ETL and Big Data Management – building enterprise data warehouse


  • Data conversion and unification of compute cycles to take advantages of cloud based data warehouse.
  • Effectively manage data extraction from existing source systems and applications, implement complex transformations and apply data warehouse modeling concepts and optimized operations for delivering data into Amazon Redshift.
  • Minimize inconsistent reports and provide the capability for data sharing with high accuracy and efficient control mechanisms.
  • Shorten the time needed, optimize ETL strategy and warehouse architecture and improve business operations while keeping lower costs.
  • Overcome the common challenges like lack of integrity, scalability and big data management.


  • Interworks delivered cost effective and robust solution that quickly ingest, prepare and deliver big data in Amazon Redshift, consisted of different submodules to more effectively manage the entire lifecycle.
  • Our solution is composed of optimized ETL pipelines implemented using SnapLogic integration platform. Common functionalities include complex query logic applicable for all integrated data types from heterogeneous systems, consuming data warehouse dimensional/fact model with highly optimized bulk operations applied.
  • Common methods such as error handling, logging and notifications were extracted in reusable pipelines to be easily-shared across solution.
  • We constructed control mechanisms for tracking complex interactions, monitoring and effectively managing dependent processes.
  • Automatically adjusted load balanced operations allow spreading the processes for data manipulation into optimal number of parallel threads providing best available performance.
  • The solution includes common SnapLogic design patterns and company’s best software practices based on our deep technical expertise and data warehouse provisioning practice.

Benefits and Results

  • Data from multiple sources is integrated in the warehouse providing a single view of business entities like customers, products, employees, locations and other assets. Unified data access increases the value of data through efficient visualization.
  • Real-time information delivery enables a number of high-value business practices and makes data available for dashboards and other types of operational or management reports, represented using a different set of BI tools.
  • Data synchronization processes tend to integrate data frequently depending on the needs that increases data currency and allows employees to focus their time on analyses and understanding the data instead of compiling and constructing information.
  • Ability to automate hourly, daily, weekly reports and keep entities updated based on their performance against key metrics and KPIs.
  • Gained improvement of precisely calculated time savings in thousands of hours per month.