Indicator Configuration Method, Data Acquisition Method, Device, Equipment and Medium

Abstract

The present disclosure provides a method for configuring metrics and a method for obtaining data, which can be applied to the financial field or the database technology field. Among them, the method for configuring metrics includes: extracting metadata information to obtain business data items; constructing a business data table based on the business data items, where the business data table includes a table data item table and a field data item table; constructing a metric model and a metric definition, where the metric definition is constructed based on the metric model, and the metric model includes a dimension set; configuring the mapping relationship between the metadata detail table and the common dimension table to construct a first mapping table; configuring the mapping relationship between the common dimension table and the metric result table to construct a second mapping table, where the metric definition, the business data table, the first mapping table, and the second mapping table are used to configure and generate metric result data. The present disclosure also provides a metric configuration device, a data acquisition device, a device, a storage medium, and a program product.

Description

Technical Field

[0001] The present disclosure relates to the financial field or the database field, and particularly relates to a method for configuring indicators, a method for obtaining data, a device, a device, a medium and a program product. Background Art

[0002] For financial institutions with numerous business processes, their data structures are complex. The indicator data concerned by different branches has both commonalities and differences, and involves a large number of rules. There is a need for unified modeling rules and automated indicator configuration to facilitate business personnel to define indicators. Currently, traditional indicator processing methods do not divide models according to business scenarios, do not define indicators through models, cannot reuse indicator dimensions, metrics, and rules, and have high development costs and are not easy to maintain. Moreover, due to the inability to achieve the correspondence between the source detail table fields and the result table fields through automated dimension mapping, the fields of each result table are inconsistent, resulting in high maintenance costs. Summary of the Invention

[0003] In view of the above problems, embodiments of the present disclosure provide a method for configuring indicators, a method for obtaining data, a device, a device, a medium and a program product.

[0004] According to a first aspect of the present disclosure, there is provided a method for configuring indicators, characterized by including: extracting metadata information to obtain business data items, where the business data items include table data items and field data items; constructing a business data table based on the business data items, the business data table including a table data item table and a field data item table, and the table data item table and the field data item table being associated through a table identifier; configuring a mapping relationship between a metadata detail table and a common dimension table to construct a first mapping table, where the metadata detail table is associated with the table data item table through a table identifier; configuring a mapping relationship between the common dimension table and an indicator result table to construct a second mapping table; constructing an indicator model and an indicator definition, where the indicator definition is constructed based on the indicator model, and the indicator model includes a dimension set; where the indicator definition, the business data table, the first mapping table, and the second mapping table are used to configure and generate indicator result data.

[0005] According to an embodiment of the present disclosure, the indicator model is associated with a metadata detail sub-table, a dimension set, a metric set, and a filtering condition, and the metadata detail sub-table is a subset of the metadata detail table.

[0006] According to an embodiment of the present disclosure, the constructing of the indicator model and the indicator definition includes: constructing a single model based on the business data table and the metadata detail sub-table; constructing a single indicator definition based on the single model; constructing a derivative model based on the single indicator definition and a preset processing rule; and constructing a derivative indicator definition based on the derivative model.

[0007] According to an embodiment of the present disclosure, constructing a single metric definition based on the single model includes: selecting a single model for constructing the single metric definition; selecting a subset of dimensions, a subset of metrics, and a filtering condition associated with the selected single model; constructing the metric definition based on the metadata detail sub-table, the subset of dimensions, the subset of metrics, and the filtering condition associated with the selected single model, wherein the subset of dimensions is a subset of the dimension set, and the subset of metrics is a subset of the metric set.

[0008] According to an embodiment of the present disclosure, constructing a derived metric definition based on the derived model includes: selecting a derived model for constructing the derived metric definition; selecting a subset of dimensions and a processing rule associated with the selected derived model; constructing the derived metric definition based on the subset of dimensions and the processing rule associated with the selected derived model.

[0009] According to an embodiment of the present disclosure, the method metric configuration method further includes: constructing a metric permission table, where the metric permission table is associated with the metric definition.

[0010] According to an embodiment of the present disclosure, the method further includes: constructing a data permission table, where the data permission table is associated with the metric definition.

[0011] A second aspect of the present disclosure provides a data acquisition method, which is characterized by including: obtaining a data extraction instruction, where the data extraction instruction includes a metric definition; associating a business data table and a common dimension table based on the metric definition; associating a metadata detail sub-table based on the business data table; associating a first mapping table and a second mapping table based on the common dimension table; establishing a mapping relationship between the metadata detail sub-table and a metric result table based on the first mapping table and the second mapping table; obtaining metric result data based on the metric result table. Wherein, the metric definition, the business data table, the first mapping table, and the second mapping table are constructed according to the metric configuration method of the first aspect of the present disclosure.

[0012] According to an embodiment of the present disclosure, the data acquisition method further includes: periodically extracting metadata information based on a preset job scheduling period; updating the configured metric definition based on the metadata information.

