Data Warehouse
Mission
The Data Warehouse is home to the University’s historical data about our institution, also known as the Decision Support Database (DSD). The DSD Data Warehouse is home to data tables that are “frozen” or extracted from other UA information systems at specific points in time. Our mission is to provide the UA community with the consistent, static data tables which serve as the foundation for the various needs of institutional reporting.
UA DATA WAREHOUSE MODERNIZATION INITIATIVE
Welcome to an overview of the ETL, Data Warehouse, and Data Catalog Modernization Initiative.
The RFP launched in September of 2023 and is seeking a technology solution that will facilitate visibility and collaborative curation of our disparate data assets - beginning first and foremost with our Data Warehouse.
People and departments across the University make decisions every day that can impact the student experience. Each of these decisions, big and small, deserves trustworthy and timely data.
- DATA IN - Every aspect of the student experience is reflected in our data like a
mirror, moving and changing as they move through our system. This “live” data has
many names, production data, operational data, transactional data – reflecting real
time interactions and changes.
- DATA OUT - At the other end of the data spectrum, we also have reporting requirements. Some are imposed on us by outside entities such as federal and state offices (IPEDS). Other data we’ve deemed as critical to support the decisions we make every day – all with the goal to improve the student experience. This can be referred to as analytical data and it resembles a picture, a snapshot of the data is frozen and saved on a schedule to provide stable reference points.
Have you ever…
- Used a report that pulls data from DSDMGR?
- Run a report from Qmenu or QAdhoc?
- Pulled data from a “freeze” table?
- Used TOAD to query something in RPTP (now RPTP On-Prem)?
- Visited one or more of the Universities IR Enrollment Dashboards?
- Read the UA in Review report?
Then you are a Data Warehouse user!
As the IRSSC and the new Data Warehousing team was formed, we began to examine our assets and identify areas of need as compared to modern data warehousing standards and industry best practices.
- We lack a platform to view and manage data across multiple data systems, content area silos, and varying campus business needs. Frequently resulting in multiple answers to the same data question.
- Increasing demands for trustworthy data and timely insights creates a strain on reporting resources to meet the demands. (80/20 rule)
- Data Warehouse created circa 1999. The same tools & methods are used today and are unsustainable as they reach end-of-life.
- Quality of data unknown, loss of institutional knowledge over time regarding data meaning and changes in data use.
- Authority and responsibility for data unclear.
Imagine this work multiplied across our system, all the people and departments grappling with data to perform their work and to drive decisions.
Most data warehousing products available today offer additional capabilities that extend beyond the scope or purview of the UA Data Warehouse. Such as an enterprise-wide data lake house, fabric, or mesh. Or a data governance platform intended for the larger University community to collaborate in the management of our data assets.
The three primary capabilities sought are:
- A data Extraction, Transformation, and Loading (ETL) tool to help bring data from various sources into one location.
- A Data Warehouse management tool to ensure robust security, access, process automations, and enhance data quality.
- A Data Catalog to capture both shared and unique data definitions and the various critical reporting metrics across UA.
- The green boxes highlight areas where new ETL, Data Warehousing, and Data Catalog tools could help the University advance in the strategic management of our data assets.
- This chart also brings to light other milestones that could advance our data governance maturity level. These lie outside the scope of the project and the beyond the purview of the Data Warehouse.
- Potential usefulness extends beyond “just IR”. Data Catalogs and accompanying platforms for self-service analytics could be used by everyone in the UA system, customizable to their distinctive data needs.
- New tools will allow us to take measure of our data quality (even if it’s terrible) and allow us to set micro-goals or apply logic or cleansing rules to improve the quality of our data.
- Being able to find our data, know its quality, and understand its context will help increase the trustworthiness of our data – for the benefit of everyone, including our students.
- Modern data tools can connect with a wide variety of data sources to provide a data catalog unified across not only data “silos” but disparate data systems as well.
For more information contact UA-IR-DataWarehouse-Team@alaska.edu
PRINTABLE PDF VERSION - UA DATA WAREHOUSE MODERNIZATION INITIATIVE
Printable PDF Version
Regular DSD Table Refreshes
Daily Updates
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Early Semester Reports
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Human Resources Tables
Monthly Updates
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Degrees Earned Tables
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BOR Tables
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Cycle/Cycap/TVEP tables
Annual Updates
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IPEDS Data Tables
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NSC Data Tables
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Finance FTV Tables
