Revenue monitoring not only involves monitoring huge amounts of data in real-time but also finding correlations between thousands, if not millions, of customer experience and other metrics. Are traditional monitoring methods capable of detecting a correlation between a drop in user log-ins and a drop in revenue as it’s happening? For many reasons, the answer is no.

The Oil and Gas industry is arguably more familiar with managing an array of changing risk factors than almost any other sector in the United States. The industry is used to facing strong headwinds and has proven itself adept at adjusting to often rapidly shifting business conditions, whether that is regulatory change, big fluctuations in supply and demand, or evolving security supply chain concerns.

One of the big standouts for me in the recent environment is just how much of a shock COVID-19 has been for organizations. This is because many have become complacent about their data over the past decade and they’re now exposed. As Warren Buffet said, "Only when the tide goes out do you discover who's been swimming naked." To deal with the current economic situation everyone now has to lift the lid on their organization.

Since the very beginning, Unravel Data has made it a mission to ensure customers are successful, wherever they deploy their modern data platforms. On-premises, in the cloud, and in hybrid environments, Unravel supports the full stack of data processing engines to provide data operations visibility wherever it resides.

From dealing with security concerns to production monitoring, businesses need to analyze the log data of their systems to ensure everything is functioning normally. In a computing context, a log refers to automatically produced and time-stamped documentation of events related to a particular system. Analysis of log data helps businesses comply with regulations, security policies and audits, understand online consumer behavior, and comprehend system troubleshoots.