[0013] According to an embodiment of the present disclosure, after obtaining the metric result data, the method further includes: processing the metric result data based on a metric permission item table to extract first visible metric data, where the metric permission table is constructed according to the metric configuration method of the first aspect of the present disclosure.

[0014] According to an embodiment of the present disclosure, after extracting the first visible index data, the method further includes: processing the index result data based on a data permission table to extract second visible index data, where the index permission table is constructed according to the index configuration method of the first aspect of the present disclosure.

[0015] A second aspect of the present disclosure provides an index configuration device, which includes: an acquisition module configured to extract metadata information and obtain service data items, where the service data items include table data items and field data items. A first construction module configured to construct a service data table based on the service data items, the service data table including a table data item table and a field data item table, and the table data item table and the field data item table are associated through a table identifier. A second construction module configured to configure a mapping relationship between a metadata detail table and a common dimension table and construct a first mapping table, where the metadata detail table and the table data item table are associated through a table identifier. A third construction module configured to configure a mapping relationship between the common dimension table and an index result table and construct a second mapping table. A fourth construction module configured to construct an index model and an index definition, where the index definition is constructed based on the index model, and the index model includes a dimension set. Among them, the index definition, the service data table, the first mapping table, and the second mapping table are used to configure and generate index result data.

[0016] A third aspect of the present disclosure provides a data acquisition device, which includes: a receiving module configured to obtain a data extraction instruction, and the data extraction instruction includes an index definition. A first processing module configured to associate a service data table and a common dimension table based on the index definition. A second processing module configured to associate a metadata detail sub-table based on the service data table. A third processing module configured to associate a first mapping table and a second mapping table based on the common dimension table. A fourth processing module configured to establish a mapping relationship between the metadata detail sub-table and the index result table based on the first mapping table and the second mapping table. A generation module configured to obtain index result data based on the index result table. Among them, the index definition, the service data table, the first mapping table, and the second mapping table are constructed according to the third construction module and the fourth construction module provided in the second aspect of the present disclosure.

[0017] A fourth aspect of the present disclosure provides an electronic device, including: one or more processors; a memory for storing one or more programs, where when the one or more programs are executed by the one or more processors, the one or more processors are caused to execute the above method.

[0018] A fourth aspect of the present disclosure also provides a computer-readable storage medium, on which executable instructions are stored, and when the instructions are executed by a processor, the processor is caused to execute the above method.

[0019] The fifth aspect of the present disclosure also provides a computer program product, including a computer program which, when executed by a processor, implements the above method. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Through the following description of the embodiments of the present disclosure with reference to the accompanying drawings, the above content and other objects, features and advantages of the present disclosure will become clearer. In the drawings:

[0021] Figure 1 FIG. schematically shows an application scenario diagram of an index configuration method according to an embodiment of the present disclosure.

[0022] Figure 2 FIG. schematically shows a flowchart of an index configuration method according to an embodiment of the present disclosure.

[0023] Figure 3 FIG. schematically shows the establishment process of the dual - dimension mapping.

[0024] Figure 4 FIG. schematically shows a flowchart of a method for constructing an index model and index definition according to an embodiment of the present disclosure.

[0025] Figure 5 FIG. schematically shows a flowchart of a data acquisition method according to an embodiment of the present disclosure.

[0026] Figure 6 FIG. schematically shows a structural block diagram of an index configuration device according to an embodiment of the present disclosure.

[0027] Figure 7 FIG. schematically shows a structural block diagram of a data acquisition device according to an embodiment of the present disclosure.

[0028] Figure 8 FIG. schematically shows a block diagram of an electronic device suitable for implementing an index configuration method and / or a data acquisition method according to an embodiment of the present disclosure. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0029] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are merely exemplary and are not intended to limit the scope of the present disclosure. In the following detailed description, for the sake of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present disclosure. However, it is obvious that one or more embodiments can also be implemented without these specific details. In addition, in the following description, descriptions of well - known structures and technologies are omitted to avoid unnecessarily confusing the concepts of the present disclosure.

[0030] The terms used herein are for describing specific embodiments only and are not intended to limit the present disclosure. The terms such as "including" and "comprising" used herein indicate the presence of the described features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0031] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those of ordinary skill in the art, unless otherwise defined. It should be noted that the terms used herein should be interpreted to have a meaning consistent with the context of this specification and should not be interpreted in an idealized or overly rigid manner.

[0032] In the case of using expressions such as "at least one of A, B, and C, etc.", generally, it should be interpreted according to the meaning commonly understood by those of ordinary skill in the art (for example, "a system having at least one of A, B, and C" should include, but is not limited to, a system having only A, only B, only C, having A and B, having A and C, having B and C, and / or having A, B, and C, etc.).

[0033] It should be noted that the index configuration method, data acquisition method, device, equipment, medium, and program product of the present disclosure can be used in the field of finance for index processing, and can also be used in any field other than the field of finance, such as the field of database technology. The application fields of the index configuration method, data acquisition method, device, equipment, medium, and program product of the present disclosure are not limited.

[0034] Embodiments of the present disclosure provide an index configuration method.

