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Expert Panel: Next-Generation Data Management Identifying Emerging Best Practices and Priority Enterprise Investments

May 1, 2024

Prerequisite: None

James G. Kobielus

Senior Director of Research for Data Management

TDWI

Data is a key asset for business success. If an enterprise hopes to innovate and prevail over the competition in today’s economy, they’re going to need to sustain ongoing investments in next-generation data management platforms, tools, applications, infrastructure, and teams.

Data management technologies and practices continue to improve at a rapid pace. For enterprises trying to prioritize where to invest their precious resources, the range, complexity, and rapid evolution of enabling technologies can be daunting. Likewise, it’s often unclear how they should be organizing their IT, data, and analytics teams and practices in order to manage their data assets most effectively.

In this sponsor panel, TDWI senior research director James Kobielus will lead data industry experts in a discussion of the challenges associated with prioritizing enterprise investments in next-generation data management infrastructure and organizations. Panelists will discuss such issues as:

  • What are the principal trends in next-generation data management that enterprises dare not ignore?
  • Should enterprises be moving their data management pipelines into edge, mesh, hybrid, multicloud, and other distributed infrastructures?
  • How should enterprises evolve their infrastructures to accelerate building, deployment, and monetization of next-generation data products?
  • What role will next-generation data platforms—such as vector stores—play in enterprise architectures in this decade and beyond?
  • To what extent should enterprises be investing in embedded artificial intelligence to accelerate and automate how they handle, store, analyze, secure, and govern their data?
  • How should organizations evolve their data management infrastructures in order to facilitate development and operationalization of deep learning, large language models, generative AI, and other intelligent applications?
  • What sorts of guardrails should enterprises build into their data management infrastructures to ensure privacy, mitigate bias, control algorithmic hallucinations, and address other governance imperatives?
  • How should organizations be training, recruiting, and incentivizing their knowledge workers in order to boost data literacy to the level needed to succeed in this new era?

Agenda Key

  • Analyst Insights: the latest trends and research delivered by TDWI analysts.
  • Expert Best Practices: experts, with in-the-trenches expertise, focus on best practices and successful real-world applications
  • Curated Case Studies: case studies, delivered by experts in the field, with a focus on actionable takeaways
  • Tech-in-Action: moderated technology demos and case study sessions that enable attendees to assess all the latest AI applications and technologies
  • Workshop: Interactive session where leaders come together with peers, with an expert facilitator, to discuss common challenges and proven best practices

Register Online

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TDWI Chicago

Chicago, IL
April 28–May 3