{"id":8167,"date":"2026-08-17T10:17:55","date_gmt":"2026-08-17T10:17:55","guid":{"rendered":"https:\/\/argonos.com\/preprod\/?page_id=1614"},"modified":"2026-10-23T16:21:49","modified_gmt":"2026-10-23T16:21:49","slug":"data-preparation","status":"publish","type":"page","link":"https:\/\/www.argonos.com\/preprod\/en-us\/platform\/data-preparation\/","title":{"rendered":"Data Preparation"},"content":{"rendered":"\n
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    \n \n \n Home<\/a>\n \n \/<\/span>\n <\/li>\n \n \n Platform<\/a>\n \n \/<\/span>\n <\/li>\n \n \n Data Preparation<\/span>\n \n <\/li>\n <\/ol>\n <\/nav>\n \n \n <\/span>\n \n Argonos Data Preparation<\/span>\n <\/p>\n \n \n Transform raw data so<\/span>\n \n your people and agents<\/span>\n \n can act on it.<\/span>\n <\/h1>\n\n \n

    Argonos Data Prep turns raw source data into datasets your operations can run on. Build the pipeline visually, supervise it running, and trace every value back to the source system it came from.<\/p>\n\n <\/div>\n \n \n \n Book a demo<\/a>\n <\/div>\n <\/div>\n\n \n

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    \n \n \n <\/iframe>\n <\/div>\n\n <\/div>\n <\/div>\n <\/div>\n <\/figure>\n <\/div>\n\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n\n \n \n \n <\/section>\n\n\n\n\n
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    \n Your data ready for<\/span>\n \n AI work<\/span>\n \n <\/h2>\n \n <\/div>\n\n \n
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      \n \n <\/ellipse><\/path><\/path><\/svg>\n <\/span>\n \n \n Data an AI project can use<\/span>\n \n \n

      Pull scattered source data into one prepared set your models and agents can consume. <\/p>\n <\/span>\n \n <\/div>\n <\/li>\n \n \n

      \n \n <\/circle><\/path><\/svg>\n <\/span>\n \n \n Legacy data in modern workflows<\/span>\n \n \n

      Reshape decades of historical data for modern environments, platforms, and processes. <\/p>\n <\/span>\n \n <\/div>\n <\/li>\n \n \n

      \n \n <\/line><\/rect><\/rect><\/rect><\/svg>\n <\/span>\n \n \n One dataset behind every report<\/span>\n \n \n

      Analytics and reporting teams draw from the same prepared source instead of dozens of private spreadsheets. <\/p>\n <\/span>\n \n <\/div>\n <\/li>\n \n \n

      \n \n <\/circle><\/polyline><\/svg>\n <\/span>\n \n \n Proof behind every number<\/span>\n \n \n

      Show the source, the transformation and the data behind any figure and decision, months after the pipeline ran. <\/p>\n <\/span>\n \n <\/div>\n <\/li>\n <\/ul>\n \n \n <\/div>\n <\/section>\n\n \n\n\n\n

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      \n \n \n HOW ARGONOS DATA PREP WORKS\n <\/span>\n <\/span>\n \n

      \n \n Turn fragmented data into\n <\/span>\n \n \n operational data\n <\/span>\n <\/h2>\n\n
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      Preparing enterprise data is more than a series of technical transformations. It’s a continuous process that turns fragmented information into reliable, operational data the enterprise can consume.<\/p>\n\n <\/div>\n <\/div>\n\n

      \n\n \n \n \n Prepare<\/span>\n \n Build pipelines visually. Scale confidently.<\/span>\n <\/button>\n \n \n Clean<\/span>\n \n Clean, standardize, validate and enrich your data<\/span>\n <\/button>\n \n \n Lineage<\/span>\n \n Every value traceable to where it came from<\/span>\n <\/button>\n \n \n Supervise<\/span>\n \n Monitor your data workflows in real time<\/span>\n <\/button>\n \n \n Extend<\/span>\n \n Adapt Data Preparation to Your Environment<\/span>\n <\/button>\n <\/div>\n\n
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      \n Prepare<\/span>\n \n

