How does AI transform chaos engineering from an experiment into a critical capability? Learn how to effectively operationalize the chaos.
Data quality isn't just a technical issue: It impacts an organization's compliance, operational efficiency, and customer satisfaction.
Details
Over 10 years ago, DZone welcomed the arrival of its first ever data-centric publication. The trends surrounding the data movement have since held many titles — big data, data science, advanced analytics, business intelligence and analytics, data analytics, and quite a few more. Despite its varying vernacular, the purpose has remained the same: to build intelligent, data-driven systems. The industry has come a long way from organizing unstructured data and driving cultural acceptance to adopting today's modern data pipelines and embracing business intelligence capabilities.
Join us for the Data Engineering Virtual Roundtable as our panel of contributors and community members draw on all former terminology, advancements, and discoveries into the larger picture, illustrating where we stand today along our unique, evolving data journeys. The panel will uncover the keys to successfully build a foundation for fast and vast data intelligence across their organization, leveraging everything from seamless data ingestion, processing, and integration techniques to vector data and LLMs, data governance, and observability.
Presenters:
Jesse Davis
Chief Technologist, DZone
Dr. Tuhin Chattopadhyay
Professor - AI and Analytics, Jagdish Sheth School of Management Bengaluru, India
Joel Lubinitsky
Senior Software Engineer, Voltron Data
Sreenath Devineni
Lead Data Engineer, CVS Health
Fred Jacquet
Technology Evangelist, AI[4]Human-Nexus
Pedram Navid
Head of Data Engineering and DevRel at Dagster Labs
Ebere OYEKWE
Founder/Data Strategy, Tekdlin
Barzan Mozafari, PhD
Founder and CEO, Keebo
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