According to McKinsey, over the past decade, advanced analytics has become a top priority across industries: 90 percent of companies recognize its value, and many have started to put internal analytics organizations in place, with an eye toward scaling use cases. Yet the majority of companies have not unlocked the full potential of advanced analytics. This is because they lack the visibility, capabilities and repeatable processes needed to deliver data to feed these new algorithms and analytics models.
DataOps is an automated, process-oriented methodology used by analytics and data teams to improve quality and reduce the cycle time of advanced analytics. In this session, you’ll learn how the Quest approach to data empowerment helps our customers underpin and assure their DataOps practice. Through a critical combination of metadata management, data governance and preparation, you can increase business and technical stakeholder data literacy, automate delivery of on-demand data insight to speed analysis of data fitness and reduce cycle time in preparing, maintaining and deploying high-quality data pipelines. You’ll see how a flexible governance framework ensures the right people have the right data, for the right use, at the right time.