Many data leaders are coming up against roadblocks preventing the promised benefits of the cloud – scalability, flexibility, and interoperability to name a few.
Join Don Gray, Chief Data Officer & SVP at Highmark Health, who will share his approaches to:
•Educate business partners
•Address challenges including governance and legacy
•Reducing risk to consumers

According to KPMG Capital, 99% of businesses consider data and web analytics to be important to their organizations, yet 85% of executives struggle to analyze and interpret their existing data. Analytics are the foundation for a differentiated customer experience and more meaningful engagement. What begins with using data to understand the customer, then deriving actionable insight from that data to achieve top-line growth and provide a consistent brand experience across all customer touchpoints, is a top priority for many organizations.
Expanding the pool of people who can analyze and develop meaningful business action from data is therefore critical to gain a competitive edge. Data democratisation as a goal has been hampered by silo issues, fears around data quality and access to skills to analyse it properly. That said, if done properly it will enable different functions to make better decisions and collaborate more effectively.
Critical to success is creating a culture where people want to take control of their own data destinies and how can IT be an enabler given the critical questions of governance.

Data and analytics is part of every business decision around digital transformation, and is now widely recognized as arguably the most important strategic asset of an organization. CDOs, CAOs and D&A leaders know that the key to success in this digital age is data. To capitalize on the true potential of data at our fingertips, organizations must fundamentally change how they view and use data.
Transforming the view of D&A from what was typically considered a support function, to a strategic growth asset and core business competency requires data leaders to innovate to match the pace of digital transformation. How do D&A leaders quantify and prove the ROI of data initiatives in the context of business value? How can data leaders drive change while bridging the gap between business and technology?

During this roundtable session we will discuss:
•How do you create frictionless collaboration within your data ecosystem - people, tools and data?
•How do you get data to the last mile, while the underlining infrastructure continues to change at a rapid rate with so many moving pieces?
•We hear that data is the new oil. What do organizations need to do to become/cultivate a data driven culture?
•What does the future hold for the CDO role and the senior data leaders that support it? What are the key challenges & successes involved – leadership qualities, longevity, skillsets required, future vision etc?
•What cultural and infrastructural changes are required to adopt real-time, open, secure, and scalable data analytics throughout the organization?
•Value delivery is often dependent upon the relationships between business strategy, data and analytics, being digital and execution. How do you link these dependencies together for a strong outcome?

Scaling and operationalizing AI, ML, and Data Science are critical to driving value and impacting how decisions within the business are made. It is vital for CDOs and D&A leaders to establish the technology trends, organizational requirements, skill development and talent required for successful deployment. How can we set ourselves up for success and develop a transformative vision for AI, enable enterprise-wide AI strategies, and use AI as a strategic differentiator?
In enterprise AI, there's a gap between what's possible and what's expected - a disconnect that is hurting implementation. While the ultimate goal for AI adoption is a more efficient organization, sometimes the gap between the possible and the achievable is too big. Sometimes, the technology is ready to deliver, but the infrastructure and quality of data aren't quite there yet.

This roundtable will explore the following key questions:
•Implementing new tech like AI often requires new ways of operating, how can organizations rethink their operations from both a business and IT perspective?
•What tools, platforms and services do organizations need to ensure they are flexible enough to adapt to a fast-moving environment?
•Strong AI outcomes require trust, data-fluency, and agility. Why is leveraging change management to create the right culture so important?
•How can organizations ensure their teams and staff are equipped with the right skills?
•In terms of AI, what is the biggest emerging trend you are seeing? Are generative AI platforms like Chat GPT the future? How can we successfully integrate them into our lives?

