Free monthly CSV files showing all newly incorporated, reinstated, and dissolved UK companies. Updated monthly with official Companies House data.

Provided by CorpSignals.com

Overview

This dataset provides a comprehensive view of UK companies, including their registration details, financial information, ownership, management, and recent filings for up to the 31st December 2023. The data has been meticulously processed using dbt (Data Build Tool) scripts to ensure accuracy and relevance.

Play with this dataset at the BI app. (Free registration is required)

Application

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Contents

The dataset comprises the following tables:

1. companies
2. companies_sic_codes
3. filings
4. officers_and_owners

Below is a detailed description of each table.

1. companies

Description: Contains detailed information about companies registered in the UK up to January 1, 2024.

Columns:

• company_number: Unique identifier for each company.
• company_type: Type of company (e.g., private limited, public limited).
• office_address: Registered office address.
• incorporation_date: Date of company incorporation.
• jurisdiction: Legal jurisdiction of the company.
• company_status: Current status (e.g., active, dissolved).
• account_type: Type of accounts filed.
• company_name: Official name of the company.
• sic_codes: Standard Industrial Classification codes.
• date_of_cessation: Date when the company ceased operations (if applicable).
• next_accounts_overdue: Indicator if the next accounts are overdue.
• confirmation_statement_overdue: Indicator if the confirmation statement is overdue.
• owners: Number of registered owners (persons with significant control).
• officers: Number of officers (directors, secretaries) associated with the company.
• average_number_employees_during_period: Average number of employees during the last accounting period.
• current_assets: Current assets as per the last accounts.
• last_accounts_period_end: End date of the last accounting period.
• company_url: Where you can check the up-to-date company information. Free registration is required.

Data Generation Process:

• Aggregated counts of owners and officers from the ch_psc and ch_officers tables.
• Joined with the ch_accounts table to include financial information.
• Filtered to include companies incorporated on or before January 1, 2024.

2. companies_sic_codes

Description: Provides detailed SIC (Standard Industrial Classification) codes for each company.

Columns:

• company_number: Company identifier.
• sic_code: SIC code assigned to the company.
• sic_description: Description of the SIC code.
• sic_section: Section of the SIC code.
• sic_division: Division of the SIC code.
• company_url: Where you can check the up-to-date company information. Free registration is required.

Data Generation Process:

• Joined ch_companies_sic_codes with the sic_codes table to enrich SIC code information.

3. filings

Description: Lists up to the five most recent filings for each company as of January 1, 2024.

Columns:

• All relevant filing information excluding transaction_id.
• company_number: Company identifier.
• date: Date of the filing.

Data Generation Process:

• Selected the latest filings from the ch_filings table.
• Applied a window function to rank filings by date for each company.
• Limited to the top five filings per company.

4. officers_and_owners

Description: Details up to five most recent officers and owners for each company, including their roles and personal information.

Columns:

• company_number: Company identifier.
• name: Full name of the officer or owner.
• kind: Type of person (individual or corporate entity).
• officer_role: Role within the company.
• occupation: Occupation of the individual.
• date: Date of appointment or notification.
• is_owner: Boolean indicating if the person is an owner.
• country_of_residence: Country where the individual resides.
• nationality: Nationality of the individual.
• company_country: Country of the company (for corporate persons).
• person_id: Unique identifier for the person.
• person_url: Where you can check the up-to-date company information. Free registration is required.

Data Generation Process:

• Combined data from ch_officers and ch_psc tables.
• Applied filters to include active officers and owners as of January 1, 2024.
• Used a window function to limit to the top five entries per company.

Segments Included:

• Companies
• Owners and Officers
• Filings

Data Generation Process:

• Aggregated counts and latest record dates from respective tables.

Data Sources

• Companies House Data: Official UK government register of UK companies.
• SIC Codes: Standard classification codes for industries.

Data Processing Details

• **Time F...

Weekly data showing the number of Companies House incorporations, voluntary dissolutions accepted, and companies placed into compulsory dissolution in the UK. These are official statistics in development. Source: Companies House.

Dataset

This dataset was created by S Nath

Released under CC0: Public Domain

Contents

The 20,000+ registered companies with a registered address in Glasgow. The information is extracted from Companies House. It includes the company name, number, category (private limited, partnership), registered address, postcode, industry (SIC code), status (ex: active or liquidation), incorporation date... It is likely that some companies may just lie off Glasgow City Council's boundary. If you find a problem in the data, you can check the source either in the full UK list or by looking up a company or let us know. The data dictionary supplied by Companies House can be viewed here. There is also a data dictionary with field names and meanings contained in the resources. This dataset does not imply: - a partnership with Companies House - an endorsement by Companies House - a product approval by Companies House Licence: None glasgow-post-codes-py.txt - https://dataservices.open.glasgow.gov.uk/Download/Organisation/cc57ac4b-12d5-43b1-ad25-434638eec18c/Dataset/3093e34f-6dcb-4980-840b-965421c1b091/File/c2634107-bd43-4537-adb8-9046aeed844e/Version/c8fde78e-5396-4293-ac35-6f6c96a5d642

