Data Integration

Modernization projects require deep understanding of data integration technologies. See how we can help you get the best performance on the platform you are currently using or migrate to cloud-based solutions.

Getting control of your data integration solution

Every organization uses data integration tools to take data from different sources for standard business processes and analysis. Many organizations use the most popular tool on the planet – Microsoft Excel. At some point, they need to operationalize the process using tools included in their database engine like SQL Server Integration Services or dedicated solutions such as Talend and Informatica. Organizations may extend their tools with Master Data Management and Data Quality Services as part of an Enterprise Information System.

Our database and application modernization experience make ABCloudZ unique, because we have experience using most of the commercially available and open source data integration platforms. Here are our featured platforms for data integration solutions:

Why data integration services matter?

Our team has developed experience with a wide variety of data integration tools through our database migration services. Often our customers have asked our team to migrate their services to a different platform. Other times, we update integration solutions to use the new destination. With new scenarios of moving data from on-premises to cloud platforms, integration is rapidly becoming a core competency for our customers.

Here are the key services where data integration plays a critical role in making sure that data is accurate and available for all forms of data analytics without disrupting the performance of the operational data stores.

Other supported data integration platforms

In addition to the tools available from Microsoft, Amazon, and Google, we have experts supporting the following specialized tools.

Unlocking your data with ABCloudZ

Across all of these solutions, we consider two design principles to help make our technology choices.

  1. Put the processing as close to the data as possible. Disk and Network latency will always exist, so we tailor our designs to take latency into account.
  2. Parallelize tasks where it makes sense. For large data transfers, it’s always better to use parallel tasks for extracting and loading data. Features like SQL Server Polybase are a great step forward, but can’t connect to traditional database engines for parallel execution. So, we always look for off-the-shelf solutions and our in-house tools and products to manage parallel task execution.

Check out what we can do to improve your solution.

Bringing data together

While data integration plays a critical role in bringing data together, knowing the backend database for the target and source systems is essential. Here are examples of data technologies that our team can help your organization get the most out of your technology investments.