Creating policies for data handling and accountability and driving culture change so people understand how to properly work with data are two important components of a data governance initiative, as is the technology for proactively managing data assets. Without the ability to harvest metadata schemas and business terms; analyze data attributes and connections; impose structure on definitions; and view all data in one place according to each user’s role within the enterprise, businesses will be hard pressed to stay in step with governance standards and best practices around security and privacy.
As a consequence, the private information held within organizations will continue to be at risk. Organizations suffering data breaches will be deprived of the benefits they had hoped to realize from the money spent on security technologies and the time invested in developing data privacy classifications. They also may face heavy fines and other financial consequences.
An assessment of the data breaches that crop up like weeds each year supports the conclusion that companies, absent data governance, wind up building security architectures strictly from a technical perspective. They don’t gain visibility into the full data landscape – linkages, processes, people and so on – to propel more context-sensitive security architectures that can better assure expectations around user and corporate data privacy will be realized.
Find out how to connect the dots across the data trinity – governance, security and privacy.