ABSTRACT Stream Data Mining is a new emerging topic in the field of research. Today, there are number of application that generate Massive amount of stream data. Examples of such kind of systems are Sensor networks, Real time surveillance systems, telecommunication systems. Hence there is requirement of intelligent processing of such type of data that would help in proper analysis and use of this data in other task even. Mining stream data is concerned with extracting knowledge structures represented in models and patterns in non stopping streams of information [1]. Such massive data are handled with software such as MOA (Massive Online Analysis) or other open sources like Data Miner. In this paper we present some theoretical aspects of stream data mining and certain experimental results obtained on that basis with the use of MOA.