Financial Analytics Fundamentals Use Data Science And Analytics In BFSI

Do you have data governance on your mind? Do you envision an environment where people are held formally accountable for the data they define, produce and use? Does metadata play a big role in that governed environment? Of course, it does. To manage any “thing” requires that you have quality information about that thing. Join Bob Seiner, of KIK Consulting and TDAN.com, with Gal Alon, Senior Director of Business Development for an industry leading metadata management automation software provider Octopai, as they discuss the who’s, what’s, why’s and how’s of automating and leveraging your metadata environment to successfully govern your organization’s data. Bob and Gal will spend the hour chatting about the role metadata management plays in data governance as well as discuss specific use cases to improve probability of Data Governance success.

As reported in Forbes last year, 73% of companies are planning to move to a fully software-defined data center within two years. A software-defined data center is based on a virtualized environment of compute, storage, networking and security in conjunction with policy-based management and automation. The evolution from a traditional data center architecture to one that is software-defined can take months if not years but can yield immense benefits for the business. Join us for a discussion on the progress toward the fully software-defined data center, including benefits of infrastructure as code and overcoming challenges associated with traditional workflows.

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?

Moving on-premises legacy data and analytics workloads to the cloud is unavoidable if you want to overcome infrastructural constraints, facilitate proactive analytics, and lower costs. You need a service that enables seamless scalability for petabyte-scale data processing, interactive analytics, and machine learning. However, end-to-end, automated workload transformation and optimization on serverless services is not straightforward.