Establish the foundations for lasting, trust-based data governance., whereby I agree to provide Gartner with my personal information, and understand that information will be transferred outside of mainland China and processed by Gartner group companies and other legitimate processing parties and to be contacted by Gartner group companies via internet, mobile/telephone and email, for the purposes of sales, marketing and research.
This approach rarely — if ever — leads to success, because a common stakeholder response emerges, often within a few months: While everyone agrees that data is important, business roles lose interest in the work because the scope of D&A governance is not put in the broader context of business goals. Build a culture of trust to help your organization navigate the complex challenges surrounding data, analytics and AI. This includes rightsizing governance, managing enterprisewide risk and addressing human behavioral change. For this all-important human element, address these three interconnected themes when making business decisions:The inherent risks that come with the development and use of D&A and AI require foresight and planning.
Beyond fragmented scopes, D&A teams and related stakeholders often don’t consider two critical dimensions of data governance: which D&A artifacts to govern and which types of policies to apply. In addition, some organizations develop programs and write policies for each information asset — one policy at a time — only to end up with monolithic programs that have little chance of working together.
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