%0 Journal Article %1 Sarika_2015 %A Prakash, Kale Sarika %A Prathap, P.M. Joe %D 2015 %I Auricle Technologies, Pvt., Ltd. %J International Journal on Recent and Innovation Trends in Computing and Communication %K Data Iceberg Iceberg(IB) Online Processing(OLAP) Processing(OLTP) Transaction analytical bitmap index(BI)Online queries query(IBQ) warehouse(DW) %N 2 %P 680--683 %R 10.17762/ijritcc2321-8169.150253 %T Bitmap indexing a suitable approach for data warehouse design %U http://dx.doi.org/10.17762/ijritcc2321-8169.150253 %V 3 %X Data warehouse is a collection of huge database which is subject oriented, integrated, time-variant and non volatile. As it is a set of huge database, fast data access is the major performance parameter of any data warehouse. Generally the information retrieved from Data Warehouse is summarized or aggregated as it is required for some decision making process of organization. To retrieve such a information queries to be fired is of the nature aggregation function followed by having clause. Extracting information efficiently from data warehouse is the challenge in front of researchers. As it is a huge database time required to access information is more compare to normal databases. Due to this creating index on this huge database is essential and it is important for increasing the performance of data warehouse .Selection of appropriate indexing decreases the query execution time and the performance of data warehouse is increase. Presently B-tree indexing is used in different database products. For creating the index on any table they uses B Tree approach. B tree indexing is useful for the databases where the frequent updates are required like On Line Transaction Processing system(OLTP). It is a time consuming approach for data warehouse and On Line Analytical System(OLAP). Data warehouse is not frequently updated so Bitmap indexing is appropriate choice for the same. We have to create bitmap index on required vector at the start only. Once it is created on fixed database we can use it any time for any query. As per the requirement of query we have to select bitmap and execute query. The bitmap indexing is appropriate choice for Data warehouse only because of its feature like it is non volatile and huge data set

@article{Sarika_2015, abstract = {Data warehouse is a collection of huge database which is subject oriented, integrated, time-variant and non volatile. As it is a set of huge database, fast data access is the major performance parameter of any data warehouse. Generally the information retrieved from Data Warehouse is summarized or aggregated as it is required for some decision making process of organization. To retrieve such a information queries to be fired is of the nature aggregation function followed by having clause. Extracting information efficiently from data warehouse is the challenge in front of researchers. As it is a huge database time required to access information is more compare to normal databases. Due to this creating index on this huge database is essential and it is important for increasing the performance of data warehouse .Selection of appropriate indexing decreases the query execution time and the performance of data warehouse is increase. Presently B-tree indexing is used in different database products. For creating the index on any table they uses B Tree approach. B tree indexing is useful for the databases where the frequent updates are required like On Line Transaction Processing system(OLTP). It is a time consuming approach for data warehouse and On Line Analytical System(OLAP). Data warehouse is not frequently updated so Bitmap indexing is appropriate choice for the same. We have to create bitmap index on required vector at the start only. Once it is created on fixed database we can use it any time for any query. As per the requirement of query we have to select bitmap and execute query. The bitmap indexing is appropriate choice for Data warehouse only because of its feature like it is non volatile and huge data set}, added-at = {2015-08-04T08:01:57.000+0200}, author = {Prakash, Kale Sarika and Prathap, P.M. Joe}, biburl = {https://www.bibsonomy.org/bibtex/28b913b99e4e5cb882bfcac1300afa73c/ijritcc}, doi = {10.17762/ijritcc2321-8169.150253}, interhash = {bc70c4bd098a053762d93036ac3dbd57}, intrahash = {8b913b99e4e5cb882bfcac1300afa73c}, journal = {International Journal on Recent and Innovation Trends in Computing and Communication}, keywords = {Data Iceberg Iceberg(IB) Online Processing(OLAP) Processing(OLTP) Transaction analytical bitmap index(BI)Online queries query(IBQ) warehouse(DW)}, month = {february}, number = 2, pages = {680--683}, publisher = {Auricle Technologies, Pvt., Ltd.}, timestamp = {2015-08-04T08:01:57.000+0200}, title = {Bitmap indexing a suitable approach for data warehouse design}, url = {http://dx.doi.org/10.17762/ijritcc2321-8169.150253}, volume = 3, year = 2015 }