SourceScrub DataWarehouse

SourceScrub offers the opportunity to infuse our raw data directly into your internal systems so that you can mold our datapoints directly around your existing processes

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Unfiltered access to our Historical Dataset

Access our raw data tables that span across a multitude of organizational details including Investments, Investors, Ownership, Employee Counts, and many more. Derive insights from timestamped 'Created Dates' and 'Modified Dates' for all company records

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Refine your own Unique Queries

Our data tables may be inter-related via keys we defined between each of the tables. SourceScrub DataWarehouse customers can derive their own formulas and proprietary metrics across tables to develop endlessly unique insights and variations

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Access to Proprietary Datapoints

SourceScrub tracks metrics outside of those we publish onto the platform. Furthermore, we collect timestamps with each dynamic metric we track within our database, thus allowing you the ability to design alerts as soon as datapoints important to you are updated

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Implementation Guidance

With a team combining several years of experience across Data and Engineering teams, SourceScrub is well-equipped to advise your team and make sure our data files are ingested correctly so that you hit the ground running

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Consultation on Technical Challenges

Following implementation or our data tables into your SQL server or productionalization of the data into a proprietary offering, SourceScrub offers DataWarehouse customers guidance through data-ingestion or other technical difficulties that may arise

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Optional Access to New Dataset Metrics

From time to time, SourceScrub may add new proprietary metrics to the existing dataset. As a customer of SourceScrub DataWarehouse, you have the option to add these new metrics to your daily diff files

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Collaboration Opportunities

We work closely with the Data/Engineering/Product teams of those firms who subscribe to SourceScrub DataWarehouse. As such, we allow them the option to collaborate with us to build resources to obtain new data they identify as being potentially beneficial and add it to the dataset