How can data architects and data scientists resolve conflicts over data quality?
Data quality is a crucial factor for any data-driven organization, but it can also be a source of conflict between data architects and data scientists. Data architects are responsible for designing, building, and maintaining the data infrastructure and governance, while data scientists are focused on analyzing, modeling, and communicating the insights from the data. How can these two roles work together to ensure data quality and avoid misunderstandings, frustrations, and delays?
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Sagar NavroopData Architect | AI | MLOps | AWS | SIEM | Observability | Technologist
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NaaG B.Helping Customers solve Data Chaos || Data Lover || Informatica || AWS || Azure || Databricks || Snowflake || AI/ML
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Parveen JainAI/GenAI/Agentic AI @Microsoft | Data Engineering | Tech Evangelist | Innovator