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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 manageAccess 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 Admin UI user interface guide provides in-depth information on using the interfacefor all the above features.