Ignite Roundtable Discussions

Join the forefront of data innovation

Ignite your industry prowess with non-competitive roundtable discussions by dissecting the core challenges you face. Share experiences, exchange ideas, and collaborate on innovative solutions in data analytics, advanced analytics & AI in the retail and consumer industry.

Unravel challenges and seize opportunities in data utilization

Hone technical acumen in data science and engineering

Engineer innovative solutions for category management, shopper insights and M&A

Ignite discussions

Sharpen skills, forge collaborations, and unleash the full potential of data investments. Don’t just adapt—lead the revolution!

These incredibly rich discussions with your industry peers will be a wealth of idea exchanges and collaborations. Taking place throughout the summit agenda, participants simply sign up for session/topic and the discussion groups will be carefully curated for maximum benefit.

Building a support network of peers, mentors, and industry experts to navigate the challenges of AI adoption and share insights and lessons learned.

Monday Afternoon Session: 3:00 PM – 4:10 PM

Topic 1

Optimizing Data Pipelines for Scalability and Efficiency & Advanced Techniques for Data Cleaning and Preprocessing

Explore best practices and tools for designing, implementing, and managing data pipelines that can scale to handle large volumes of data efficiently. Discuss advanced data cleaning and preprocessing techniques used to address common challenges such as missing values, outliers, and inconsistent data formats. Explore and share approaches for data imputation, outlier detection, feature engineering, and normalization to ensure high-quality data for analysis and modeling.

Topic 2

BI before AI: But How? Breaking Barriers on Your Journey to AI Adoption

This discussion focuses on the critical foundation of business intelligence (BI) and analytics, setting the stage for successful AI adoption by ensuring a strong data-driven culture and infrastructure. Discuss actionable strategies and insights for overcoming barriers and getting started with AI adoption, inspiring confidence and momentum.

Topic 3 (Technical)

Building Scalable and Robust Data Analytics Platforms

Discuss strategies and technologies for building scalable and robust data analytics platforms that can support diverse analytical workloads and use cases. Participants can discuss architecture patterns, cloud-native technologies, and containerization strategies for building flexible, scalable, and resilient data analytics infrastructures.

Tuesday Morning Session: 11:00 AM – 12:10 PM

Topic 1

What is possible for your industry “if” and “when” AI is properly leveraged?

This discussion dives into the transformative potential of AI in retail and consumer from impact on Category Management to Merchandising and even supporting M&A strategies…sparking imagination and creativity around what’s possible when AI is properly leveraged.

Topic 2

Addressing Talent Shortages and Skills Gaps: Future-proofing roles and skills in the new world of Advanced Analytics and AI

Discuss the evolving role of data professionals, explore the skills and competencies needed to thrive in your data-driven organization, including technical skills (e.g., data analysis, machine learning, programming) and soft skills (e.g., communication, problem-solving, critical thinking). Brainstorm ideas for future-proofing roles and skills through ongoing training and development.

Tuesday Afternoon Session: 2:30 PM – 3:40 PM

Topic 1

Maximizing the Value of Retailer & Syndicated Data. How to Overcome Challenges in Integrating and Harmonizing external Data with Internal Data Sources:

Strategies for effectively leveraging syndicated and retailer data sets dive into the complexities of integrating and harmonizing external data with internal data sources. Participants can discuss approaches for data integration, data mapping, and data quality management to ensure consistency and accuracy across disparate data sets.

Topic 2

Securing and Governing Data in Retail and Consumer Analytics

This discussion explores approaches for ensuring data security, privacy, and governance in retail and consumer analytics environments. Participants can discuss best practices for data access control, encryption, compliance management, and audit logging to protect sensitive data and comply with regulatory requirements.