Utilizing AWS to Build a Data Warehouse and Analytics Capabilities

Challenge

A leading nonprofit serving higher education needed a data warehouse and analytic capabilities to support industry research and internal business operations. Our client was looking for a cost-effective, extensible and scalable solution that could grow with the business. Specifically, the organization needed to address:
  • The lack of software, infrastructure, and tools to support data warehousing and analytic needs
  • Insufficient staff to manually deliver on internal and external requests for research and operational reporting metrics
  • Disparate systems and sources of data, making it time consuming to retrieve the necessary data required to satisfy the needs of internal and external constituents
  • A desire to shift toward a data-driven mindset throughout the organization to measure performance and drive decisions

Solution

Developed a strategy and plan to build an initial version of the data warehouse and analytics capability that included:
  • Interviewing internal and external constituents to understand their needs and the questions that could be answered by available data
  • Analyzing and prioritizing constituent needs to provide quick wins and a roadmap for analytic capabilities
  • Architecting, securing, and implementing AWS environments and services to provide a scalable and extensible foundation for the data warehouse and analytics ecosystem
  • Executing an agile process to iteratively ingest data sources and visualize the data utilizing AWS QuickSight
  • Providing ongoing change management and training to ensure adoption and maintainability of the solution
  • Engaging executives, stakeholders, and constituents throughout the project to ensure delivery of the highest value needs

Outcome

A cost-effective, secure, scalable, and extensible AWS-based solution that:
  • Centralized core client data and external data sets in a secure and economic manner
  • Automated data pipelines to ingest data updates to reduce ongoing operations and maintenance needs while meeting GDPR and CCPA requirements
  • Leveraged AWS AI services to extract raw text from PDF files to address higher ed analytics use cases
  • Simplified access to organizational KPIs through numerous visualizations that quickly gauge performance in near real time
  • Significantly reduced the amount of time required to produce standard reports and dashboards through self-service, on-demand reporting capabilities, versus former manual processes that took up to two weeks
Published April 25, 2021