CDAO Chicago schedule

• Strategize the transformation of business models to accommodate changing conditions 
• Gaining support from team and decision makers surrounding D&A initiatives as resources may become limited 
• Uncover how to identify cost savings and optimization opportunities and implement them in a strong D&A strategy.

Mike Woods, VP and General Manager- Central U.S., DENODO

Paul Aeschleman, Sr. IT Product Manager and Technical Delivery Leader, Health Care Service
Corp.(HCSC), BLUE CROSS BLUE SHIELD

• The old way of managing data was like putting all your eggs in one basket - slow and
expensive. With logical data management, you can access all your data sources ondemand without making copies, reducing time to data by 65% and time to revenue by
83%.
• This journey from monolithic to logical architectures empowers business users with selfservice and simplifies governance.
• Takeaways: Simplify your data management journey, empower business users with selfservice, improve Your time to INSIGHT with logical architecture

Dr. Ram Singh, Chief Performance Media Officer, CROSS MEDIA USA

Harshal Patel, Business Analytics Manager, ALLSTATE

Karin Chu, PhD, VP, Head of Data Science, PEAPOD DIGITAL LABS

• Examine the state of self-service, how it is currently being provided across organizational
needs and why it is becoming a necessity
• Transform raw data into actionable insights that ultimately lead to users being more
productive and efficient
• Discuss deployment and continuous training to ensure consistent data accuracy

• Uncover what data fabric means for business outcomes 
• Methods to enlarge the current data warehouse to support data fabric design 
• Next steps after a data fabric has been planned, designed, built, and maintained to optimize the use of the new integration 

 

Moderated by: Chantal Schweizer, Practice Director, Data Services, PIVOTREE

Vijay Rajandram, Ph.D, Chief Data Officer, NORTHERN TRUST ASSET MANAGEMENT

Anil Saldanha, Chief Innovation Officer, RUSH UNIVERSITY SYSTEM FOR HEALTH

Allen Levenson, Former Head of Sales, Marketing & Brand Analytics, Chief Data & Analytics Office, GENERAL MOTORS

• How to foster a data-driven culture to see improved operation flows, increased revenue
and productivity
• Uncover tried and true methods to enable enterprises to build a data culture
• Discuss how a successful, tight-knitted culture can lead to the success of D&A solutions,
generating business value

• Top trends that can transform data management practices and infrastructure 
• Strategy to aid in selecting the right data integration tool type for your use cases in data and analytics that ensures ROI  

 

Moderators:

Sherri Adame, Software Defined Vehicle Data Governance Lead, General Motors

Tibi- Stef Praun, Principal Data Scientist, The Kraft Heinz Company

Jie Shen, PhD, Director, Digital Science, ABBVIE

Michael Spadafore, Marketing & Analytics Manager, FORD MOTOR COMPANY

• Encourage productivity and promote better decision making
• Leverage the use of data-centric AI to tailor strategies and create customized products
and services based on customer’s preferences
• Overview of the state of data-centric AI today and its profound significant advantages

• Apply advanced analytics and modeling techniques to identify patterns, trends, and
  relationships that enable decision-makers to quickly grasp the meaning and implications
  of data
  • Empower your business to effectively harness and utilize data to drive decision-making to
  be better positioned to compete in respective markets
  • Embedding data governance into data design to make data easily findable and accessible

Tim Riddle, Sr Product Director, Data & Analytics,  PREMIER INC.  

Arindam Mukherjee, Head BI, Analytics and Data Governance,  LUNDBECK  

 

• Benefit from use cases that aid in greater accuracy and efficiency, customer satisfaction and increased competitiveness

• Using data to foresee future outcomes or actions, such as forecasting product demand or predicting customer decline with predictive analytics  
• Find areas for expansion or improvement and use data-driven selections to make choices that are more in line with strategic objectives. 

• Examine the potential of ChatGPT and other large language models powered
  applications
  • Uncover concerns that the technology has unleashed such as its potential to
  produce factually incorrect information, distribute harmful content, or facilitate
  fraud
  • Discuss potential practical applications of the technology

• Explore key skills needed to make a successful, impactful data leader
• State of the market analysis on why data leadership is uniquely challenging
• Uncover an effective framework that leads to organizations experiencing an
enhance in collaboration and communication

• Discuss with your peers about how to create a D&A practice that has common objectives, is active and casual, yet has an influence on the company 
• Highlight the various team structures and the benefits of each and how to design them to align with business models 
• Methods to bridge skill gaps and leveraging external partners to provide support, scalability and efficiency 

 

Flo Castro-Wright, Chief Data Officer, CDC FOUNDATION
Kajal Chokshi, Sr Manager- People Analytics, ABERCROMBIE & FITCH CO.

• Share experiences and strategies for promoting inclusion, equity, and diversity
• Methods to overcome technology biased to improve candidate selection
processes
• How to retain and develop hired talents and maintain inclusive leadership styles

• Discuss major trends and overview of leading technologies
• Leverage machine learning to automate data analytics processes to improve
services, retain customers and more.
• The importance of being strategic with aligning new ML initiative with business
goals and KPI’s
• Use cases of ML in data that ultimately aid in delivery value and steps to take to
invest in data science and ML

• Jason Wang, Chief Risk Officer & VP, Data Analytics, ALLSTATE INSURANCE COMPANY
  OF CANADA
  Daniel Chertok, Sr Data Scientist, NORTHSHORE- EDWARD ELMHURST HEALTH
  • Earning public confidence with explainable AI
  • The use of algorithms to overcome bias
  • Incorporating transparency into existing systems
  • How to accomplish safety, security, and privacy with sensitive information