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Background
Data and Analytics industry has a lot of good solutions - for example platforms that can do data warehousing well, platforms that do data processing well and platforms that specialize in visualization but these platform accentuate silos when put into business use. Additionally, while making all of these work together for going from data to analytics, there are significant overheads that customer organizations have to incur. These overheads then become an example of technology being an end to itself.
Features' Overview
With Sprngy’s feature set, it is easy to go from raw data to insights quickly, without worrying about any of the technology overheads. Some features Sprngy provides are:
Connector Ecosystem
Low Code Data Life cycle Management
High performance Data Stores
High Performance Query Layer
Intuitive User Interface
Scale-as-you-go with public cloud
Auditing and monitoring features for each stage of data life cycle
Inbuilt visualizations for data ingestion, balance, audit, control, quality and governance
Business Intelligence Capabilities
Machine learning for advanced analytics
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