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DataNext Trust Europe - The Data Integrity, Governance & Observability Show
DAMA
Data Governance
06 Feb 2025
United States
Having reliable & trustworthy data is vital to the success of every organisation - without it all data projects & initiatives will be doomed to fail, before they have even started. Putting in place effective data quality, governance & observability standards builds organisational trust in data.
“Bad data is a bad decision you don’t yet know about” - DataNext Trust will deep dive into the key topics that organisations must consider to build trust in data & how to create a platform to gain a competitive advantage from data initiatives.
Data Day Texas 2025
Data Management
25 Jan 2025
Austin,
United States
Data Day Texas each year highlights the latest tools, techniques, and projects in the data space, bringing speakers and attendees from around the world.
IMPACT World Tour in the Minneapolis
AI
Data Management
22 Jan 2025
Minneapolis,
United States
Curious about how leading teams are driving trust and reliability in data and AI at scale? Join us for IMPACT World Tour in the Minneapolis, presented by Monte Carlo. This exclusive event is a gathering of data professionals, industry leaders, and AI pioneers, focusing on the critical theme of "Driving Trust in Data + AI."
Enterprise Data Governance Online
Data Governance
22 Jan 2025
United States
Enterprise Data Governance Online is a free online event hosted by DATAVERSITY. This annual in-depth educational program is dedicated to teaching anyone working with data to build, manage, and improve their Data Governance strategies.
CDO & Data Leaders Summit
CDO
3 - 3 Dec, 2024
New York,
United States
Join your data & analytics peers as you discover the latest trends and challenges facing your role.
CYPHER USA
21 - 22 Nov, 2024
Santa Clara,
United States
Cypher is a Must-attend event for AI professionals and business leaders to discover how Enterprises in USA are adopting Generative AI.
Tech & AI LIVE 2024 New York
AI
20 - 20 Nov, 2024
New York,
United States
Watch, learn and connect with industry professionals wherever you are in the world through our dedicated virtual platform as Tech & AI LIVE leads the drive towards digital transformation.
IMPACT: The Data Observability Summit
AI
Data Management
14 Nov 2024
United States
Monte Carlo’s annual virtual summit dedicated to sharing thought leadership, best practices, and advice about what it takes to drive impact with reliable data and AI at scale! Now in it’s fourth year, IMPACT brings together the data community to showcase the latest and greatest trends, technologies, and processes in data quality, large-language models, data and AI governance, and of course, data observability.
DAMA GA November 2023 CHAPTER MEETING
08 Nov 2024
Roswell, GA,
United States
More than half of work is accomplished by knowledge workers–usually defined as those who must “think for a living” [Davenport, 2005]. I contend that all knowledge workers work with data. Since most learn about data individually (if at all), the opportunity to gain from communal or best practices learning has not been present. Most refer to this as a lack of data literacy. Whether applied at the individual or organizational level, literacy is a binary concept and our data needs are more varied. Data proficiency and data acumen are more descriptive/useful terms and these should also be used to describe today's organizational data knowledge requirements. This program will describe five specific data knowledge requirement levels and objective behaviors that must be demonstrated by those operating at each level. Lack of this data knowledge has so far hindered society from fully realizing our collective potential benefits. More importantly, organizations adopting these data knowledge requirements can directly and immediately improve organizational knowledge worker productivity.
MLOPS + GENERATIVE AI WORLD 2024
7 - 8 Nov, 2024
Austin,
United States
Guided and selected by our committee to ensure the lessons and takeaways across these two days will help you put more models into production environments, effectively, responsibly, and efficiently.