ETL
We use the ETL integration method to extract data from various sources and transform it into a consistent structure. Then we load data into centralized databases, and ensure consistency, accuracy and reliable reporting for your business intelligence needs.
From extracting data to transforming it into the target scheme and load into the database, everything is possible via ETL.
- Suitable for: Structured data and batch processing, like financial reporting systems and scheduled sales.
ELT
Our experts also implement the ELT pipelines to load raw data quickly into modern platforms. Then we apply transformations, and enable the advanced analytics, faster ingestion and scalable processing for real-time USA applications.
- Suitable for: It is suitable for Real-time and big data use cases like live personalization, ecommerce and OMS.
Data Virtualization
The Database Integration Developer at Melonleaf applies data virtualization and creates unified views on multiple databases. It allows users to get real-time integrated data without moving or duplicating the datasets. It provides a virtual layer to help users to get a single view of multiple data sources, and reduce need for replication.
- Suitable for: To access external systems and distributed internal systems that do not integrate physically.
Data Propagation
We are also expertise in data propagation integration methods and detecting and transit incremental data changes only. It integrates the real-time synchronization across systems and reduces bandwidth usage, latency and processing overhead. It is used to capture the data changes and share it across systems continuously.
- Suitable for: To maintain real-time consistency in dynamic datasets like payment systems and banking platforms.