Consolidate across organisation data
to enable all possible analytics on it
To consolidate data across all sources
Consolidate data from across various data silos: Collect all data across all data silos within organisation at single location automatically and continuously. Enable analytics across all data: Capability to process structured unstructured data with advanced analytics possible on it.
All data stored together at single location
Analytics across all data possible
Scalable, robust and high performance
About Dataeaze data lake
Understanding data lake
Understanding components of data lake
Use Cases Enabled By Data Lake
Enable MIS Reporting
Enable decision makers with MIS reports getting auto refreshed frequently with latest business state. On data collected from across various sources, platform allows to build ETL and transform data to reporting data marts, where schema is catered for ease of reporting. Any BI tool can be connected to these data marts to enable MIS Reports for business users. Platform provides time guarantee SLAs varied from real time updates to batch refreshes multiple times a day
Enable Machine Learning
Build prediction models, enable targeted marketing with user segmentation engine, improve customer experience with recommendation and personalisation. Deploy Machine Learning for auto improvement of business. Platform comes up with rich set of Machine Learning libraries. With our experience and expertise of data science we take your machine learning requirements into live working systems.
Process Events Real Time
Enable use cases which need to process events as soon as arrived, update report in real time, send feedback to user or raise alert in real time Suited for IOT use cases.Platform comes up with scalable, reliable distributed real time event processing engine. Extendible in nature, any real time data processing use case can be implemented in this engine. Being extendible, any changes in requirements can easily be incorporated in it.
How do we help?
End to end data lake bringup and maintenance
Bring up an enterprise grade robust and scalable hadoop big data lake and reporting data mart Suitable to your use cases and data scale needs. Resolve source data complexity and bring your existing data on board maintain this platform to make sure use cases are served on time
Implement data engineering automation
Setup automated data ingestion pipeline. Design and build reporting data mart. Build ETL workflows as per analytics requirements
Implement data analytics use cases
Analyse your data, your use case needs Architect, Implement end to end ETL + interactive data store load + API layer Make MIS reporting, Machine Learning and Real Time reporting possible on this platform