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Stating the obvious, the first step is to register on sprngy.com and select your product preferences. Sprngy provides a trial to get familiarized with the product set.

After the registration is complete, Sprngy will send a confirmation email when the cloud resources are deployed and ready for use with link to the administrative interface. This process usually takes 15-20 minutes after registration is complete.

Using the link to the administrative interface, you can:

  • Set up Application: 'Define the Data entities grouped under an ‘application’. E,g, ‘Billing’ application can have entities like ‘client’, ‘services’, ‘bills’, ‘payments’ etc. Relationships between the entities can be defined here.

  • Upload Data: Upload data in csv files for the entities defined.

  • Define metadata blueprint: Define the ‘Meta Model’ using the steps provided in the interface. Bulk upload feature is also available to be used as an alternative.

  • Define Data processing preferences: Using the simple screen provided in the interface, define data processing preferences in the ‘Ingest Model'. Bulk upload feature is also available.

  • Run workloads: Workloads can now be run to process the data. Workloads can be run in two steps:

    • Staging Data Lake (SDL) to Fast Data Lake (FDL): This is to run Sprngy’s pre-built data profiling pipelines based on the meta model and ingest model definitions. This workload results in pristine data layer.

    • Fast Data Lake (FDL) to Business Data Lake (BDL): This is to run Sprngy’s pre-built data correlation pipelines based on the meta model and ingest model definitions. This workload results in business-ready data layer providing rapid access to curated and correlated data.

Other features the administrative interface provides are:

  • Define Data Import Routines: Import routines (including connection details) to import data from other sources can be defined using the ‘Import Model’. This is for advanced use cases.

  • Define Analytic Models: Algorithms to support machine learning modelling requirements can be defined using ‘Analytic Models’. This is for advanced use cases.

  • User Management: Features to manage Access and permissions to the administrative interface.

  • Manage Workloads: Features to monitor workload status as well as for re-running and deleting workloads, as required.

  • View Logs: Interface to filter and view application logs.

The user interface guide provides in-depth information for all the above features.

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