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In this episode of the podcast, we explore how enterprises can streamline their data practices and supercharge analytics by unifying data through robust Enterprise Data Management (EDM) and integration strategies. From post-M&A data consolidation to crafting standardized templates for ETL, data quality checks, and prioritizing chunks of high-value data—this single source of truth ensures AI, analytics, and insights aren’t hampered by “garbage-in, garbage-out.” Join us as we unpack pragmatic steps for achieving seamless integration, reusable governance, and trusted, high-quality data foundations.
https://blog.datamatics.com/streamline-enterprise-data-management-edm-and-analytics-practices-through-data-integration
By DatamaticsIn this episode of the podcast, we explore how enterprises can streamline their data practices and supercharge analytics by unifying data through robust Enterprise Data Management (EDM) and integration strategies. From post-M&A data consolidation to crafting standardized templates for ETL, data quality checks, and prioritizing chunks of high-value data—this single source of truth ensures AI, analytics, and insights aren’t hampered by “garbage-in, garbage-out.” Join us as we unpack pragmatic steps for achieving seamless integration, reusable governance, and trusted, high-quality data foundations.
https://blog.datamatics.com/streamline-enterprise-data-management-edm-and-analytics-practices-through-data-integration