Data Integration

Data Integration by Stretch Qonnect

More data. More sources. Faster. With less maintenance.

In the chase to gain competitive advantages with analytics, companies are adding more and more new data sources, all of which need to deliver data quickly with minimal manual interaction. This can quickly become unfeasible without a holistic approach to data integration, which is where Stretch Qonnect can help you.

Many organizations fall into the trap of solving analytics and data integration challenges ad-hoc, which might save time on the individual project, but at great expense to the organization as a whole. Time and resources are wasted on repeating tasks for new projects and on doing processes manually that could easily be automated.

Stretch Qonnect helps you implement a holistic approach to data integration and build a modern data integration infrastructure that saves you time and money you can spend on more productive endeavors.

We work with cutting-edge technologies from data streaming, data warehouse automation, data lake creation, and data cataloging to help you succeed with data integration.

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Modern Data Integration

In today’s hyper-competitive business climate, real-time insights are critical. Users need robust data integration and agile analytics solutions to make decisions fast. Unlike traditional batch data movement and ETL scripting, which are slow, inflexible and labor-intensive, we work with automated data integration platforms for creating data streams from transactional systems.

Efficiently move data to applications, warehouses, and lakes — on-premise and in the cloud — and make your data immediately available via a catalog marketplace experience.

Here are some of the things Stretch Qonnect can help you succeed with:

CDC Streaming

Get started with Change Data Capture (CDC) to instantly move changes from source systems to your target. With modern CDC streaming solutions, you can completely automate the end-to-end data replication, allowing data engineers to easily set up and monitor data pipelines.

Data Warehouse Automation

Doing you all ETL code manually can easily be a thing of the past with modern data warehouse automation tools. Upwards of 80% of the manual tasks associated with creating a modern data warehouse can be automated to reduce the time and costs of building and maintaining enterprise data warehouses.

Data Lake Creation

Efficiently move your data to data lakes and automatically generate the necessary ELT code in Apache Spark to standardize and combine change streams into a single analytics-ready data lake.

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