The need for Data Quality-Centric Data Observability

Buzzword or Business-critical? Like every new product category, organizations are grappling with the emergence of the data observability space and what to do next. Regardless of where this market is headed, one question surfaces? Can it solve an age old problem around Data Quality? In this webinar, we will see how a comprehensive approach with both content and context is needed for Observability to add Business value in the space of Data Quality.

Abstract:

For the past few decades, data has been growing and technologies used to build modern data stack has been exploding. Amidst that are also new approaches that have been surfacing with business yet to see if it would result in “real” value. One such approach is Data Observability and the focus towards Data Quality. We all know that the cost of fixing bad data quality is less at source or upstream (production) than identifying and fixing later at downstream (consumption). But can it solve the below issues or challenges

• Will it solve the majority of the problem using upstream observability vs downstream?
• Does it add value to the business if downstream content and context is ignored?
• Does Data Observability create Email fatigues or truly solve the problems?
• Does it enable the concepts of decentralized data ownership as Data Mesh talks about?
• Does it enable Data engineers to effectively manage their data platforms and collaborate across all personas and more importantly their use cases?
• Or more importantly does it add a direct value to business and strategic outcomes?

On a high level, simply one could say “YES” to all but in this webinar CEO and Founder of DQLabs, Raj Joseph coming from the data quality trenches, sits down with industry expert and Principal, SanjMo, Sanjeev Mohan, to unpack the world of Modern Data Quality, the rise of Data Observability, and its critical intersection with Data Quality. In this 30-minute fireside chat, we unpack the new data landscape and what data producers, consumers, and leaders should consider when building a Modern data strategy for the future.