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  • Data Curation:

    • Importing data from disparate sources and defining curation to data to build a single source of truth using data lake technology

    • Defining metadata blueprint with Sprngy’s ‘Meta Model’

    • Creating a pristine data layer with Sprngy’s pre-built, low-code pipelinesdynamic data processing engine

  • Data Correlation:

    • Defining relationship between data entities with Sprngy’s intuitive admin UI user interface.

    • Creating business-ready data layer primed for rapid access at scale with Sprngy’s pre-built, low-code pipelines

  • Data Analysis:

    • Creating and sharing visualizations with Sprngy’s in-built visualization tool

    • Creating ad-hoc queries using the query browser available in the visualization tool

    • Auditing and monitoring the platform with in-built audit visualizations.

    • Connecting a visualization tool and/or a querying tool of your choice

  • Making Predictions:

    • Supporting machine learning model development and testing

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