Data democratization will catapult companies to new heights of performance, if done right. The ultimate goal is to have anybody use data, at any time, to make decisions with no barriers to access or understanding (Bernard Marr). Businesses that wish to benefit from data democratization will have to create it intentionally. This means an organizational investment must be made in terms of budget, software & tools, and team training. So how do we get there?
Expanding the pool of people who can analyse and develop meaningful business action from data is critical to gain a competitive edge for your business. Data democratization as a goal has been hampered by silo issues, fears around data quality, and access to skills to analyse it properly. That said, if done properly it will enable different functions to make better decisions and collaborate more effectively. Critical to success is creating a culture where people want to take control of their own data destinies and how can it be an enabler given the critical questions of governance.
Businesses armed with the right tools and understanding are succeeding today because their employees are armed with the knowledge necessary to make smart decisions and provide better customer experiences. The transition to a more democratized view of data should not be a binary choice—fully centralized or decentralized. Data democratization must be viewed as a full continuum of options between those extremes. The ideal solution is found by monitoring for a ‘goldilocks’ state for data democratization (not too much and not too little) and engaging in the culture and process changes inside a company that makes it possible.

This roundtable will explore the following key questions:
•Moving to a more democratized use of data may mean significant organizational change that a company has not previously considered and for which it is unprepared. Where do you start?
•What kind of activities build employees trust in data and a willingness to follow and even contribute towards an effective data strategy that shows the value?
•What is the forefront of data democratization and what kind of results are companies seeing when trusting employees within a clear structure?
•How is technology enabling companies to overcome silo, data quality and enablement issues? What tools have you found successful?
•How could we scale real-time analytics to every worker, every device, so that every business decision is data-driven?

We’ve all heard “Data is the new oil” – Data has immense, untapped potential, but requires processing, cleaning, and analysis to draw out insights that create value for our businesses. Even more, it requires building and sustaining a culture around data – diligent data practices applied consistently. In this presentation, I will share the frameworks our teams have applied at Bloom Energy to accomplish business growth (10% growth in revenue annually) through data insights.

We are undoubtedly living in a time where organizations cannot ignore or underestimate thoughtful adoption of artificial intelligence. But the question remains; how do we navigate briskly changing trends and rapidly growing business demands, especially given economic recession creating the burden of extreme budget constraints? Join Saima Shafiq from PNC who will walk us through effectively ‘Riding the AI Wave’.

The term “big data” is ubiquitous. With exabytes of information flowing across broadband pipes, companies compete to claim the biggest, most audacious data sets. And businesses of all varieties — old and new, industrial, and digital, big, and small — are getting into the game. But the reality is that our relentless focus on the importance of big data is often misleading. Yes, in some situations, deriving value from data requires having an immense amount of that data. But the key for innovators across industries is that the size of the data isn’t the most critical factor — having the right data is. Businesses armed with the right tools and understanding are succeeding today because their employees are armed with the knowledge necessary to make the right decisions and improve their customer’s experiences. It may seem obvious that the employee experience shapes the customer experience, and that employee empowerment, satisfaction and success will impact customer success. But those truths are commonly under-prioritized or siloed when business pressures mount. Today, we will discuss the challenges we often encounter as we work to empower our employees with the right data at the right time to serve our customers and ways to work through these common challenges.

With the rapid advancement of technology, the amount of data available to organizations has increased dramatically, making it more important than ever to understand how to effectively use data to improve customer engagement and experience. According to recent studies, using data analytics to drive customer engagement can result in significant benefits for businesses. For example:

•Companies that prioritize customer experience have seen a 15% increase in revenue compared to those that don't (Forrester)
•75% of consumers are more likely to purchase from a company that provides personalized experiences (Epsilon)
•Companies that use data to drive decision-making are 6 times more likely to retain customers (Forbes)

Our panelists will share their insights on how to turn data into actionable insights, and how to use those insights to personalize customer experiences and drive engagement. We will also discuss the latest trends, tools, and techniques for using data to drive customer engagement.

The discussion will cover topics such as:
•How to effectively collect and analyze customer data
•Using predictive analytics and AI to personalize customer experiences
•Building a data-driven CX strategy
•Navigating & curating disparate, unstructured data across multiple systems
•Key metrics and KPIs for measuring success

With the introduction of generative AI, the pressure for businesses to deliver AI-driven outcomes is increasing. In this session we will discuss common challenges in operationalizing AI, guiding principles for delivering lasting value in this space, and ideas for getting started with generative AI.

With the exponential pace of change unleashed via recent AI innovations, in this session we will explore changes to the workplace and what skills and knowledge will be required to stay relevant in the job market. We will also delve into corresponding ethical considerations.