How Investors Can Leverage Big Data and AI for Better ESG and Water Risk Analysis

Data Governance is both a technical and an organizational discipline, and getting Data Governance right requires a combination of Data Management fundamentals aligned with organizational change and stakeholder buy-in. Join Nigel Turner and Donna Burbank as they provide an architecture-based approach to aligning business motivation, organizational change, Metadata Management, Data Architecture and more in a concrete, practical way to achieve success in your organization.

It’s no secret that trust provides a competitive advantage, with trusted companies outperforming their market peers. Boards, executives, and businesses across the globe want to find ways to build trust with consumers, employees, investors, and all stakeholders. But how do you define metrics, quantify, and measure trust?

What began as a trickle is now the mainstream: Organizations are moving to the cloud for data management. No longer is the cloud just a cheaper place to park data; it is key to supporting business-critical innovation in advanced analytics, data science, and AI as well as for end-user business intelligence, data exploration, and data visualization. Data lakes and data warehouses running on market-leading platforms such as AWS are growing fast, just as they are on the platforms of competing providers. However, as cloud-based workloads grow in number and size, organizations are facing difficult data preparation challenges. The flow of data raw, diverse, and frequently unstructured can quickly turn cloud data lakes into impenetrable swamps. Without good data preparation technologies and practices, users of all types are frustrated; their productivity and satisfaction suffer because it’s too hard to get accurate data that’s appropriately transformed and structured for their purposes.

Navigating the course of data center management comes with a multitude of obstacles. Most IT professionals must balance maximizing uptime, improving security, optimizing operations and meeting budget realities. In the case of data center maintenance, what is the best route to take after initial warranty support expires? Uptime a