Retail data analysis method
A data analysis and data technology, applied in the direction of database index, relational database, database model, etc., can solve the problems of data set query performance degradation, subject table data expansion, etc., to reduce data intercommunication costs, meet data needs, and respond quickly Effect
Inactive Publication Date: 2021-01-22
武汉市钱鲸科技有限公司
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Problems solved by technology
[0006] Query performance will slow down with business development. When the amount of business data is small, the traditional solution can meet user needs. However, after the amount of business data reaches a certain level, since all the fields of the corresponding topic are mixed in a data set, it will make the topic The table data is extremely inflated, causing the query performance of this dataset to drop
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[0023] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention.
[0024] refer to figure 1 , a retail data analysis method, the method comprises the steps of:
[0025] S1: Provide dimension and index screening of various themes. Users can select the dimensions and indicators to be analyzed according to their own needs, obtain the retail data they want, and directly check all the dimensions and indicators that need to be queried;
[0026] S2: In the metadata system, define the dimensions and indicators that can be produced by all topics, as well as the tables where the dimensions and indicators are located, associated fields, and calculation formulas;
[0027] S3: After the user selects the dimensions and indicators to filter, the ...
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The invention discloses a retail data analysis method, which is jointly completed based on a data warehouse and metadata, divides basic data into'dimensions' and 'indexes' by utilizing the metadata, lists all data fields of different topics, weakens the topics, enables a user to freely select different dimensions and indexes for combination, and improves the retail data analysis efficiency. Basedon the corresponding relation between all service metadata and technical metadata, the system converts indexes and dimensions which a user wants to screen into corresponding topics in a data warehousemarket layer, screens out a table with the minimum weight, splices sql grouping aggregation and associates and merges result sets according to conditions, achieves cross-data-set query, reduces the data intercommunication cost, and meets multi-dimensional and multi-angle data requirements of the user comprehensively met, the operation is simple, all queries can be quickly responded without waiting, and ad-hoc queries are truly realized.
Description
technical field [0001] The invention relates to the technical field of retail data monitoring, in particular to a retail data analysis method. Background technique [0002] Various olap systems on the market are generally based on data warehouses, that is, extract a subset of detailed data from data warehouses and store them in OLAP storage after necessary aggregation for reading by front-end analysis tools. [0003] There are following problems in this scheme: [0004] The requirements for user analysis capabilities are high. Users need to consider which subject data they want to analyze before querying, which data source / data set to choose, such as sales, membership, inventory, etc., in order to get the desired data, but Most users don't know how to select queries when they just enter the interface, and they need to go through systematic training before they can use it, and the learning cost is relatively high. [0005] Choose a single theme. When the business is complex...
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IPC IPC(8): G06F16/2457G06F16/22G06F16/28G06F16/2455
CPCG06F16/24573G06F16/2282G06F16/285G06F16/2456
Inventor 柴楹薛静
Owner 武汉市钱鲸科技有限公司