[0035] Figure 1 A schematic application scenario diagram of the index configuration method according to an embodiment of the present disclosure is shown.

[0036] As Figure 1 shown, the application scenario 100 according to this embodiment may include terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 is used to provide a medium for communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, etc.

[0037] Users can use the terminal devices 101, 102, 103 to interact with the server 105 through the network 104 to receive or send messages, etc. Various communication client applications may be installed on the terminal devices 101, 102, 103, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social platform software, etc. (only for example).

[0038] The terminal devices 101, 102, and 103 can be various electronic devices with the functions of inputting data items and making index query requests, including but not limited to smart phones, tablet computers, laptop computers, desktop computers, and so on.

[0039] The server 105 can be a server that provides various services. For example, it can be a background management server (only for example) that supports the websites browsed by users using the terminal devices 101, 102, and 103. The background management server can analyze and process data such as user requests received, and feedback the processing results (such as index result data generated according to the data items input by the user and the index query request) to the terminal devices.

[0040] It should be noted that the index configuration and data acquisition method provided by the embodiments of the present disclosure can generally be executed by the server 105. Correspondingly, the index configuration and data acquisition device provided by the embodiments of the present disclosure can generally be set in the server 105. The index configuration and data acquisition method provided by the embodiments of the present disclosure can also be executed by a server or a server cluster different from the server 105 and capable of communicating with the terminal devices 101, 102, 103 and / or the server 105. Correspondingly, the index configuration and data acquisition device provided by the embodiments of the present disclosure can also be set in a server or a server cluster different from the server 105 and capable of communicating with the terminal devices 101, 102, 103 and / or the server 105.

[0041] It should be understood that Figure 1 the numbers of the terminal devices, networks, and servers in

[0042] are merely illustrative. According to the implementation requirements, there can be any number of terminal devices, networks, and servers. Figure 1 The following will be based on Figures 2 to 5 the described scenario to describe in detail the index configuration method of the disclosed embodiments through

[0043] Figure 2 FIG. schematically shows a flowchart of the index configuration method according to an embodiment of the present disclosure.

[0044] As Figure 2 shown, the index configuration method of this embodiment includes operation S210 to operation S250.

[0045] In operation S210, extract metadata information and obtain service data items.

[0046] According to an embodiment of the present disclosure, for configuring metrics, metadata information can be first extracted from the metadata detail table in the database. Among them, the metadata detail table can include a narrow table or a wide table, and the metadata detail table can be stored in a GP database, a batch MPP database, a source-attached library, etc. A typical metadata detail table can include pg_class, pg_attribute, pg_namespace, pg_decription, pg_database, etc. Among them, business tags can be marked on the metadata information according to the source channel of the metadata detail table and the business scenario to form business data items, which serve as the basic data for constructing metric definitions. Among them, the business data items include table data items and field data items. Among them, typical table data items and field data items can include the fields as described in Table 1 and Table 2 respectively:

[0047] Table data item

[0048] Field Name Comment Table_code Table Code Table_eng_name English Name of the Table Table_chn_name Chinese Name of the Table Table_type Table Type Label_name Business Label

[0049] Field data items in Table 1

[0050] Field Name Comment Data_opt_code Data Item Code Data_opt_eng_name English Name of the Data Item Data_opt_chn_name Chinese Name of the Data Item Data_opt_type Data Item Type Table_code Source Table Code Label_name Business Label

[0051] Table 2

[0052] In operation S220, a business data table is constructed based on the business data items.

[0053] According to an embodiment of the present disclosure, after extracting the business data items, a business data table that respectively summarizes the table data items and field data items can be generated based on the extracted table data items or business data items. The business data table can include a table data item table and a field data item table, and the table data item table and the field data item table can be associated through a table identifier. Thus, the table data items corresponding to the current table identifier and the field data items included in the table can be obtained by querying the table identifier. Through the business data table, the field data item data of each metadata detail table can be associated and queried.

[0054] In a typical example, the metadata detail table can include the counter transaction and account information table (tp201_ecp_log_his_account), which includes the reconnection transaction time (txn_dt), institution number (insid), channel (chnl_tpcd), transaction amount (txn_amt), currency code (currency_cd), transaction global trace number (sys_evt_trace_id), etc. By extracting the metadata information, table data items (as shown in Table 3) and field data items (as shown in Table 4) can be obtained.

[0055] Table data item

[0056] Table Code A101 English Name of the Table tp201_ecp_log_his_account Chinese Name of the Table Counter Transaction and Account Information Table Table Type Full Transaction Table Business Label Counter Business

[0057] Table 3 Field Data Items

[0058]

[0059] Table 4

[0060] Furthermore, the table data items of multiple metadata detail tables can be summarized into a table data item table, and the field data items of different metadata detail tables can be summarized into a field data item table. The corresponding table data items and field data items can be queried through a table identifier (such as a table code). By constructing a business data table, it is convenient to find the metadata detail table and reduce the data overhead in the index configuration process.

[0061] In operation S230, configure the mapping relationship between the metadata detail table and the common dimension table, and construct the first mapping table.

