CDO STRATEGY MEETING
Revolutionize, Adapt, Evolve
February 8, 2022 | East | Hybrid Event
This event will take place in-person, with a virtual option
A Knowledge Exchange Program for Corporate Data Leaders
Discussion based gathering for CDOs, CDSs, CIOs and SVPs/VPs (Data Analytics, Management, Governance, Integration and more) from the largest enterprises in the US
Select 4-5 discussion groups out of over 25 topic-specific options to fit your priorities and planned initiatives
Each group is led by a CDO and attended by a maximum of 12-16 Sr. Executives
Select specific engagements with suppliers that match well with your current needs and goals
WHAT IS THE CDO MEETING
The CDO Strategy Meeting is a discussion based gathering of Data Leaders from the largest companies in the US. This event is invite only and attended strictly by CDOs, CDSs, CIOs, SVP/VPs and Directors.
WHY IS IT UNIQUE?
As opposed to a traditional conference setting with a speaker/ audience format, the “discussion group” environment demands group participation which leads to a sharing of ideas and experiences at multiple levels and stages of implementation.
Each CDO is engaged with and selects on average 2-3 vendors they want to meet with. Their selection is based solely on current or planned initiatives and interest in the product/service offerings of the suppliers.
DISCUSSION TOPICS INCLUDE:
Chief Data Officers (CDOs) Role: Challenges and Opportunities in 2021
Leverage the new emphasis on data and invest in your organization’s future
- Challenges: what role the CDOs play in determining their organization’s success or failure?
- Opportunities: build robust plans for responsible data collection and sharing
- Data as-a-Commodity: what are the lessons learned from the pandemic about the role of the data and the new ways of harnessing data and delivering insights to help the business adjust.
AI Holistic Strategy
Develop an enterprise-wide AI strategy
- Identify the elements of your analytics program
- Ensure AI solutions are bringing value to the enterprise
- Master data fluency and excellence and provide the highest value to your enterprise analytics at the lowest cost to the organization
Develop an enterprise data engineering for better decision making
- Build data orchestration platforms to become a data-driven company
- Invest in data discovery engines to make data, findable, accessible, interoperable, and reusable
- Implement data Lakehouse to conduct machine learning and businesses intelligence
Why ethics, security, and privacy are imperative for your AI strategy
- Provide the framework, governance, and guidance to enable implementation
- Identify the inhibitors to the adoption of AI \ ML
- Ensure the security of your data and AI systems from unauthorized access, use, and cyber-crimes
How to become a data-driven company?
- Define a business demand to solve a critical business need to help your organization realize the value in its data investments
- Identify the cultural challenges that impede your data initiatives
- Recognize data-driven transformation is a long-term process that requires resilience and fortitude
Building a Data Strategy
Develop data strategy in tandem with your business strategy
- How do we leverage the data that we have today?
- How to use data to support business processes, measure them, and improve them
- Understand data value across the three business dimensions, Increasing revenue, decreasing cost, and managing risk
Big Data Strategies in the Digital Economy
How big data is the driving force for the IT investment strategies and creating future opportunities for your organization
- Develop best-in-class data platforms and flows, enhancing e-commerce and digital platforms with AI/ML
- Integrate self-service and AI into your business environment
- Build a foundation for AI capabilities to incorporate into your digital transformation requirements
Build a Data Privacy Framework
Develop a data regulation framework that encourages innovation, data sharing, and gain people’s trust that their data is being used responsibly.
- Establishing standardization and transparent methodology that defines a data governance principle that ecosystem partners can rely on
- Assess the risks, transparency, and due diligence to protect against poor decisions
- Use data and turn it into value for your customers