Abstract   Nowadays,  the  vital  parts  of  the  business  programs   are  the  data  warehouses  and  the  data  mining  techni ques.  Especially  these  are  vital  in  the  Radio  Frequency  I dentification  (RFID)  application  which  brings  a  rev olution  in  business  programs.  Manufacturing,  the  logistics  distribution   and  various  stages  of  supply  chains,  retail  store and  quality  management  applications are involved in the RFID technology in  business. A large volume of temporal and spatial data is generated by the  ubiquitous  computing  and  sensor  networks  of  RFID  an d  these  are  often  generated  with  noises  and  duplicates.  The  noises  and  duplicates  in  the  RFID  data  declare  the  need  of  an  effective  data  warehousing  system.  The  warehousing  system  has  the  responsibility  to  provide  proper  data  cleaning  tech nique  to  clean  the  dirty  data  which  occurs  in  the  a pplications.  Also,  the  cleaned data has to be transformed and to be loaded  properly so that they can be stored in the database with minimum space  requirements.  In  this  paper,  we  propose  a  novel  dat a  cleaning,  transformation  and  loading  technique  wh ich  makes  the  data  warehousing system employed for any RFID applicatio ns more effective. The chosen RFID application is tracking of goods in  warehouses  using  RFID  tags and  readers,  one  of  the  significant  RFID  applications.  The data  cleaning  is  performed  based  on  the  probability  of  each  RFID  tag’s  response  and  the   window  size  which  is  made  adaptive.  The  window  siz e  changes  on  the  basis of the occurrence of the dirty data and hence  the cleaning is more effective. The purified data is transformed in a special  structure  in  such  a  way  that  the  ware  house  can  hav e  only  the  tag  IDs  which  are  under  transaction  and the  time  of  interrogation in the size of bits. The transformed  data are loaded into the warehouse using the propos ed loading technique in a  dedicated tabular format.    

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