  Next Generation Sequencing (NGS) technology has resulted in massive amounts
of proteomics and genomics data. This data is of no use if it is not properly
analyzed. ETL (Extraction, Transformation, Loading) is an important step in
designing data analytics applications. ETL requires proper understanding of
features of data. Data format plays a key role in understanding of data,
representation of data, space required to store data, data I/O during
processing of data, intermediate results of processing, in-memory analysis of
data and overall time required to process data. Different data mining and
machine learning algorithms require input data in specific types and formats.
This paper explores the data formats used by different tools and algorithms and
also presents modern data formats that are used on Big Data Platform. It will
help researchers and developers in choosing appropriate data format to be used
for a particular tool or algorithm.
