Digital Dashboard for Higher Education (Part 5): Data Warehouse
Data warehouse and Business Intelligence go hand-in-hand with the design requirements of a digital dashboard for Higher Education. The data warehouse provides a platform to store campus-wide information from multiple operational datamarts. In this entry, we’ll discuss the role of the data warehouse in developing the digital dashboard for Higher Education. In our next entry, we’ll cover how to improve performance using Business Intelligence.
Executives at Higher Education institutions are increasingly in need of timely and accurate information to make critical business decisions, assess risks against benchmarks and respond quickly to market changes. Like growing commercial industries, Higher Education is in need of accurate, timely and relevant information on which to base decisions, not only for long-term planning, but also to address day-to-day developments. In order to store vast amounts of historical data electronically and to facilitate reporting and analysis work, Higher Education needs to develop the proper data warehousing architecture.
Business Intelligence applications rely on Data Warehouses, as they function as database repositories designed to support a company’s decision-making process. Information populated on digital dashboards are extracted and transformed from Data Warehouses. For bloggers, a digital dashboard is an aggregation of different types of information accessible from a single Web page.
Data warehouses are assuming a more strategic role in making these business decisions, addressing these three challenges:
1. Delivering near real-time data
2. Integrating the applications that make the best use of the data
3. Providing transparent access to systems that contain business-critical data
Solving these challenges typically requires retrieving and analyzing data; extracting, transforming and loading data; and managing the elements of the data dictionary. Data warehouses are optimized for speed of data retrieval, so even for the largest databases, retrieval speed is not a major concern. Multi-dimensional modeling and denormalized data are key factors that contribute to the fast and efficient performance of a data warehouse that directly expedites the data population on a digital dashboard.
Again, we will cover the Business Intelligence end of the Data Warehouse/Business Intelligence equation in our next blog entry.
Tags: BI, business intelligence, Data Warehousing, digital dashboard, Higher Education, Key Performance Indicators, KPI, universities, university