Qlik has recently made a major development regarding its governance and trust capabilities. They have introduced data products as the key component of trust for contemporary businesses. Now, companies will be able to better control the datasets used to train their AI algorithms and even human analysts. This change comes as a response to increasing demands for transparency as AI becomes responsible for making decisions on its own.
Prior to Qlik, companies faced problems of “weak data,” which resulted in poor outcomes from AI processes. Qlik addresses this issue by implementing controls such as trust signals and anomaly detection. In addition, a “Data Product Agent” enables organizations to produce and distribute these resources through natural language processing. This allows every piece of data to stay accountable for production purposes.
“As AI moves from answers into decisions and actions, weak data stops being a reporting problem and becomes an execution problem,” said Mike Capone, CEO, Qlik. “Data products need the same accountability as any other production asset, with clear signals for what humans and AI can safely rely on. That is how enterprises scale AI without scaling risk.”
Strengthening Data Accountability with Trust Scores and Contracts
Moreover, each asset comes with an explicit Trust Score. It assesses accuracy and timeliness to assist users in making decisions. Thus, stewards will be able to pinpoint and address problems with quality within conversations. Taken together, these capabilities help span the divide between technical data engineering and tangible business benefits. In addition, the launch includes data contracts. They establish standards for the level of service and allow setting clear expectations for data providers and users. In the end, Qlik enables organizations to accelerate innovation while keeping tight control of governance boundaries. As a result, AI becomes a safe and scalable resource for the entire labor force worldwide.
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Source: Businesswire
