Data Integration Services & Consulting

Modern data integration technology and techniques allow you to easily clean, transform, and view all of your data in a single location for unified, reliable, and effective analysis.

Cloud-based data architectures provide companies with flexibility, scalability, and simplified infrastructure management. However, these approaches often result in siloed data, making analytics difficult.

Our data integration services combine modern data integration technologies and techniques with proven experience so you can perform analysis across all your sources, regardless of form, function, or location.

Our data integration services can help you

  • Integrate and extract large volumes of disparate data
  • Transform structured and semi-structured enterprise data into easily analyzed formats
  • Track data lineage and apply data tests to confirm assumptions
  • Ensure data is clean, consistent, and available in real-time
  • Load data into cloud-based data warehouses, data lakes, and BI Tools
  • Access the data needed to accelerate AI/ML projects
  • Simplify data management operations and automate administrative tasks
  • Modernize your data architecture

Data Integration Techniques

Our data integration consulting services involve a variety of integration techniques to automate the process of connecting disparate data from across the enterprise.

Prebuilt ELT and ETL Frameworks

We’ve created reusable frameworks for ELT and ETL paradigms which allow us to quickly achieve consistent naming conventions, auditable processes, and easily-understood lineage for the ingestion pipeline.

Data Transformation

Taking advantage of modern tools on the market, we standardize transformation processes so that they can be easily understood at a high level. We believe the most important part of transformation isn’t transformation itself; it’s creating a process that can be replicated, interrupted, iterated on, and understood.

Dynamic Data Structures

As part of our data integration consulting best practices, our processes will first try to dynamically adjust and compensate for any structural changes in the data. If this cannot be achieved dynamically, our processes will highlight the culprits that could cause data integration to fail (and alert you to the situation!), allowing you to quickly remedy the problem.

Data Cleansing

Data scientists and analysts no longer have to spend the majority of their time cleansing data for analysis. In a modern data stack, data cleansing is handled programmatically within the stack so that data scientists and analysts can spend their time solving complex business problems and uncovering opportunities.

Integration Prioritization

There are costs associated with the movement, transformation, and integration of big data; data storage; and the upfront and ongoing costs of data stewardship. For these reasons, you may not actually want to integrate all of your data. We have best practices and tools that help prioritize which data to integrate – and which data to NOT integrate – so you can optimize your data integration processes and reduce cost.

Technologies We Work With

With data integration software and API integration tools evolving at a rapid pace, our consultants will ensure you take advantage of the best technology to ingest and transform your data.