The IFPUG Functional Sizing Standards Committee (FSSC) is pleased to announce the availability of their recently published white paper: Applying Function Point Analysis to Data Warehouse Analytics Systems. This paper, co-authored by Roopali Thapar, E. Jay Fischer and Peter Thomas, builds on the IFPUG paper: Function Points and Counting Enterprise Data Warehouses, published in 2007.
Since the earlier paper was published, the rising popularity of data analytics and Big Data has driven an evolution in Data Warehouse technology. Users request more complex business analytics and reporting requirements, along with a growing need to simplify the information access within the Data Warehouses. As a result, new “user friendly” components have evolved for pulling data from Data Warehouses, irrespective of underlying data structures. One such component is the Universe. The Universe is an abstraction created for the user to simplify access to the information required or for downstream consumption, without needing to know the details of the database implementations. Thus, the Universe facilitates an integrated query, reporting and analysis solution for business users via the abstraction layer for the application data that represents business functions.
Applying Function Point Analysis to Data Warehouse Analytics Systems focuses on sizing the Universe creation and its maintenance in this environment. To set the stage, this paper first presents background material describing data analytics concepts, components and terminology. The paper also helps to understand the impacts on the sizing of reporting requirements where Universe is present in the Data Warehouse environment. This paper acts as a reference for those complex scenarios in Business Analytics, which are not covered in prior IFPUG white paper on Data Warehousing.
You can obtain a copy by navigating to the IFPUG Member Services Area and logging in, then selecting the IFPUG Online Store and then clicking on the title of the Featured Product “Applying Function Point Analysis to Data Warehouse Analytics Systems”. Add it to your cart, then continue on to Checkout, and follow the directions to make a purchase. To download your purchase, follow these directions.