The Accessing And Analyzing System Of The Consumption Of Materials And Energy Sources Based On The Data Warehouse

In such a highly competitive society, the mass data possessed by the companies come to be a significant wealth. To meet the badly demand for the data decision support and analysis, a new information technique called data warehouse was springing up in recent years. The applicable data warehouse technique is capable of analyzing the data precisely, efficiently, speedily and comprehensively to acquire the knowledge of decision-making. The major content of this article is about how to apply this technique to the system, which assesses and analyzes the consumption of materials and energy sources in petrochemical enterprises. In the first part of this article, the author makes an on-the-spot and in-depth analysis of the demand for the assessing system of the consumption of materials and energy sources in Qilu petrochemical plastic factory, and then manage to design and explore the system, by which the users are able to browse and supervise the consumption status of each work team. It facilitates the users to regulating the technology, reducing the raw materials and energy sources, ultimately lowering the unit cost and increasing the profit for the enterprise. In the following part, the author designs a multidimensional cube for the consumption of materials and energy sources as the precondition of analysis. On the basis of this cube, the author studies some problems being encountered when deploying the data warehouse, including the data extract, data cleansing, data transform and screen display etc. He gives two examples of querying the report forms of consumption of materials and energy sources in work teams and the monthly consumption of materials and energy sources, Comparing the performance between OLAP and SQL and finally makes a conclusion that OLAP has higher performance than that of SQL under the circumstances of mass data. In the end, the author preliminarily discusses the possibility of how to utilize the data warehouse to analyze the production situation in workshop and adjust the technology parameter to optimize the production and save the energy sources. By giving an example of 'percentages of water compositions', the author offers a general resolution.