Galaxy Data Warehouse – An Enterprise Wide Data Warehouse

TSG’s Galaxy Data Warehouse is a platform for containing all of an organization’s data in one centralized place in a normalized or de-normalized form for deployment to users. It enables organizations to extract, transform, and load data across various sources to create data to support analysis and decision-making that is consistent, detailed, aggregated, summarized, and accurate.

Residing on a relational database management system (RDBMS), Galaxy contains data management and easy data access tools. IT is primarily a MS SQL -based environment with a built-in multitasking capability, consisting of data warehouse loading, data transformation, data rationalization, meta data tools, a data reporting engine, and an intelligent file transfer tool.

Fully functional and ready-to-use, the Galaxy Data Warehouse includes options for an administrative and financial repository, clinical repository, ambulatory repository, and claims and encounters repository. It can also provide a mechanism for MPI across multiple systems. Galaxy comes with a built-in integration engine without the need for any other interfaces or support from MEDITECH or other systems.

Certified MU Modules
Core Objectives 9: Patient list creation

  • Generate lists of patients by specific conditions to use for quality improvement, reduction of disparities, research, or outreach
  • Enable a user to electronically select, sort, access, and create lists of patients according to, at a minimum, the data elements included in:
    (i) Problem list; (ii) Medication list; (iii) Demographics; and (iv) Laboratory tests and values/results

ETL – The Three Functional Components

Our Galaxy Data Warehouse lets you create ETL processes that are reusable, easily modified, and include embedded data quality processing services. It is made up of three very different functional areas, each of which can be customized to meet the needs of your business.

  • Extraction: This component handles acquisition of data from legacy systems and outside sources. There the data is identified, copied, formatted, and prepared for loading into the warehouse.
  • Transformation: This component stores data so that different data mining, executive information, and decision support systems can make use of it effectively. Transformation can run on any platform with any data source. The user interface is powerful, yet easy-to-use, supporting collaboration and the reuse of processes and common metadata.
  • Loading: This component of the warehouse is the access area. Various end-user PCs and workstations draw data from the warehouse with the help of multidimensional analysis products, data discovery tools, and analysis tools. You can easily refresh, append, and update data during loading.

 Benefits

  • Removes the constraints of a proprietary database
  • Centralizes all legacy and disparate data sources
  • Serves as the basis for custom applications, interfaces and web applications
  • Removes analysis off of your OLTP system, allowing you to gain substantial response/turnaround time both on your OLTP system and in the analysis process
  • Serves as the basis for an archival system, allowing you to purge your OLTP system more frequently and thereby avoiding expensive hardware upgrades
  • Ability to easily design, create, and load OLAP cubes
  • Metadata can be captured and documented throughout the data integration and transformation processes and is available for immediate reuse