A recent report published in Molecula showed many AI and ML projects fail because of data pipeline problems. The report further revealed that 84% of businesses have a major problem with non-optimized data warehouses, high storage costs of data because of too much data, outdated IT infrastructure and finally manual or slow processes that do not meet business needs. Another research by Gartner showed that 53% of AI projects make it from prototype to production.
According to Andy Thurai, VP and principal analyst at Constellation Research Inc., data operations are still a big concern with enterprises. Several challenges including missing information, inconsistent information and biases in datasets are hindering AI and ML projects from reaching the acme of their capabilities. This is where robotic data automation (RDA) comes in.
RDA is a set of robotic processes used for solving data pipeline issues, simplifying all data handling processes required for the success of AI and ML projects. RDA automates the manual, cumbersome and expensive data pipeline process with bots.
According to Cloudfabrix, a California-based software company, it’s built the world’s first robotic data automation fabric (RDAF) technology to unify observability, AIops and automation — turning noisy IT data into action and prediction. Cloudfabrix’s RDAF technology offers a multi-tenant environment to design, explore, test, experiment, collaborate, reiterate, observe and deploy pipelines in production. With $17 million raised in total funding to date, Cloudfabrix claims its RDAF technology helps organizations move beyond traditional monitoring into observability pipelines and AIops.