Qualified Salary Benchmarking & Payment History Analytics used for?
This product has 4 key use cases. Cintra recommends using the data for Payment History Analytics, Salary Benchmarking, Employee Pay Strategy, and Cost Forecasting. Global businesses and organizations buy Company Data from Cintra to fuel their analytics and enrichment.
Who can use Cintra UK Payroll Data 40+ Years Historical Data and over 500K Individuals CIPP Qualified Salary Benchmarking & Payment History Analytics?
This product is best suited if you’re a Small Business, Medium-sized Business, or Enterprise looking for Company Data. Get in touch with Cintra to see what their data can do for your business and find out which integrations they provide.
Which countries does Cintra UK Payroll Data 40+ Years Historical Data and over 500K Individuals CIPP Qualified Salary Benchmarking & Payment History Analytics cover?
This product includes data covering 1 country like United Kingdom. Cintra is headquartered in United Kingdom.
How much does Cintra UK Payroll Data 40+ Years Historical Data and over 500K Individuals CIPP Qualified Salary Benchmarking & Payment History Analytics cost?
Pricing information for Cintra UK Payroll Data 40+ Years Historical Data and over 500K Individuals CIPP Qualified Salary Benchmarking & Payment History Analytics is available by getting in contact with Cintra. Connect with Cintra to get a quote and arrange custom pricing models based on your data requirements.
How can I get Cintra UK Payroll Data 40+ Years Historical Data and over 500K Individuals CIPP Qualified Salary Benchmarking & Payment History Analytics?
Businesses can buy Company Data from Cintra and get the data via SFTP and Email. Depending on your data requirements and subscription budget, Cintra can deliver this product in .csv and .xls format.
What is the data quality of Cintra UK Payroll Data 40+ Years Historical Data and over 500K Individuals CIPP Qualified Salary Benchmarking & Payment History Analytics?
Cintra has reported that this product has the following quality and accuracy assurances: 10% Salary Cost Reducation. You can compare and assess the data quality of Cintra using Datarade’s data marketplace.
What are similar products to Cintra UK Payroll Data 40+ Years Historical Data and over 500K Individuals CIPP Qualified Salary Benchmarking & Payment History Analytics?
This product has 3 related products. These alternatives include Canaria Salary Data US 25M+ Monthly Job Postings & 2 Year Historical AI-LLM Enhanced Salary Data, Envestnet Yodlee’s De-Identified Electronic Payment Research Panel USA Employee Payroll Data covering 4800+ employers Cohort Analysis, and Private Company Data & Firmographic Data: 2+ Years of Trustpilot & 3+ years of Glassdoor Data +1 Source for B2B Marketing Public Web Data. You can compare the best Company Data providers and products via Datarade’s data marketplace and get the right data for your use case.