Reduce time to value with clean data
- Spend less data engineering resources
- Leverage 20+ additional data points for more precise analysis
- Access 36M+ company and 682M+ employee clean data records
- Get flat files or use a highly scalable API
| Data Points | Example Values |
|---|---|
| company_name | Benur Mobility |
| company_location_hq_country | France |
| company_industry | Automotive |
| company_size_range | 501-1000 employees |
| company_description | “Making the best EVs in the world” |
| company_specialties | Outplacements & Trainings |
[
{
"company_hash": "g768f9sdafuh23f9gasdf",
"company_name": "Great Company Name",
"company_websites_main": "https://greatcompanysite.com",
"company_size_range": "1001-5000 employees",
"company_size_employees_count": "2354",
"company_industry": "Staffing and Recruiting",
"company_description": "Multinational staffing and recruiting company",
"company_location_hq_raw_address": "Sydney, New South Wales, Australia",
"company_location_hq_country": "Australia",
"company_last_updated": "2023-08-13",
"company_specialities": "Outplacements & Trainings",
"expired_domain": "0",
"unique_domain": "1",
"unique_website": "1",
"company_enriched_summary": "Great Company offers staffing, recruitment, and outsourcing services for businesses.",
"company_enriched_keywords": ["staffing","recruitment","outsourcing","talent","Augmented Humanity"],
"company_enriched_b2b": "true",
"metadata_title": "Staffing and Recruiting Services for Businesses",
}
}
]What is clean data?
Clean data refers to professional network data that was processed by removing outliers, unifying values, and eliminating irrelevant or low-value records. For example, stylistic code tags, present in raw data, are removed.
After cleaning, these datasets are also enriched with additional data. Our clean datasets are refined and enhanced versions of our raw datasets. It is the go-to solution for companies that have limited data engineering capabilities or want to reduce their time to value.
Ready-to-use clean datasets
Filtered, unified, and standardized clean datasets. Enriched by leveraging a carefully instructed large language model (LLM).
Company data
Our clean dataset consists of over 36 million high-value B2B company records. Duplicate and incomplete profiles are removed. All company information is checked and enriched with the help of AI to ensure you have all the necessary data at hand.
Employee data
Our clean dataset of employees consists of over 682 million up-to-date candidate profiles. Duplicate and incomplete profiles are removed. Employee data records are enriched with taxonomy-related data fields.
Time-saving features
Reduced dataset size
Our clean dataset size is around 4 times smaller compared to regular raw datasets.
Less data engineering needed
You can save a significant amount of data engineering resources with clean data.
Quicker data processing
Clean datasets are easier to ingest and process.
Shorter time to value
Onboarding with a new data vendor can take months. A simplified data structure makes it much easier to get started.
Enriched data fields
Thanks to AI-driven enrichment, you get 20+ additional data points and the existing ones are improved.
Convenient formats and delivery
Multiple data formats (JSON, JSONL, or CSV) and flexible delivery frequency (quarterly, monthly, or weekly).
Get clean data via API
One of the ways to get access to our clean datasets is by using a highly scalable API. Submit a trial request and test it for free!
AI-powered data enrichment
The data you’re getting is not only clean, but also supplemented with additional data not available in the raw version of our datasets. Clean dataset contains 20+ additional data fields. Some of these data fields are created or enriched with the help of LLM technology.
Coresignal’s raw vs. clean datasets
| Features | Raw data | Clean data |
|---|---|---|
| Structured/unsructured data | Structured data | Structured data |
| Filtering | Dataset contains all scraped profiles. | Dataset contains complete, high-value profiles. A significant portion of duplicates and incomplete profiles are filtered out. |
| Standardization of values | No | Data values like dates and location are standardized |
| Text field cleaning | No | Stylistic code tags and special characters are removed, multiple spaces are changed to single spaces, trailing special characters are trimmed/removed. |
| Data points | Dataset contains data points that are present in the source and metadata. | Dataset contains most of the data points that are present in the source, meta data, and additional data points. |
| Data enrichment | Data is not enriched | Data is enriched |
| Data formats | Available in JSON, JSONL, and CSV | Available in JSON, JSONL, CSV, and Parquet format |
Why 500+ companies choose Coresignal
Dedicated account managers
Get the most out of your clean dataset with the help of a dedicated account manager. We value long-term relationships and strive to provide quick support.
In the market since 2016
Our team includes some of the most experienced web data extraction professionals. The advanced infrastructure they built over the years allows us to expand our datasets daily.
Responsible data collection
We offer data in multiple formats, flexible delivery frequency and ensure transparent information about data operations to our clients.
Frequently asked questions
Clean data is a refined and enhanced version of our raw datasets. Currently, we offer two clean datasets: employee dataset and company dataset.
The key differences are:
For a more detailed comparison, refer to the section Coresignal’s raw vs. clean datasets above.
Quarterly, monthly, and weekly.
Companies that don't have the required resources or don't want to clean and process raw data themselves.