The West Coast Data & Analytics Event schedule

• Defining the role AI in empowering local economies
• How AI can be used to improve efficiency and effectiveness?
• Developing a long-term strategy
• The DoorDash Journey, challenges and lessons learned

In the era of Artificial Intelligence (AI), data strategy stands as the linchpin for organizational success and innovation. This presentation delves into the critical intersection of data strategy and AI, exploring essential considerations and transformative imperatives for businesses navigating the digital landscape.

• How to unearth hidden prejudices within AI algorithms?
• Steps to mitigate inherent biases when using Gen AI
• Adopting ethical guidelines to govern Gen AI applications
• Implementing means of detecting and/or correcting biases

Turn Data and AI Models into production-ready web applications.

During this session, we will demonstrate how to use Taipy to create dynamic, graphically intensive applications that offer practical insights for your Data/AI decision-support applications, all within Python.

We will cover two essential aspects:

• How to create interactive dashboards with minimal coding, eliminating the need for expertise in HTML, JS, or CSS.
• Creating and managing what-if scenarios by modeling dataflows and orchestrating pipelines through an easy-to-use and flexible user interface.

Join us to explore the tangible benefits of Taipy

• Discussion Group A: Group A: Fostering a Culture Driven by Data: Empowering Informed Decision-Making
  •    Empowering your company to utilize data as a crucial factor in decision-making
  •    Striking a balance between relying on data and leveraging intuition for strategic insights
  •    Recruiting and nurturing talent to be recognized as strategic collaborators rather than mere data providers
  •    Highlighting the significance of storytelling with data to seamlessly integrate it into your organizational culture

Available for Sponsorship 

• Why Analytics are at the forefront of the AI wave of change
• How to unlock Analytical Maturity at scale across your organization
• Goldilocks – finding the sweet spot for value for your AI investments in 2024
• How to govern and prepare your data infrastructure to support upgraded Analytical AI proficiency

Sponsored by Alteryx

• Mastering the art of avoiding both "overfitting" and "underfitting" training data to maximize your machine learning model's effectiveness
• Recognizing the significance of QA testing as an essential step not to overlook in the process
•  Exploring strategies to mitigate biases and ensure fairness in ML algorithms
• Emerging trends such as federated learning, reinforcement learning, or AI ethics, and how they might shape the future of ML projects
• How to measure and maximize the return on investment (ROI) for these projects

• Spearheading an effective data literacy initiative to drive tangible and rapid transformation 
• Painting a vivid picture and conveying data's worth to non-data personnel, enhancing their involvement 
• Establishing a comprehensive framework capable of conveying data to diverse audiences with varying levels of data proficiency 
• Introducing user-friendly data analytics tools that don't require advanced technical skills

• Using generative AI for producing new features
• Using ML for data analysis
• Gen AI in the realm of e-commerce
• Using Gen AI for data analysis
  
  

• Using generative AI for producing new features
• Using ML for data analysis
• Gen AI in the realm of e-commerce
• Using Gen AI for data analysis
  
  

• What does it take to actually become a customer-centric organization?
• Shifting from product-driven to customer-driven: best practices to adapt the entire data ecosystem
• How to align your business practices, data analytics, and talent development, around delivering personalized relationships
• Balancing hyper-personalization with data privacy

Panelists:

• Vineet Kumar, Head of Data Science- GTM Sales AI, LinkedIn 
• Kathleen Maley, VP, Analytics, Experian 
• Prachi Priya,Prachi Priya, AI Strategist, Advisory Board Member, Data Leadership Collaborative, Former 
  Chief Data & Analytics Office

Moderator:

• Strategic AI Investments: Highlighting key investment trends and how financial leaders can leverage AI to drive corporate strategies that align with current market dynamics.
• Risk Management in the AI Era: Discussing contemporary risk management techniques to navigate the evolving challenges and regulatory landscapes associated with AI technologies.
• Monetizing AI Innovations: Examining the latest approaches to generating revenue from AI initiatives, focusing on sustainable growth and value creation in today’s economy.

Data and analytics leaders know that delivering AI solutions requires hard conversations about data readiness. Conflicts around priorities, governance, and tech debt are inevitable as teams strive to balance delivering rapid value with sustainable data infrastructure. Ultimately, the success of a team depends on its leaders' ability to navigate conflicts effectively, fostering an environment where diverse perspectives and constructive debates are encouraged to drive innovation and achieve excellence,

In this interactive session, we’ll:
•    Explore active listening and powerful questions as a foundation for cross-team collaboration.
•    Learn a simple but effective model for straight talk that can transform challenges into shared wins.
•    Share and connect with best practices. 

• Employing cutting-edge analytics tools to extract meaningful insights from data, enabling informed decisions
• Investing in data cleansing and validation processes to ensure accuracy and reliability
• Training personnel in data analysis and interpretation, enhancing their decision-making capabilities
• Investing in systems that provide real-time data updates, facilitating timely decision-making
• Ensuring data investments align with ethical standards and regulatory compliance

• How do you overcome issues caused by availability of data?
• How do you retrain AI models for similar use cases with limited manpower?
• In what ways can you bring citizen data scientists to fruition in order to utilize additional insights?

• Understand the challenges data mature enterprises are facing as they enable self-service reporting
• Discuss how AI can be used to reduce inevitable analytics risks
• Dive into cost optimization opportunities in enterprise reporting

• Exploring the advantages of varied team structures for enhanced coordination and collaboration
• Leveraging internal data to shape novel and inclusive diversity & inclusivity strategies
• Acknowledging and addressing both deliberate and unintended consequences of quotas within your team
• Elevating diversity & inclusivity engagement through advanced learning and development initiatives
• Establishing channels for team members to provide feedback on diversity and inclusivity initiatives