Minerva ETL Solution
Take advantage of Minerva, a full-fledged high-performing ETL platform where size and performance are no issue.
Several massive networks rely on Minerva for real-time data collecting and data, including tier 1 CSPs. For CSPs, Minerva processes multi-vendor network-wide performance, configuration, and fault management data. These data streams are generated by hundreds of thousands of network elements and delivered at revolutionary speeds.
Smaller-sized and medium-sized networks also benefit from the advanced features and modularity of Minerva. Pick what you need and save money. Leverage advanced modules but choose only the parts you need, depending on the use case and network size.
Open-source and modular ETL platform
Integration with existing systems is easy due to the open-source ETLs architecture. The well-known and high-performing open-source PostgreSQL ETL data warehouse serves as a basis for our Minerva solution.
Integrate other solutions to boost innovation. Our 1OPTIC platform provides other solutions that perfectly integrate with the Minerva ETL solution.
The platform’s modularity also allows Minerva ETL platform to be the excellent base solution for building an advanced data analytics platform. It is perfectly suited for rolling out advanced machine learning algorithms or for specific AI purposes.
How does Minerva ETL work?
The first part is the Extraction part. During the data Extraction phase, raw data is being exported or moved from data source locations. The data sources can either export structured or unstructured data. Minerva is the perfect data extraction tool.
Some examples of these data sources are;
- SQL and NoSQL servers
- Flat files
- CRM systems
- ERP systems
Minerva can either push or pull data, where extraction requests can be made. The whole extraction process can either be scheduled or on-demand.
One of the major and unique features of Minerva is that it supports multi-vendor data sources and is able to extract them all.
Minerva processes raw data and transforms it to the desired analytical output format. Due to the transformation to interpretable data, implementing Key Performance Indicators becomes important. There are several modules available for advanced KPI calculations.
Minerva ETL applies the following tasks in this phase (some optional and depending on use case);
- Validation, cleansing, authentication, filtering, and de-duplication of the raw data
- Removal, pseudonymization, encryption of data
- Raw data advanced KPI calculations
- Raw data translations to compare multi-vendor data sources
- Data quality audits
- Formatting and preparing the data for the Loading phase
The transformation phase happens at game-changing speeds. If you want to see what this means for your company, make sure to request a demo.
The last phase of Minerva is the data loading part. Minerva is moving the transformed data to the target data warehouse.
It then loads all the data changes batch-driven into the target warehouse, a fully automated process. Schedule the loading or deliver loading continuously at real-time speeds.
Apply scheduled data loading in use-cases where the target data warehouse has specific off-hours of lower traffic on the data source systems.
Continuous data loading is helpful in cases where network monitoring and optimization is a 24/7 process, allowing the end-users to instantly access data.
Feel free to submit your use case to see what works best for your network.
Not convinced yet?
Send us sample data to process and be surprised!