Extract and transform data
with precision.

Merge systems, trace any anomaly, or derive a birds-eye view to forming critical decisions.
Data migration is a very vital decision an enterprise has to make. It means to move data permanently from one storage to another storage. It has to be planned very precisely. There are three major processes involved in migration a) collection/extraction of data b) transformation of data 3) Loading data at the destination.

Few Best Practices of DevOps

Monitoring and

Since the quantity of data is growing and the quality of data is also changing, it is becoming difficult to manage this data with traditional systems. It also becomes difficult to use this data for the strategic planning of the enterprise further. So, modern data architecture benefits business to make further analysis and also manage its growing size.

Analyze and
monitor data

Due to traditional data architecture, its impossible to process bulk data and get the desired reports. Modern architectures make it possible to get data logged and analyzed. Data monitoring and automation can also be implemented if data migration is done on cloud solutions. Processing time its reduced and real-time monitoring is possible.


The world is going towards the microservices approach, and this has opened up newer and better options for business solutions. While adopting new services/products or while building a modern, fully customized application using new technologies, both approaches require to migrate its existing data to the news source. This migration ensures data integrity in the new system.

Mergers and

Mergers and acquisitions are very common growth options for an Enterprise. It opens up the scope of growth, market coverage, and eliminates competition. While this merger and acquisition generate the opportunity of data migration activity for checking overall data integrity and getting combined analysis.

Our data migration process

• Identification of the objective and scope
• Understand the current data source and analyze all the details like data format and data type.
• Pre-migration testing of data
• Extracting and classification scripts on staging
• Real-time migration testing
• Post-migration testing and validation of data on stage
• Implementing in a production environment.
• Build a secure and robust data migration process.


Every data migration is different depending on data sources and their nature. This is a high-level diagram depicting on-prem data migration architecture.

Adopt smarter softwares and systems. Opportunity to get aligned with new technologies as well as new platforms that can leverage better analytics.

Helps in resolving anomalies and errors in the current system Data automation and analysis can help in the eradication of any current systems.

Facilitate custom reports over the data warehouse Open the doors to any custom reports which can be fetched from new and modern data storage.

Facilitate in acquisition and mergers Make overall analysis easy after acquisition and mergers.