{"created":"2020-09-01T13:16:03.225842+00:00","id":3669,"links":{},"metadata":{"_buckets":{"deposit":"9d4eef86-c91f-4dce-9d84-4eada918085e"},"_deposit":{"id":"3669","owners":[],"pid":{"revision_id":0,"type":"recid","value":"3669"},"status":"published"},"_oai":{"id":"oai:meral.edu.mm:recid/3669","sets":["1582963302567:1597824273898"]},"communities":["ucsy"],"item_1583103067471":{"attribute_name":"Title","attribute_value_mlt":[{"subitem_1551255647225":"Stationery Sales Analysis Using OLAP","subitem_1551255648112":"en"}]},"item_1583103085720":{"attribute_name":"Description","attribute_value_mlt":[{"interim":"Today, business organizations need to know what’s going on in the market, and make the right foreseeing decision. To overcome this requirement, this system implements useful tools to analyze the Stationery Shop sales records on multidimensional database and data cube by using on-line analytical processing (OLAP) that can view or browse information from different angles. Data mining tools can analyze enormous sets of data and then extract the meaning of the data and the resulting information can provide for the decision making process. A data warehouse, a repository of long-term storage of data from multiple data sources, organized sources as to facilitate management decision making. It makes better and faster decisions and expected to present right information in the right place at the right time with the right cost to make the right decision. It can present implementation of data warehouse for stationery shop. OLAP is a methodology that support analysis and decision support system with aggregate values extract from daily transaction database. Data cube will be used for faster reports since they store the pre-computation of count of the transactions."}]},"item_1583103108160":{"attribute_name":"Keywords","attribute_value_mlt":[{"interim":"Data Warehousing"},{"interim":"Analysis"},{"interim":"OLAP"},{"interim":"Business Intelligence"}]},"item_1583103120197":{"attribute_name":"Files","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2019-07-29"}],"displaytype":"preview","filename":"3663.pdf","filesize":[{"value":"286 Kb"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"url":"https://meral.edu.mm/record/3669/files/3663.pdf"},"version_id":"87c3ea51-d8e3-4297-b7c1-7c63121d1e81"}]},"item_1583103131163":{"attribute_name":"Journal articles","attribute_value_mlt":[{"subitem_issue":"","subitem_journal_title":"Fourth Local Conference on Parallel and Soft Computing","subitem_pages":"","subitem_volume":""}]},"item_1583103147082":{"attribute_name":"Conference papers","attribute_value_mlt":[{"subitem_acronym":"","subitem_c_date":"","subitem_conference_title":"","subitem_part":"","subitem_place":"","subitem_session":"","subitem_website":""}]},"item_1583103211336":{"attribute_name":"Books/reports/chapters","attribute_value_mlt":[{"subitem_book_title":"","subitem_isbn":"","subitem_pages":"","subitem_place":"","subitem_publisher":""}]},"item_1583103233624":{"attribute_name":"Thesis/dissertations","attribute_value_mlt":[{"subitem_awarding_university":"","subitem_supervisor(s)":[{"subitem_supervisor":""}]}]},"item_1583105942107":{"attribute_name":"Authors","attribute_value_mlt":[{"subitem_authors":[{"subitem_authors_fullname":"Kyaw, Myat Myitzu"}]}]},"item_1583108359239":{"attribute_name":"Upload type","attribute_value_mlt":[{"interim":"Publication"}]},"item_1583108428133":{"attribute_name":"Publication type","attribute_value_mlt":[{"interim":"Article"}]},"item_1583159729339":{"attribute_name":"Publication date","attribute_value":"2009-12-30"},"item_1583159847033":{"attribute_name":"Identifier","attribute_value":"http://onlineresource.ucsy.edu.mm/handle/123456789/1410"},"item_title":"Stationery Sales Analysis Using OLAP","item_type_id":"21","owner":"1","path":["1597824273898"],"publish_date":"2019-07-29","publish_status":"0","recid":"3669","relation_version_is_last":true,"title":["Stationery Sales Analysis Using OLAP"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2021-12-13T03:55:38.455503+00:00"}