'Moving from Manual to Automated Data Discovery' -Why it Matters to Organisations Today.

摘要

Many large organisations are still trying to discover data manually, using solutions that are either completely manual, or hybrids of manual and partially-automated tools. With data growth exponential, and regulatory pressures ramping up, this approach is no longer sustainable. As Daniel Patrick Moynihan, former member of the United States Senate, put it: "Everyone is entitled to his own opinion, but not his own facts." Most organisations today have an opinion about what their data environment looks like, but without an automated solution that goes out and brings back the full metadata picture, they are not really dealing with the facts. This article looks at the challenges that businesses face in moving from a manual to an automated approach to data discovery, the steps they need to take along the way, and the benefits they can achieve once they have completed the journey. Data discovery is rising up the corporate agenda. As data becomes more important to enterprises, so too does the data discovery process which essentially involves the collection and analysis of data across the organisation to enable firms to understand their data, gain insights from it and then act on those insights.