There are several anonymizing techniques like abstraction, containerization for isolation preserving small data publishing. The abstraction loses amount of information for high spatial data. Containerization does not avoid enrollment acknowledgment and does not give clear separation between aspects. The authors are presenting a technique called slicing which partitions the data both horizontally and vertically. They also show that slicing conserves better data service than abstraction and can be used for enrollment acknowledgment conservation. One more important advantage of slicing is that it can handle high-spatial data.