Dropbase is a collaborative data import and data management platform. Dropbase helps companies import, validate, and manage all their data from CSV and Excel files inside cloud databases optimized to handle large amounts of data, with no technical help required. We’ll use the funding to expand our data platform capabilities and continue closing the gap between spreadsheets and analytical databases.
While most of the modern data integration tools focus on extracting data from internal - and typically - online sources such as databases and APIs, there’s a growing demand for tools that can help integrate data from external sources such as data from partners, suppliers, or customers.
Oftentimes, external data sources don’t have API’s to easily connect to, yet this data is required to fully understand the business and run operations. To complicate matters, external data is usually messy, with a mix of data types, encodings, data placement, and a mismatch with how the destination system or database expects the data to be structured and formatted. Even if data could be shared through APIs, the data still needs to be mapped and validated.
Most of the time, integrating external data means that the data sender manually extracts data from a source system and exports it as a CSV file, uploads it to a cloud drive, SFTP, or as an email attachment, and sends it over to the data receiver. The receiver then has to download, clean, map, and then re-upload, usually to a database which has its own set of requirements and constraints. This entire process is quite inefficient, especially when the data sender extracts data with the same schema on a regular basis to send it out to the data receiver.
One of our main goals at Dropbase is to significantly improve this process, automate it, and make it easier for companies to collect external data, and combine it with internal data to make better data-driven decisions and improve business operations for customers such as award-winning baby stroller manufacturer, Mockingbird.
Dropbase helps us automatically process complex and unformatted external data from our manufacturers, resulting in streamlined operations and helping us continue to sustainably deliver delightful experiences for Mockingbird customers -- Ross Berger, VP Operations at Mockingbird.
We believe that data analysts and operation managers should be able to just open up their favorite data tools and all the data they’ve received from their external partners should already be there, cleaned and ready to use. Data teams should never have to clean the same CSV file or data extract twice.
What makes Dropbase's technology better is that we provide an actual database and we allow semantic validation checks.
Database
At the core of of Dropbase is a database - a fully featured, SQL database optimized for data scale and performance. This provides many advantages
Semantic Validations
Data validation checks helps detect data that does not match requirements by your system so you can fix them and import them to the database. One of the differentiating aspects of our Checks implementation is that we not only allow syntactic checks but also semantic checks. What does this mean?
Syntactic checks are checks that look for data that is formatted in a specific way. For example, zip codes that conform to a certain pattern such as 5 digits for US zip codes, or alternating letters and numbers for Canadian postal codes. Semantic checks, however, go beyond formatting checks. They help validate that dates in your data can only be after a specific date. Or that a number falls within a range. We are the only product in this category that allows this kind of validation.
WIth this announcement, we are also releasing to general availability 3 features:
This funding helps the company lay the foundation of Dropbase as a data platform that will enable growing companies to automate data imports, data validation, and data sharing. While we are currently focused on helping data teams import data into databases, we have plans to expand the product into an end-to-end platform for data imports, data management, and data exchanges for both internal and external use cases. We’re building a new operating system for enterprise data - an end-to-end platform for data import, data sharing, and data management.