Context:

The People with significant control (PSC) snapshot is a data snapshot containing the full list of PSC's provided to Companies House. The Prime Minister first put corporate transparency on the international agenda when he chaired the G8 summit in Lough Erne and secured commitment to action, the commitment to enhance corporate transparency in the UK was reaffirmed at London’s International Anti-Corruption Summit in May 2016. Since then the EU and G20 countries have also agreed to act. The UK is the first country in the G20 to create a public register of this kind.

The UK has high standards of business behaviour and corporate governance. The overwhelming majority of UK companies contribute productively to the UK economy, abide by the law and make a valuable contribution to society. But there are exceptions. Some of the features of the company structure which make it good for business also make it attractive to criminals. Companies can be misused to facilitate a range of criminal activities - from money laundering to tax evasion, corruption to terrorist financing. Sometimes those individuals running companies will not conduct themselves in accordance with the high standards we expect in the UK, posing a risk to other companies and consumers alike.

Information about the ownership and control of UK corporate entities will bring benefits for law enforcement, business, civil society and citizens. By making this information publicly available, free of charge, the government is setting a standard that we are persuading other countries to follow.

Content:

A person of significant control is someone that holds more than 25% of shares or voting rights in a company, has the right to appoint or remove the majority of the board of directors or otherwise exercises significant influence or control. This is a snapshot of data in zipped JSON form, as of Aug 23 2017. Daily updated snapshots and streaming API details can be found here. The People with Significant Control (PSC) register includes information about the individuals who own or control companies including their name, month and year of birth, nationality, and details of their interest in the company. From 30 June 2016, UK companies (except listed companies) and limited liability partnerships (LLPs) need to declare this information when issuing their annual confirmation statement to Companies House.

Acknowledgements:

Guidance here. The data is collected by UK government.

Inspiration:

• Who owns the most businesses? In certain areas?
• Any weird looking situations where ownership might be obscured?

The Free Company Data Product is a downloadable data snapshot containing basic company data of live companies on the register.

The latest snapshot will be updated within 5 working days of the previous month end.

Gender Pay Gap legislation introduced in April 2017 requires all employers of 250 or more employees to publish their gender pay gap each year. The gender pay gap is the difference between the average earnings of men and women, expressed relative to men’s earnings.

You can also:

• https://gender-pay-gap.service.gov.uk/Viewing/search-results?t=1&search=&orderBy=relevance" class="govuk-link">explore this data on a dashboard
• https://data.gov.uk/dataset/54219db1-dd98-49d9-a383-a5978bb0aeb9/gender-pay-gap" class="govuk-link">export all national gender pay gap data

I work with UK company information on a daily basis, and I thought it would be useful to publish a list of all active companies, in a way that could be used for machine learning.

There are 3,838,469 rows in the dataset, one for each active company. Each row, has the company name, date of incorporation and the Standard Industrial Classification Code.

The company list is from the publicly available 1st November 2017 Companies House snapshot.

The SIC code descriptions are from the gov.uk website.

In the file AllCompanies.csv each row is formatted as follows:

• CompanyName - Alpha numberic company name
• IncorporationDate - in British date format, dd/mm/yyyy
• SIC - 5 digits or if not known, None - see separate file for description of each code.

Inspiration

Possible uses for this data is to use ML to suggest a new unique but suitable name for a company based on what other companies of the same SIC are called.

Perhaps analyse how company names have evolved over time.

Using ML, perhaps determine what a typical company name looks like, maybe analyse if company names have got longer or more complicated over time.

I am sure there are many more possible uses for this data in ways, that I cannot imagine.

This is my second go (the first was published a few hours ago) at publishing a dataset on any medium, so any useful tips and hints would be extremely welcome.

Links to the raw data sources are here:

• Companies House http://download.companieshouse.gov.uk/en_output.html
• SIC Codes https://www.gov.uk/government/publications/standard-industrial-classification-of-economic-activities-sic

Individuals which have been disqualified from holding the post of a company director in the United Kingdom following a court decision.

A monthly updated list of all financial transactions made by Companies House, as part of the Government`s commitment to transparency in expenditure

Normalised UK company accounts derived from Companies House filings, including balance sheet fields and computed ratios. Optimised for benchmarking, enrichment and APIs.

All statutory company information captured by Companies House. Includes basic company data (company name, registered office address, company status, incorporation date, country of origin, company type, nature of business, accounting reference date, date of last accounts/annual return filed, date of next accounts/annual return due, previous names, share allocation) and all statutory filings by companies contained in the Register.