Data Quality Can Make Or Break Efforts To Bring Artificial Intelligence To It Operations
However, there’s a problem: AIOps requires the right kind of data at the right time, but much of this data either isn’t ready or needs a quality overhaul. While AIOps functions on data points such as system logs and metrics, historical performance, event data, streaming real-time operations events, incident-related data, and ticketing, much of this data may be incomplete or hidden away in silos. In short, if data isn’t up to par, AIOps may flop, or worse yet, steer technology decisions in the wrong direction....