      Build pipelines visually. Scale confidently.<\/h3>\n \n
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      Create, orchestrate and reuse data preparation workflows through an intuitive visual environment. <\/p>\n\n <\/div>\n \n

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      • \n <\/polyline><\/svg>\n Drag-and-drop workflow design, no code required<\/span>\n <\/li>\n
      • \n <\/polyline><\/svg>\n Transformation logic saved as components and reused across pipelines<\/span>\n <\/li>\n
      • \n <\/polyline><\/svg>\n Custom processors, APIs, and SDKs where the standard set runs out<\/span>\n <\/li>\n
      • \n <\/polyline><\/svg>\n Enterprise connectors into your source systems<\/span>\n <\/li>\n <\/ul>\n \n

        Reduce manual preparation and accelerate time to trusted AI-ready data.<\/p>\n \n <\/div>\n <\/div>\n \n \n

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        \n Clean<\/span>\n \n

        Clean, standardize, validate and enrich your data<\/h3>\n \n
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        Verify quality inside the flow, not after ingestion and acceptance. <\/p>\n\n <\/div>\n \n

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        • \n <\/polyline><\/svg>\n Profile source data before you build against it<\/span>\n <\/li>\n
        • \n <\/polyline><\/svg>\n Cleanse, standardize, and validate as records move<\/span>\n <\/li>\n
        • \n <\/polyline><\/svg>\n Cleanse, standardize, and validate as records move<\/span>\n <\/li>\n
        • \n <\/polyline><\/svg>\n Review data issues faster, before going live<\/span>\n <\/li>\n <\/ul>\n \n

          Turn raw data into datasets teams can trust without double-checking.<\/p>\n \n <\/div>\n <\/div>\n \n \n

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          \n Lineage<\/span>\n \n

          Every value traceable to where it came from<\/h3>\n \n
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          Lineage captured by the pipeline as it runs, not reconstructed later from documentation. <\/p>\n\n <\/div>\n \n

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          • \n <\/polyline><\/svg>\n Source-to-destination lineage on every field<\/span>\n <\/li>\n
          • \n <\/polyline><\/svg>\n Every transformation recorded as it happens<\/span>\n <\/li>\n
          • \n <\/polyline><\/svg>\n Investigate a bad number back to its origin<\/span>\n <\/li>\n <\/ul>\n \n

            Improve transparency, governance and troubleshooting.<\/p>\n \n <\/div>\n <\/div>\n \n \n

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            \n Supervise<\/span>\n \n

            Monitor your data workflows in real time<\/h3>\n \n
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            Keep visibility over pipeline execution, performance and resource usage across your preparation environment.<\/p>\n\n <\/div>\n \n

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            • \n <\/polyline><\/svg>\n Execution status, processing time, and resource use in one view<\/span>\n <\/li>\n
            • \n <\/polyline><\/svg>\n Failures surfaced with the record and the step that broke<\/span>\n <\/li>\n
            • \n <\/polyline><\/svg>\n Queue priority for the pipelines that can't wait<\/span>\n <\/li>\n
            • \n <\/polyline><\/svg>\n Alerts when throughput or quality drifts<\/span>\n <\/li>\n <\/ul>\n \n

              Fit data preparation into your existing enterprise ecosystem.<\/p>\n \n <\/div>\n <\/div>\n \n \n

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              \n Extend<\/span>\n \n

              Adapt Data Preparation to Your Environment<\/h3>\n \n \n
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              • \n <\/polyline><\/svg>\n Build custom processors<\/span>\n <\/li>\n
              • \n <\/polyline><\/svg>\n Integrate APIs and SDKs<\/span>\n <\/li>\n
              • \n <\/polyline><\/svg>\n Connect enterprise data sources<\/span>\n <\/li>\n
              • \n <\/polyline><\/svg>\n Reuse and extend preparation logic<\/span>\n <\/li>\n <\/ul>\n \n

                Fit data preparation into your existing enterprise ecosystem.<\/p>\n \n <\/div>\n <\/div>\n <\/div>\n\n <\/div>\n\n <\/div>\n <\/section>\n\n