[0062] In operation S240, configure the mapping relationship between the common dimension table and the index result table, and construct the second mapping table.

[0063] According to the embodiments of the present disclosure, it can be understood that the metadata detail table usually contains attributes such as dimensions and metrics. To reduce the amount of data processing during index configuration and avoid data redundancy caused by different organizations defining different names for dimensions with the same meaning, a common dimension table can be provided so that common dimensions can be directly selected from this table during index definition, and a clear mapping between the metadata detail table and the result table can be constructed. The mapping relationship between the metadata detail table and the common dimension table can be configured, and the mapping can be saved and the first mapping table can be constructed. The mapping relationship between the common dimension table and the index result table can also be configured, and the mapping can be saved and the second mapping table can be constructed. Through dual-dimension mapping, the mapping relationship configuration between the dimension fields of the metadata detail table and the index result table can be completed, so that users only need to focus on the common dimensions from a business perspective without paying attention to the table structure and the mapping relationship between each field. Among them, the metadata detail table can be associated with the table data item table through a table identifier. Thus, the association between index definition and the business data table can be established, and the metadata detail table can be associated through the business data table. Further, the metadata detail table and the index result table are associated through dual-dimension mapping.

[0064] Figure 3 Schematically shows the establishment process of the dual-dimension mapping.

[0065] Such as Figure 3As shown, the metadata breakdown table may include Breakdown Table 1 and Breakdown Table 2. The first mapping table includes Mapping Table A, and the second mapping table includes Mapping Table B. The index result table may include Result Table 1 and Result Table 1. Among them, Breakdown Table 1 and Breakdown Table 2 may contain the same dimensional fields: organization, time, and channel. However, the definitions of different dimensional fields in different breakdown tables may be different. For example, "Organization 1" and "Organization 2"; "Time 1" and "Time 2"; "Channel 1" and "Channel 2" have different field names. Through Mapping Table A, the "Organization 1" and "Organization 2" fields in Breakdown Table 1 and 2 can be respectively mapped to the "organization" field in the common dimensional table to form a unique mapping relationship. Similarly, the "Time 1" and "Time 2" fields in Breakdown Table 1 and 2 can be respectively mapped to the "time" field in the common dimensional table to form a unique mapping relationship; the "Channel 1" and "Channel 2" fields in Breakdown Table 1 and 2 can be respectively mapped to the "channel" field in the common dimensional table to form a unique mapping relationship. Further, through Mapping Table B, the "Organization 3" and "Organization 4" fields in Result Table 1 and 2 can be respectively mapped to the "organization" field in the common dimensional table to form a unique mapping relationship. Similarly, the "Time 3" and "Time 4" fields in Result Table 1 and 2 can be respectively mapped to the "time" field in the common dimensional table to form a unique mapping relationship; the "Channel 3" and "Channel 4" fields in Result Table 1 and 2 can be respectively mapped to the "channel" field in the common dimensional table to form a unique mapping relationship. Through the above double mapping, the organization field in Breakdown Table 1 - "Organization 1", the time field - "Time 1", and the channel field - "Channel 1" can be respectively mapped to the organization field in Result Table 1 - "Organization 3", "Time 3", and "Channel 3". Similarly, the mapping relationships of "Organization 2" - "Organization 4", "Time 2" - "Time 4", and "Channel 2" - "Channel 4" between Breakdown Table 2 and Result Table 2 can be established.

[0066] According to an embodiment of the present disclosure, the above double mapping relationship can be used for the construction of an index model and index definitions. Among them, when the user constructs an index model and index, the first mapping table and the second mapping table may be invisible to the user, and the common dimensional table may be visible. When the user selects a dimension set, the mapping relationship between the metadata breakdown table and the data result table can be automatically established through double mapping. It can be understood that when constructing the result table based on the double mapping relationship, the fields can be grouped and de-duplicated to reduce data overhead. The introduction of the common dimensional table and the double mapping relationship ensures the generality and maintainability of the result table, and also makes the dimensions easy to configure and expand.

[0067] In a specific example, based on the counter transaction record and account information table, common dimension tables, the first mapping table, the second mapping table, and the indicator result table as shown in Table 5 - Table 8 can be constructed for the metadata detail table. Combining with Table 4, the counter transaction record and account information table can include field data items such as transaction global tracking number, institution number, channel number, currency number, transaction amount, etc.

[0068] Common dimension table

[0069] Common Dimension Code Common Dimension Name DOT0001 Organization DOT0002 Channel DOT0003 Time ... ...

[0070] Table 5 First mapping table

[0071] Metadata Detail Table Data Item Code Table Number Common Dimension Code 000002 A101 DOT0001 000003 A101 DOT0002 000005 A101 DOT0003

[0072] Table 6

[0073] Through the first mapping table, a mapping relationship is formed between the [institution number] in Table 4 and the common dimension DOT0001, between the [channel number] and the common dimension DOT0002, and between the [transaction time] and the common dimension DOT0003.

