Eight enterprise data management requirements that must be addressed in order to get maximum value from your Big Data technology investments.
Storage and Data Formats
Unlike relational databases, Big Data storage does not usually dictate a data storage format. That is, Big Data storage supports arbitrary data formats that are understood by the applications that use the data. For example, data may be stored in CSV, RCFile, ORC or Parquet, to name a few. In addition, various compression techniques -- such as GZip, LZO, and Snappy -- can be applied to data files to improve space and network bandwidth utilization. This makes data lake storage much more flexible. Multiple formats and compression techniques can be used in the same data lake to best support specific data and query requirements.