Overview
At RS-5, we are proud to present our comprehensive Data Analytics Framework for Higher Education that combines the power of connectors and apps to revolutionize the way you handle and analyze your data. Our framework provides a robust and scalable solution for organizations seeking to unlock the full potential of their data assets.
Our Data Warehouse Framework comes equipped with a wide range of pre-built connectors that enable effortless integration with diverse data sources. Whether you need to extract data from databases, cloud services, APIs, or even legacy systems, our connectors provide a standardized interface for smooth communication.
In addition to our powerful connectors, our Data Analytics Framework is built to support customizable apps that extend the functionality of the core system. These apps provide specialized features, services, and customizations tailored to your specific needs.
Workbench components:
• Extraction, Transformation and Load (ETL) workflow
The ETL workflow is dynamically created at run time based on meta-data for data acquisition. ODS population, data history, transformations, population of dimensional models and logging. The ETL workflow manages process concurrency and index management based on meta-data to maximize ETL performance.
• Data Extraction Engine and Operational Data Store (ODS)
Integrate disparate sources of information into a single authoritative repository for reporting and analytics. Our extraction engine supports data acquisition from on premise and cloud applications including direct database connections, raw symmetric and asymmetric data files and ability to call application API’s. The extract engine loads the raw data into the Operational Data Store (ODS) where data stored in native form. The ODS also supports limited conforming of normalized data and creating value added data elements to enhance the ability of uses data interact with ODS data. e.g. creating common data keys across data sources, standardizing varying source data formats into common structure.
• Data History Compiler
Many applications today lack effective dating for transaction changes which presents challenges to producing reliable and consistent historical comparative reporting. Using the Data History compiler, just add the table to metadata and the transaction change history will be created for the table. This enable unlimited historical point in time analysis and reporting comparatives for any data source.
• Dimensional Data Model Framework
ETL process to transform and load data into dimensional data models base on meta data to provide descriptive analytics. Dimensional data models are excellent choice for modeling a business process like admission or enrollment management. These models focus on the business process and not specific source application and are often source from multiple applications like a CRM and SIS system.
• Advanced modeling
Advanced modeling goes beyond descriptive analytics to provide advanced metrics, ranking, correlation analyses and predictive analytics. The Workbench supports the ETL and advanced database strategies to easily implement more advanced analytics. Construct multi-dimensional cubes or reports that support interactive, visual analysis of data. Develop early warning systems that alert users when a defined tolerance are exceeded enabling proactive intervention.
• Administration and Logging
RS-5 can provide subject area data model templates that are based on our over 200 implementations in Higher for Admissions, Enrollment Management, Finance, Human Resources and Advancement
Data Warehouse starter kit include data warehouse workbench, I subject area template, 3 reports templates and our development and support time.