01

Data integration

Enhances accuracy and trust by establishing a reliable, single source of accurate, governed data, ensuring confidence in the "one source of truth".

02

Data-driven & collaborative

Data integration transforms raw data, fostering analysis and interdepartmental collaboration, understanding the impact of actions.

03

Increased efficiency

By minimizing manual data gathering and preparation, along with custom report building, analyst, development, and IT teams can refocus on strategic initiatives.

What we do

We will concentrate on
four main use cases.

Data Ingestion

Data Ingestion moves data from various sources to a storage destination, preparing it for analytics through real-time or batch streaming and data cleaning.

Data Replication

Copies and synchronizes data between systems, ensuring backup and consistency, occurring in bulk, scheduled batches, or real-time across data centers or the cloud.

Data Automation

Speeds up analytics-ready data availability by automating the entire data warehouse lifecycle, including modeling, ingestion, data marts, and governance.

Big data integration

Ensures comprehensive business views for analytics tools through intelligent pipelines, prioritizing scalability, performance, and real-time data quality.

Data integration (DI)

Data integration (DI) consolidates data from multiple sources into a central repository, primarily to bolster BI and analytics capabilities. While contemporary DI tools and methods can manage real-time operational data, historically, the focus was on transferring static, relational data among data warehouses.






Application Integration

Application integration (API) synchronizes data between separate applications to meet operational needs like aligning HR and finance systems, ensuring consistency across datasets. SaaS application automation tools facilitate efficient creation and maintenance of native API integrations.

Streaming Change Data Capture

Discover the benefits of modernizing your data and analytics environment with scalable, efficient, and real-time data replication, without disrupting production systems.