We are excited to invite you to the Modern Data Quality Summit 2024, starting August 20-21 at 8.30 AM PT
We bring together the best and the brightest minds in the community to share how successful organizations are effectively achieving their data quality goals. We examine modern data quality approaches and tools to meet the needs of today’s fast-paced digital worlds and to drive rapid decision-making, innovation, and growth.
Here are some of the stimulating areas of focus at this year’s MDQS!
Decentralization approach of data mesh, especially data products, is rapidly getting adopted to deliver business value faster. This track uncovers how to ‘shift left’ data quality and its impact on delivering data outcomes through marketplaces.
SanjMo
DQLabs
Nextdata
A cohesive metadata plane that connects catalog, lineage, data prep, data quality, semantic layer, observability, security, and privacy unleashes the full potential of your data governance strategy. This track covers insights, ideas, and best practices of modern approach to metadata management.
Voya Financial
DQLabs
DQLabs
Traditional data quality approaches are too rigid, time-consuming, manual, and ineffective to meet the needs of past-paced data-driven organizations. Learn new developments in the data quality space that are finally helping deliver trust.
Data Quality Camp
SanjMo
Are data contracts the missing link to reduce the impedance mismatch between data producers and data consumers? This track explores the what, why and hows of data contacts, and the importance of data quality attributes in meeting the data product service level agreements.
Data Engineering Weekly
DQLabs
Data classification involves assigning standard semantic labels to fields and datasets. This is key for a number of use cases including Data Quality, Data Discoverability, Data Governance, and Data Privacy. Unfortunately, the scope of typical data estates makes manual data classification unfeasible. This talk will cover different automated data classification approaches successfully used by specialized start-ups and big tech companies like LinkedIn and Meta.
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Company Name
Learn from the experiences of practitioners how they are transforming data quality and aligning to business strategic imperatives.
United Community Bank
DQLabs
SanjMo
What actions must one take to make data quality effective? This session brings the curtains down with actionable guidance on how data practitioners should prepare for the next generation of data quality.
SanjMo
DQLabs
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