Data Strategy and ArchitectureApplied AICloud Data ManagementData AnalyticsAI & DataCloud
Briefing•1 hour

Data Strategy and Engineering for AI Briefing

A comprehensive data strategy requires aligning data assets through technology with business objectives to achieve desired outcomes. This briefing from WWT explores data strategy and foundational data component options for becoming a data driven organization, with a special consideration for delivering AI solutions.

Details

This briefing provides a comprehensive exploration of the critical components necessary for achieving data-driven AI business outcomes. We will cover data maturity, strategy, engineering, visualizations, data science and AI, highlighting how these elements collectively enhance organizational capabilities. Identifying dependencies and sharing lessons learned throughout the presentation. 

Evaluating Data Maturity We begin by requesting a very brief self-assessment of data maturity, focusing on current capabilities, desired future states, and the path to AI outcomes. This evaluation is crucial for understanding your organization's readiness to leverage advanced data capabilities and achieve strategic objectives.

Data Strategy: Data Fabric vs. Data Mesh This section offers a comparative analysis of Data Fabric and Data Mesh. We will discuss the building blocks and processes necessary for each approach, emphasizing how they align data assets with business objectives. Key considerations for establishing a quick data strategy designed for execution.

Data Engineering for Success In this segment, we emphasize the importance of designing for outcomes, covering architecture/platform considerations, data readiness, and common pitfalls. We'll share lessons learned from WWT's experiences to provide practical insights into building a robust data engineering foundation.

Transforming Data with Visualizations The visualizations section highlights the transformation of data into actionable insights and the empowerment of stakeholders through self-service analytics. This enables informed decision-making and enhances organizational agility. Including tips for ensuring end user adoption.

Harnessing Data Science & AI A high level overview aligning  business outcomes to analytics, machine learning, AI business applications, and the emerging field of agentic AI. This section underscores the transformative potential of AI in driving business innovation and achieving competitive advantage.

Conclusion and Next Steps In our closing remarks, we summarize the key points discussed and outline actionable next steps to action. 

Agenda:

  • Data Maturity 
    • Current Capabilities
    • Desired Future State
    • Value Milestones & Evolution
  • Data Strategy 
    • Data Fabric vs. Data Mesh
    • Building blocks & Processes
  • Data Engineering 
    • Design for Outcomes
    • Architecture/Platform 
    • Data readiness
    • Common Pitfalls/Lessons Learned
  • Visualizations 
    • Actionable Insights
    • Self Service Analytics
  • Data Science & AI  
    • Machine Learning
    • AI Business Applications
    • Agentic AI
  • Discussion & Wrap up 
    • Next Steps
    • Q & A

What is a Briefing? 

A scheduled event with a WWT Subject Matter Expert — typically via a live Webex — where our experts present an overview of specific topics, technologies, capabilities or market trends. Your attendees are allotted time for Q&A to pose questions specific to your organization.  

Who Should Attend? CEOs, CIOs, CDOs, data owners, line of business owners, IT Directors or anyone interested in learning more about how a comprehensive data strategy enables and transforms business, delivering data & AI solutions.

Post Briefing Actions? A data strategy workshop focused on business use case development and data source identification and evaluation.

Experts

William StanleyChief Technology Advisor