Data Quality in the Age of AI and Machine Learning (Data Quality Series Part 3)
By Kunju Kashalikar
Data quality is a crucial aspect of any organization’s operations, and its impact is growing as artificial intelligence (AI) and machine learning (ML) continue to evolve. However, determining what qualifies as "good enough" data can be a challenge.
Learn more
What to Consider When Building a Data Quality Strategy (Data Quality Series Part 2)
Data Quality Series Part 2: Ensuring data quality is about finding the right balance—over-cleaning can remove valuable insights, while evolving data demands flexibility. This blog post explores how businesses can define quality thresholds, manage costs, and leverage AI-driven automation to maintain consistency and usability.
The Importance and Value of Strong Data Quality Fundamentals (Data Quality Series Part 1)
Data Quality Series Part 1: Discover how strong data quality fundamentals drive AI and GenAI success by ensuring accuracy, completeness, and consistency through end-to-end data management.
BFSI Data Quality: Implementing World Class Risk and Compliance Measures
By Joshua Wick
Considering evolving regulations, data quality will always remain at the core of BFSI resilience and competitive advantage. BFSI organizations that invest in data quality will be able to join the world’s standards, stay on-side, and scale.
New CFPB Data Compliance Requirements Will Test the Limits of Financial Data Management Strategies
Changing business conditions, the rapid shift to renewables and market pricing dynamics all require energy wholesalers to pivot strategies with agility and confidence.
Understanding Data Lineage: Why It’s Essential for Effective Data Governance
In the world of data-driven decision-making, transparency is key.
Categories
Top Authors
Christopher Keller
Maggie Laird
Joshua Wick
Steve Donovan
Rishu Shrivastava
Featured
Simplifying Complex Data Workloads for Core Operations and...
Creating Data Operational Excellence: Combining Services + Technology...