<![CDATA[Batik product has spread in various regions in Indonesia. Batik companies usually have data that accumulates and accumulates without any follow-up to the data. It is also not supported by well-executed final reports. Therefore it is necessary to build a data warehouse that can be used as a source of information for Batik management related to the trend of the type of batik motif based on the category of goods and marketing area from time to time. One important process that must be done in the operation of data warehouse is the process of copying data from the operational database. Before the operational data goes into the data warehouse, ETL process (extract, transform, load) to the data is done. The process is intended to standardize the data used in the data warehouse. Meanwhile, the scheme designed for the development of data warehouse using Snowflake Schema model. The results showed that batik warehouse data has four dimension tables (Product dimension, Region dimension, Time dimension, and Customer dimension), four sub dimension tables (Category dimension, Sub_Category dimension, Pattern dimension and Gender dimension) and one Fact table, Fact Sales. The extraction process produces dimension tables (Product dimension, Region dimension, Time dimension and Customer dimension) and sub-dimensional tables (Category dimensions, Sub_Category dimensions, Pattern dimensions and Gender dimensions). All monitoring of sales data of batik products is done using cube browser. The information displayed by each dimension can be viewed in more detail with the drill down or roll up process in accordance with the hierarchy rules of each dimension field.]]>
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