[0074] Second mapping table

[0075] Common Dimension Code Result Table Attribute Column Result Table Name DOT0001 br_code QY_INDEX_RESULT DOT0002 channel_code QY_INDEX_RESULT DOT0003 data_date QY_INDEX_RESULT ... ... ...

[0076] Table 7 Indicator result table

[0077]

[0078] Table 8

[0079] Through the second mapping table, a corresponding relationship can be formed between the institution field [br_code] in the indicator result table and the common dimension DOT0001, between the [channel_code] and the common dimension DOT0002, and between the [data_date] and the common dimension DOT0003.

[0080] Through the above double mapping, a mapping relationship is formed between the [institution number] in the metadata detail table and the institution field [br_code] in the indicator result table. Similarly, a mapping relationship is formed between the [channel number] and the channel field [channel_code], and between the [transaction time] and the time field [data_date].

[0081] Furthermore, when constructing the indicator result table, the institution numbers can be grouped and de-duplicated and then written into the column of br_code, the channel numbers can be grouped and de-duplicated and then written into the column of channel_code, and the transaction times can be grouped and de-duplicated and then written into the column of data_date to ensure the generality and maintainability of the indicator result table and make the dimensions easy to configure and expand.

[0082] In operation S250, an index model and index definitions are constructed.

[0083] According to an embodiment of the present disclosure, the index definitions are constructed based on the index model, and the index model includes a dimension set. By using the dimension set to construct the index model, the source of index data can be quickly determined.

[0084] In some specific embodiments, the index model may be associated with a metadata detail sub-table, a dimension set, a metric set, and a filtering condition. Among them, the metadata detail sub-table may be one or more metadata detail tables that need to be associated when constructing a specific index model based on a specific business scenario or scope. It can be understood that the metadata detail table may be a subset of the metadata detail table set. The dimension set and the metric set are from the business data table, and the filtering condition may be preset by the management personnel based on experience. It can be understood that when the model is only associated with one metadata detail table, the dimension set and the metric set can also be directly obtained based on the metadata detail table.

[0085] According to an embodiment of the present disclosure, constructing the index model and index definitions may include constructing a single model and a single index definition, and constructing a derivative model and derivative index definitions based on the single model.

[0086] Figure 4 A flowchart showing a method for constructing an index model and index definitions according to an embodiment of the present disclosure is schematically shown.

[0087] As Figure 4 shown, the index configuration method of this embodiment includes operation S410 to operation S440.

[0088] In operation S410, a single model is constructed based on the business data table and the metadata detail table.

[0089] According to an embodiment of the present disclosure, based on the business scenario to be processed, the metadata detail sub-table, dimension set, metric set, and filtering condition required for constructing the single model can be extracted or defined from the business data table and the metadata detail table, so as to construct the single model.

[0090] A typical single model can be constructed based on the following method:

[0091] According to the specific business scenario and rules, construct a single model [counter business model], and quickly query the required elements according to the business label [counter business]:

[0092] (1) Select the metadata detail sub-table of the model - [counter transaction and account information table].

[0093] (2) Select the dimension set of the model - select three dimensions from the common dimension table: time, organization, and channel.

[0094] (3) Select the metric set of the model - select two metrics: transaction amount, select the calculation formula [SUM] for calculating the total transaction amount; transaction global tracking number, select the calculation formula [COUNTDISTINCT] for calculating the total number of transactions.

[0095] (4) Select the filtering condition of the model - select and edit currency = '156' to represent RMB transactions.

[0096] In operation S420, construct a single - indicator definition based on the single model.

[0097] According to the embodiments of the present disclosure, the single model selected for constructing the single - indicator definition can be used as the source model of the single indicator, and the metadata detail sub - table, dimension subset, metric subset, and filtering condition associated with the selected single model can be used as the source of the dimensions, metrics, and filtering conditions of the single - indicator definition and the data acquisition channel for indicator - related data. It can be understood that during the process of constructing the single - indicator definition, an indicator label can also be defined to facilitate the identification and reading of indicator - related data. Among them, all or part of the dimension set can be selected as the dimension subset of the single - indicator definition, and similarly, all or part of the metric set can be selected as the metric subset of the single - indicator definition. Thus, through different selections and combinations of the dimension subset and metric subset in a single model, multiple different single indicators can be generated, greatly reducing the time for indicator construction, improving the data - processing efficiency, and avoiding data redundancy.

[0098] A typical single - indicator definition can be constructed based on the following method:

[0099] Based on the constructed single model, according to the specific business scenario, single - indicator definitions [Over - the - counter transaction amount] and [Over - the - counter number of transactions] can be constructed:

[0100] (1) Select the single model [Over - the - counter business volume model], and the system automatically associates the metadata detail sub - table, dimension set, metric set, and filtering condition according to the model definition.

[0101] (2) Within the dimension range defined by the model, select the dimension subset required by the indicator: time, organization, and channel.

[0102] (3) Within the metric range defined by the model, select the metric subset required by the indicator. For example, if the transaction amount is selected, the indicator is [Over - the - counter transaction amount]; if the transaction global tracking number is selected, the indicator is [Over - the - counter number of transactions].

