Cassandra is a NoSQL(Not only Structured Query Language) database which serves large amount of data with high availability .Cassandra data storage dimensioning also known as Cassandra capacity planning refers to predicting the amount of disk storage required when a particular product is deployed using Cassandra. This is an important phase in any product development lifecycle involving Cassandra data storage system. The capacity planning is based on many factors which are classified as Cassandra specific and Product specific.This study is to identify the different Cassandra specific and product specific factors affecting the disk space in Cassandra data storage system. Based on these factors a model is to be built which would predict the disk storage for Ericsson’s voucher system.A case-study is conducted on Ericsson’s voucher system and its Cassandra cluster. Interviews were conducted on different Cassandra users within Ericsson R&D to know their opinion on capacity planning approaches and factors affecting disk space for Cassandra. Responses from the interviews were transcribed and analyzed using grounded theory.A total of 9 Cassandra specific factors and 3 product specific factors are identified and documented. Using these 12 factors a model was built. This model was used in predicting the disk space required for voucher system’s Cassandra.The factors affecting disk space for deploying Cassandra are now exhaustively identified. This makes the capacity planning process more efficient. Using these factors the Voucher system’s disk space for deployment is predicted successfully.