ETL Maturity Model for Data Warehouse Systems: A CMMI Compliant燜ramework

Shahzada Khurram · Salman Naseer · Ahmed Tawhid Ahmed Soliman · Akber Abid Gardezi · Jin‐Ghoo Choi

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Big Data and Business Intelligence Data Quality and Management Knowledge Management and Technology

Abstract

The effectiveness of the Business Intelligence (BI) system mainly depends on the quality of knowledge it produces. The decision-making process is hindered, and the user’s trust is lost, if the knowledge offered is undesired or of poor quality. A Data Warehouse (DW) is a huge collection of data gathered from many sources and an important part of any BI solution to assist management in making better decisions. The Extract, Transform, and Load (ETL) process is the backbone of a DW system, and it is responsible for moving data from source systems into the DW system. The more mature the ETL process the more reliable the DW system. In this paper, we propose the ETL Maturity Model (EMM) that assists organizations in achieving a high-quality ETL system and thereby enhancing the quality of knowledge produced. The EMM is made up of five levels of maturity i.e., Chaotic, Acceptable, Stable, Efficient and Reliable. Each level of maturity contains Key Process Areas (KPAs) that have been endorsed by industry experts and include all critical features of a good ETL system. Quality Objectives (QOs) are defined procedures that, when implemented, resulted in a high-quality ETL process. Each KPA has its own set of QOs, the execution of which meets the requirements of that KPA. Multiple brainstorming sessions with relevant industry experts helped to enhance the model. EMM was deployed in two key projects utilizing multiple case studies to supplement the validation process and support our claim. This model can assist organizations in improving their current ETL process and transforming it into a more mature ETL system. This model can also provide high-quality information to assist users in making better decisions and gaining their trust.

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2010Design Science Research in Information Systems 1996The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling 2004The Data Warehouse ETL Toolkit: Practical Techniques for Extracting, Cleaning, Conforming, and Delivering Data 2006Metrics for data warehouse conceptual models understandability 2011A Model of Data Warehousing Process Maturity 2010Business Intelligence Maturity Models: An Overview 2006Data Warehousing Process Maturity: An Exploratory Study of Factors Influencing User Perceptions 2008IQM3: Information Quality Management Maturity Model

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