The most advanced ML Observability product in the market
Building an ML platform is nothing like putting together Ikea furniture; obviously, Ikea is way more difficult. However, they both, similarly, include many different parts that help create value when put together. As every organization sets out on a unique path to building its own machine learning platform, taking on the project of building a […]
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We’re excited 😁 to share that Forbes has named Aporia a Next Billion-Dollar Company. This recognition comes on the heels of our recent $25 million Series A funding and is a huge testament that Aporia’s mission and the need for trust in AI are more relevant than ever. We are very proud to be listed […]
Data integrity is assuring the accuracy and consistency of data over the lifetime of an asset. Any system that stores, processes, or retrieves data must consider this aspect when designing, implementing, and utilizing it. In some circumstances, data integrity is used as a proxy term for data quality. However, data validity is a prerequisite for data integrity.
Regardless of the data integrity technique used, its purpose is the same: make sure data is recorded as intended (such as a database rejecting mutually exclusive possibilities correctly). Furthermore, ensure the data is identical when retrieved later.
