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What use cases does Sprngy cover?
Sprngy is a unified platform to provide Data Life Cycle Management features on the cloud. It includes data import, data profiling, data curation, data correlation and data analysis through visualizations through predictions. Sprngy can work with structured, semi-structured and unstructured data. With its Admin interface and model-driven architecture, managing the data lifecycle and adapting to business changes is hassle-free.
What benefits does Sprngy deliver?
Often, data scientists end up spending a lot of time in manual or administrative tasks like preparing the data for analysis. Their time should be spent on identifying business insights to continue to provide competitive advantage to their organizations. Sprngy automates the underlying data life cycle management to ensure data scientists’ time is well spent. Additionally, Sprngy provides:
-> Bring Data from anywhere: With built-in connectors to leading platforms and data sources, importing data was never easier!
-> Get started in minutes: With its model-driven architecture, data pipelines can be set up in minutes.
-> Everyone is a data scientist: Sprngy uses a low-code approach making it easy for anyone to set up, use and troubleshoot the application.
-> Deep Dive troubleshooting: Built in auditing and monitoring features provide diagnostics at each step of the way and forward and backward traceability.
-> Adapt to changes, quickly and easily: Rule-based processing ensuring Changes can be incorporated in near real-time and easily.
-> Optimize cloud spend: Optimize cloud spend by leveraging the auto start/stop configuration on the cloud. These benefits lead to low Total Cost of Ownership, low barrier to user adoption and maximizing time spent on more valuable activities.
What are the key features of Sprngy?
Sprngy is built to ensure data scientists can go from raw data to meaningful insights quickly and hassle-free. Sprngy provides the following features to enable that goal:
1. Ingest: built-in connectors for leading CRM, Cloud, Social Media, Marketing and RDBMS platforms as well as features to create custom connectors.
2. Curate: Intuitive UI interface to provide data definition, annotations and rules to get to pristine data easily.
3. Correlate: Create algorithms to identify trends, patterns and business drivers specific to your industry.
4. Analyze: Built-in visualization layer to review correlated business data as well as audit logs to monitor the application.
5. Predict: Features to build models to make predictions.