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Data Governance (530 results) showing 291 - 300



This solution intelligently links & combines records from two related data sources into a single master record. The module acts as a crucial component in Master Data Management. It assigns a common ID to records belonging to the same entity/duplicates. The probabilistic linkage algorithm provides...

Model Package - Fulfilled on Amazon SageMaker


Cloud303 will conduct a 60-minute FTR assessment with the relevant stakeholders to assess your current standing against the requirements of the Foundational Technical Review depending on the customer path of deployment (Partner Hosted or Customer Hosted). After the discussion, the customer will be...


The Databricks Accelerator is the ultimate solution for turbocharging your Databricks implementation, guaranteeing sustained reliability and simplified management. With our expertise in AWS, Databricks, and automation, we are providing you with a tool that empowers you to unlock the full potential...


The Voyager Program Manager is essential in directly supporting and managing the deployment of the Voyager software product, available on AWS Marketplace, focusing on information retrieval and data governance within AWS Cloud environments. This senior role is tasked with the strategic oversight of...


Eratos is powered by a distributed infrastructure that makes isolated and siloed datasets accessible, discoverable and manageable, while the data remains at rest. Our Cloud Development Environment application layer enables users to collaboratively build solutions that generate novel insights which...


Our Data Analytics Assessment service on AWS offers a comprehensive and systematic approach to evaluating and optimizing your data analytics capabilities. With three key stages - Discovery, Assessment, and Recommendations - our process ensures a thorough examination of your data infrastructure,...


Whether you're starting your journey by deploying your first ML workload on AWS or if your company is looking at expanding your ML footprint, the value of ML Ops cannot be understated. Bringing the discipline and efficiency of DevOps into your ML practices creates a system process for moving your...


Lower total cost of ownership, flexibility, and value-for-money. Collaborative, iterative, and user-first approach to delivery. Utilise, transform, and integrate data sources at scale. Optimised data infrastructure for each use case. Analyse and synthesize structured/unstructured data in a unified...