[0103] In operation S430, a derivative model is constructed based on the single - indicator definition and preset processing rules.

[0104] According to an embodiment of the present disclosure, after constructing the single - indicator definition, a derivative model can be quickly constructed through the preset processing rules, and further, a derivative - indicator definition can be obtained to avoid data redundancy caused by repeated definitions. Typical processing rules may include data - calculation rules, for example, four - arithmetic - operation rules. The processing rules for forming a derivative indicator through four - arithmetic operations on multiple single indicators to construct a derivative model can use the common dimensions among multiple single - indicator definitions as the dimension set of the derivative model. A derivative model is constructed based on the single - indicator definition and preset processing rules.

[0105] A typical derivative model can be constructed based on the following method:

[0106] Based on the two defined indicators of [Over - the - counter transaction amount] and [Over - the - counter transaction number], a model of [Average over - the - counter transaction amount per transaction] can be constructed:

[0107] (1) Select the two indicators of [Over - the - counter transaction amount] and [Over - the - counter transaction number].

[0108] (2) Define the editing processing rule: [Average over - the - counter transaction amount per transaction]=[Over - the - counter transaction amount / Over - the - counter transaction number].

[0109] (3) Select the common dimensions of the two single indicators: time, institution, and channel to complete the construction of the derivative model.

[0110] In operation S440, a derivative - indicator definition is constructed based on the derivative model.

[0111] According to an embodiment of the present disclosure, a constructed derivative model can be selected as the source model for the derivative - indicator definition. Select the dimension subset and processing rules associated with the selected derivative model. A derivative - indicator definition can also be constructed based on the dimension subset and the processing rules associated with the selected derivative model. Among them, all or part of the dimension set can be selected as the dimension subset of the derivative - indicator definition.

[0112] A typical derivative indicator can be constructed based on the following method:

[0113] (1) Select the derivative model [Average over - the - counter transaction amount per transaction], and automatically associate the dimension set and processing rules of the model according to the model definition.

[0114] (2) Within the dimension range defined by the model, select the dimension subset required by the indicator: time, institution, and channel.

[0115] According to an embodiment of the present disclosure, the index definition, the service data table, the first mapping table, and the second mapping table can be used to configure and generate index result data.

[0116] According to an embodiment of the present disclosure, in order to improve the security of index configuration, the index configuration method may further include constructing an index permission table. Among them, the index permission table is associated with the index definition. Specifically, the permission management of the corresponding dimension data items can be configured based on the dimensions in the index definition. For example, the dimension in the index definition may include an organization. The organization field may include multiple sub-organizations, and these multiple sub-organizations may have different levels within the organization, and different sub-organizations may have different index visibility permissions. Thus, an organization permission table can be constructed first, and then an index permission table can be constructed based on the organization permission table. Among them, the organization permission table and the index permission table can be associated through an organization identifier.

[0117] A typical organization permission table can be as shown in Table 9:

[0118] Organization Permission Table

[0119] Organization Code Authorized Organization Organization Hierarchy ... ... ...

[0120] Table 9

[0121] Correspondingly, an index permission table can be set as shown in Table 10:

[0122] Index Permission Table

[0123]

[0124] Table 10

[0125] It can be understood that the index permissions can include two aspects: 1. The visibility permissions of the index definitions of the branches and their subordinate organizations to which the currently logged-in user belongs: 2. The indexes shared by the entire organization. The union of the two can be used as the entire index range that the current user can see.

[0126] According to an embodiment of the present disclosure, in order to further improve the security of index configuration, the index configuration method may further include constructing a data permission table. Among them, the data permission table can be associated with the index definition. As mentioned above, the dimension in the index definition may include an organization. In addition to having different index visibility permissions for different sub-organizations in the organization field, for the same index, their visible data ranges may be different. Thus, a data permission table corresponding to different levels of organizations can be set, or a data permission table corresponding to different levels of personnel in the same organization can be set. Through the dual permission control mechanism of index permissions and data permissions, the isolation and sharing of index result data can be realized, and the data usage security of personnel at all levels of each organization can be improved.

[0127] It can be understood that the above-mentioned various data tables, common dimension tables, filtering conditions, and processing rules can all be constructed into database processing statements to achieve automated assembly of indicators, improve the efficiency of indicator assembly, and reduce labor costs.

[0128] Based on the above indicator configuration method, the present disclosure also provides a data acquisition method.

[0129] Figure 5 A flowchart of the data acquisition method according to an embodiment of the present disclosure is schematically shown.

[0130] As Figure 5 shown, the data acquisition method includes operation S510 - operation S560.

[0131] In operation S510, a data extraction instruction is obtained.

[0132] In operation S520, the business data table and the common dimension table are associated based on the indicator definition.

[0133] In operation S530, the metadata detail sub-table is associated based on the business data table.

[0134] In operation S540, the first mapping table and the second mapping table are associated based on the common dimension table.

[0135] In operation S550, the mapping relationship between the metadata detail sub-table and the indicator result table is established based on the first mapping table and the second mapping table.

