Latest Posts
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Designing AI Infrastructure for the Modern Enterprise
Enterprises are increasingly prioritising AI infrastructure, particularly generative AI, as essential for integrating AI frameworks into business workflows. The demand for specialised infrastructure is driven by the need for scalability, cost efficiency, and reliability, especially… Read more
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Avoiding Data Quality Failures: Enterprise Challenges and Best Practices
Data quality is crucial for businesses, as poor data quality can lead to significant financial losses and hinder decision-making. It encompasses dimensions such as accuracy, completeness, uniqueness, consistency, timeliness, and validity. Enterprises often struggle with… Read more
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Building Enterprise Data Lineage & Provenance
Data lineage is crucial for data management and governance, tracking data from its origin to destination. It ensures quality control and compliance, benefiting data engineers and owners. Unlike data provenance, which focuses on the origin… Read more
Archive Posts
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[Update 2023]: If you are an Enterprise user of Pentaho/Hitachi Vantara, please contact the Pentaho support team to help with approved solutions and approach. Otherwise, you could possibly violate the contract of the PRD. In Pentaho Report Designer, adding a parameter is a very simple process. You just need to go to the “Data” Section…
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The post discusses how to handle memory issues in Pentaho. Solutions include increasing memory parameters for on-premise installations, making specific considerations for running Pentaho on Java 11 or higher, or on Kubernetes.
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Error Handling becomes a very important step when you are trying to develop any application. It makes developer’s life easy if there is a proper way to understand Errors. Pentaho Data Integration (Kettle) provide a very easy step to handle exception. The only effort is to define an error handling output and to stream your…
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