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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This blog post discusses about the building of OpenAI GPT Assistant Framework using Pentaho Data Integration. The blog post discusses the integration of OpenAI GPT Assistant with Pentaho Data Integration to leverage generative AI capabilities. It covers topics such as OpenAI GPT models and their available APIs, the use of Assistants Framework, Pentaho transformations/jobs and…
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This post dives into the use of Pentaho Carte, a lightweight web server for running and managing remote Pentaho data transformations and jobs. The post covers how to set up the station with either command lines or Docker, run multiple servers, and customize configurations. It also looks at how to use Carte via UI, exploit…
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The article discusses image classification in machine learning and AI, with a focus on Convolutional Neural Networks (CNN). It explains the basic concepts, application, and architecture of CNNs, and their limitations. It highlights the processing of the MNist dataset and real-world image classification problems. It also indicates the use of pre-trained models like AlexNet and…
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Google Cloud recently unveiled Vertex AI, a unified AI/ML platform designed to fast-track the development and maintenance of AI/ML solutions. Offering a unique, integrated pipeline and requiring 80% less coding than similar platforms, Vertex AI encompasses data extraction, analysis, training, evaluation, deployment, and monitoring. This innovative platform promises to facilitate MLOps procedures, thereby aiding AI-fueled…
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Building machine learning (ML) systems can be an arduous process that includes a wealth of hidden technical debts. In enterprise set-ups, where expectation is for fast and accurate delivery of a model, challenges include data collection, infrastructure management, and model monitoring, among others. Incorporating a DevOps (development and operations) culture into the ML process can…
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