This session will describe the foundational concepts for the discipline of master data management and the technology solutions that support it. What is master data and why is it important? What are the most common business benefits of successful MDM programs? What are the discipline and technology components of a successful MDM program?
Organizations' increasing need to connect things that share data -- disparate data and analytics programs, MDM and master data stores, applications, processes, teams and external partners. But without a well-planned strategy based on requirements for mediation and governance, it's hard to enjoy a smooth flow of trusted data. What are data hubs and how do they support data sharing and governance? What are the most effective starting points for a data hub strategy? What are the best approaches to architect and deploy data hubs?
This session will describe the foundational concepts for the discipline of master data management and the technology solutions that support it. What are the current states of the MDM discipline and its associated software market? What are the latest implementation trends and market developments? How can you prepare to effectively take advantage of these developments?
IoT deployments tend to be one sensor for one measurement for a single purpose. But, Data and Analytics can enhance and expand the value of IoT to integrate data from many sensors and measurements with enterprise and third-party data for a grant purpose. But, the ability to integrate data depended on the ability to unambiguously identify the IoT devices, correlate over the same time periods, and connect the data with each other in a meaningful way. This session will explain the role of MDM and the unique ways that has to be deployed in order to accomplish just that.
E-commerce has served to drive a voracious appetite for product data. Satisfaction of the "demand side" of product data calls for an end-to-end data strategy and capability. What are the drivers for product data in support of digital commerce? What is the end-to-end product data capability required to satisfy digital commerce requirements? How can organizations deliver against these requirements?
Master data management is a critical success factor in constructing optimal customer experiences. Learn the benefits of aligning the MDM discipline to CX and making it a part of your CX strategies. Why is MDM critical to the customer experience? How will MDM increase and optimize your 360-degree view and your CX capabilities? What new opportunities for managing customer information does MDM bring?
Best practice roadmaps through Gartner’s implementation styles can create early high-value deliverables to any MDM program. We'll cover typical roadmaps for both customer and product master data and their ability to deliver early business value. How do you choose MDM implementations styles? What are the best practices for sequencing styles? How should you manage the risks of this approach?
Gartner's Ignition Diagnostic maturity model provides a clear process for measuring and improving the maturity of your organization's data and analytics program. Attendees will understand the key objectives and activities of the data and analytics function including: How to benchmark their maturity against other organizations.
The Future of Data Management will help plan for what’s next. It describes where the market, function or capability is going and how it’s evolving. It should help early adopters get a leg-up and more conservative companies plan and prepare for and make the changes.