Improving Compression Efficiency of Data Warehouse

نویسندگان

  • Mohd. Fraz
  • Ajay Indian
  • Hina Saxena
  • Saurabh Verma
چکیده

Data compression has a paramount effect on Data warehouse for reducing data size and improving query processing. Distinct compression techniques are feasible at different levels, each of types either give good compression ratio or suitable for query processing. This paper focuses on applying lossless and lossy compression techniques on relational databases. The proposed technique is used at attribute level on Data warehouse by applying lossless compression on three types of attributes (string, integer, and float) and lossy compression on image attribute.

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تاریخ انتشار 2013