Data Warehousing

Data Warehousing systems integrate multiple data sources to enable advanced analytics through alternative data collections and views, improve the performance of complex queries without impacting operational systems, maintain comprehensive data histories of source systems, and increase data quality.

Unique Design Decisions

Loblolly understands the design decisions that are generally unique to data warehousing/business intelligence systems. For Business Intelligence projects, visualization of requirements is particularly important to show the potential of a given set of BI tools and data. Visualization allows users to see interactions between data sources, timing constraints, and possibilities not available in most static reporting environments. The identification of data collections required to address the business requirements for any data warehouse project is key to its success. Once the data collections have been designed, the system of record for all data elements is identified along with the establishment of the order of precedence for those source systems. Additional requirements regarding data security and data sharing are also collected and incorporated into the overall design.


Loblolly leverages our expertise in Enterprise Information Management (EIM) to develop enterprise-wide data warehouse strategies to integrate data across state agencies to improve the delivery of services, evaluate program effectiveness, assure that services are delivered in a cost effective manner, and help forecast future needs.

Snowflake Partner