[0136] In operation S560, the indicator result data is obtained based on the indicator result table.

[0137] According to an embodiment of the present disclosure, after configuring the metric model and metric definitions, metric result data can be automatically extracted. In some specific embodiments, the system can obtain a data extraction instruction submitted by a user, where the data extraction instruction may include metric definitions. Based on the subset of dimensions in the metric definition, a common dimension table and a business data table can be associated. Further, a metadata detail sub-table can be associated based on the business data table. Since a dual mapping mechanism is established during the process of configuring metrics, the first mapping table and the second mapping table can be associated based on the common dimension table, so that the mapping relationship between the metadata detail sub-table and the metric result table can be established based on the first mapping table and the second mapping table. Further, according to the data items in the metadata detail sub-table, combined with the metric subset and filtering conditions or processing rules in the metric definition, the metric result table can be obtained. Based on the metric result table, metric result data can be obtained. Among them, the metric definition, the business data table, the first mapping table, and the second mapping table can be constructed according to the metric configuration method of the embodiments of the present disclosure. It can be understood that since each data table, common dimension table, filtering condition, and processing rule can be constructed into a database processing statement, automatic assembly of metric processing statements can be realized without manual intervention, reducing labor costs.

[0138] According to an embodiment of the present disclosure, metadata information can be periodically extracted based on a preset job scheduling cycle, and the metric definition can be updated and configured based on the metadata information to obtain accurate metric result data in real time without manual intervention, reducing labor costs.

[0139] According to an embodiment of the present disclosure, after obtaining the metric result data, the method may further include: processing the metric result data based on a metric permission table to extract first visible metric data. Among them, the metric permission table is constructed according to the metric permission table construction method of the embodiments of the present disclosure. By setting the metric permission table, the visible range of the metric can be restricted, improving the security of data usage.

[0140] According to an embodiment of the present disclosure, after extracting the first visible metric data, the method may further include: processing the metric result data based on a data permission table to extract second visible metric data. Among them, the data permission table is constructed according to the data permission table construction method of the embodiments of the present disclosure. By setting the data permission table, the visible range of the metric result data can be further restricted, improving the security of data usage.

[0141] Based on the above metric configuration method, the present disclosure also provides a metric configuration device. The following will be combined with Figure 6 to describe this device in detail.

[0142] Figure 6 The structural block diagram of the metric configuration device according to an embodiment of the present disclosure is schematically shown.

[0143] As Figure 6 shown, the index configuration device 600 of this embodiment includes an acquisition module 610, a first construction module 620, a second construction module 630, a third construction module 640, and a fourth construction module 650.

[0144] Among them, the acquisition module 610 is configured to extract metadata information and obtain business data items, where the business data items include table data items and field data items.

[0145] The first construction module 620 is configured to construct a business data table based on the business data items. The business data table includes a table data item table and a field data item table, and the table data item table and the field data item table are associated through a table identifier.

[0146] The second construction module 630 is configured to configure the mapping relationship between the metadata detail table and the common dimension table, and construct a first mapping table, where the metadata detail table is associated with the table data item table through a table identifier.

[0147] The third construction module 640 is configured to configure the mapping relationship between the common dimension table and the index result table, and construct a second mapping table.

[0148] The fourth construction module 650 is configured to construct an index model and index definitions, where the index definitions are constructed based on the index model, and the index model includes a dimension set.

[0149] According to the embodiment of the present disclosure, the index definitions, the business data table, the first mapping table, and the second mapping table are used to configure and generate index result data.

[0150] Figure 7 Schematically shows a structural block diagram of a data acquisition device according to an embodiment of the present disclosure.

[0151] As Figure 7 shown, the data acquisition device 700 of this embodiment includes a receiving module 710, a first processing module 720, a second processing module 730, a third processing module 740, a fourth processing module 750, and a generating module 760.

[0152] The receiving module 710 is configured to obtain a data extraction instruction, and the data extraction instruction includes index definitions.

[0153] The first processing module 720 is configured to obtain a data extraction instruction, and the data extraction instruction includes index definitions.

[0154] The second processing module 730 is configured to associate the business data table and the common dimension table based on the index definitions.

[0155] The third processing module 740 is configured to associate the first mapping table and the second mapping table based on the common dimension table.

[0156] The fourth processing module 750 is configured to establish a mapping relationship between the metadata detail sub-table and the index result table based on the first mapping table and the second mapping table.

[0157] The generation module 760 is configured to obtain index result data based on the index result table.

[0158] According to an embodiment of the present disclosure, the index definition, the service data table, the first mapping table, and the second mapping table are constructed according to Figure 6 the described modules.

