What to Consider When Building a Data Quality Strategy (Data Quality Series Part 2)

By Kunju Kashalikar

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)

By Kunju Kashalikar

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.

Competing Globally Through Data Agility: Grupo EULEN Becomes Data-Fit with Pentaho

By Pentaho

Grupo EULEN uses the Pentaho+ Platform to boost agility, streamline data workflows, track metrics, and drive faster, smarter decisions.

Bridging The Gaps: Helping Mid-Tier Bank IT Teams Minimize Risk and Reach Data Modernization, Compliance and AI Goals

By Joshua Wick

Mid-tier banks face unique challenges in data modernization, governance, and compliance due to budget and resource constraints, requiring tailored strategies to meet growing regulatory and AI demands.

Why Mid-Tier Banks Require a Closed Source Data Management Solution to Meet DORA Compliance

By Joshua Wick

While DORA is a looming regulatory burden, it presents a real opportunity for smaller and mid-sized banks.

Data-Fit and Future Ready

By Maggie Laird

Pentaho President Maggie Laird on What’s New and What’s Next

Simplifying Complex Data Workloads for Core Operations and GenAI Aspirations

By Kunju Kashalikar

Automation, built-in governance, data quality and storage optimization all enhanced in Pentaho’s latest platform update

 
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