Special emphasis needs to be given when building Big Data Models. It is so because the Big Data itself is less predictable when compared to the other traditional kind of data. It is a little bit complex process as it involves reorganizing and rearranging the business data by the business processes. To support the business objectives, the data models need to be designed to have logical inter-relationships among the various business data. Then these logical designs need to be translated into the corresponding physical models. Big Data is significantly different than the traditional data, the old data modelling techniques do no longer apply to Big Data. So you are required to apply different approaches for modelling Big Data. The data interfaces should be designed to incorporate elasticity and openness due to the unpredictable nature of the Big Data to accommodate future changes. Here the focus should not be on a schema but on designing a system. We should also take into consideration the various Big Data modeling tools out there. Not all the Big Data present there should be considered for modeling. Only the data appropriate to your business concerns should be selected to build models around.