[0159] According to an embodiment of the present disclosure, the obtaining module 610, the first construction module 620, the second construction module 630, the third construction module 640, and the fourth construction module 650; or any multiple of the receiving module 710, the first processing module 720, the second processing module 730, the third processing module 740, the fourth processing module 750, and the generation module 760 may be combined and implemented in one module, or any one of them may be split into multiple modules. Alternatively, at least part of the functions of one or more of these modules may be combined with at least part of the functions of other modules and implemented in one module. According to an embodiment of the present disclosure, the obtaining module 610, the first construction module 620, the second construction module 630, the third construction module 640, and the fourth construction module 650; or at least one of the receiving module 710, the first processing module 720, the second processing module 730, the third processing module 740, the fourth processing module 750, and the generation module 760 may be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on chip, a system on a substrate, a system in a package, an application specific integrated circuit (ASIC), or may be implemented by any other reasonable way of integrating or packaging circuits, etc., in hardware or firmware, or implemented in any one of the three implementation manners of software, hardware, and firmware, or in an appropriate combination of any several of them. Alternatively, the obtaining module 610, the first construction module 620, the second construction module 630, the third construction module 640, and the fourth construction module 650; or at least one of the receiving module 710, the first processing module 720, the second processing module 730, the third processing module 740, the fourth processing module 750, and the generation module 760 may be at least partially implemented as a computer program module, and when the computer program module is run, the corresponding functions may be executed.

[0160] Figure 8A block diagram of an electronic device suitable for implementing an indicator configuration method and / or a data acquisition method according to an embodiment of the present disclosure is schematically shown.

[0161] As Figure 8 shown, the electronic device 900 according to an embodiment of the present disclosure includes a processor 901, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 902 or a program loaded from a storage section 908 into a random access memory (RAM) 903. The processor 901 can include, for example, a general microprocessor (e.g., CPU), an instruction set processor, and / or a related chipset, and / or a dedicated microprocessor (e.g., an application specific integrated circuit (ASIC)), etc. The processor 901 can also include on-board memory for caching purposes. The processor 901 can include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0162] In the RAM 903, various programs and data required for the operation of the electronic device 900 are stored. The processor 901, the ROM 902, and the RAM 903 are connected to each other via a bus 904. The processor 901 performs various operations of the method flow according to an embodiment of the present disclosure by executing the programs in the ROM 902 and / or the RAM 903. It should be noted that the program can also be stored in one or more memories other than the ROM 902 and the RAM 903. The processor 901 can also perform various operations of the method flow according to an embodiment of the present disclosure by executing the programs stored in the one or more memories.

[0163] According to an embodiment of the present disclosure, the electronic device 900 can further include an input / output (I / O) interface 905, and the input / output (I / O) interface 905 is also connected to the bus 904. The electronic device 900 can further include one or more of the following components connected to the I / O interface 905: an input section 906 including a keyboard, a mouse, etc.; an output section 907 including, for example, a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 908 including a hard disk, etc.; and a communication section 909 including a network interface card such as a LAN card, a modem, etc. The communication section 909 performs communication processing via a network such as the Internet. A drive 910 is also connected to the I / O interface 905 as needed. A removable medium 911, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 910 as needed so that a computer program read from it can be installed into the storage section 908 as needed.

[0164] The present disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or may exist alone without being assembled into the device / apparatus / system. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the methods according to the embodiments of the present disclosure are implemented.

[0165] According to an embodiment of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, for example, it may include but is not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above. In the present disclosure, the computer-readable storage medium may be any tangible medium that contains or stores a program, and the program may be used by or in combination with an instruction execution system, apparatus, or device. For example, according to an embodiment of the present disclosure, the computer-readable storage medium may include the above-described ROM 902 and / or RAM 903 and / or one or more memories other than ROM 902 and RAM 903.

[0166] Embodiments of the present disclosure also include a computer program product, which includes a computer program that contains program code for executing the method shown in the flowchart. When the computer program product runs on a computer system, the program code is used to cause the computer system to implement the method provided by the embodiments of the present disclosure.

[0167] When the computer program is executed by the processor 901, the above functions defined in the system / apparatus of the embodiments of the present disclosure are executed. According to an embodiment of the present disclosure, the above-described systems, apparatuses, modules, units, etc. may be implemented by computer program modules.

[0168] In one embodiment, the computer program may rely on tangible storage media such as optical storage devices and magnetic storage devices. In another embodiment, the computer program may also be transmitted and distributed in the form of a signal on a network medium and downloaded and installed through the communication part 909, and / or installed from the removable medium 911. The program code included in the computer program may be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0169] In such an embodiment, the computer program can be downloaded and installed from a network through the communication part 909, and / or installed from the removable medium 911. When the computer program is executed by the processor 901, the above functions defined in the system of the embodiments of the present disclosure are performed. According to the embodiments of the present disclosure, the above-described systems, devices, apparatuses, modules, units, etc. can be implemented by computer program modules.

[0170] According to the embodiments of the present disclosure, the program code for executing the computer program provided by the embodiments of the present disclosure can be written in any combination of one or more programming languages. Specifically, these computing programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages include, but are not limited to, such as Java, C++, python, the "C" language, or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, by connecting through the Internet using an Internet service provider).

[0171] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagram may represent a module, a program segment, or a part of code, and the above-mentioned module, program segment, or part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram or flowchart, and the combinations of blocks in the block diagram or flowchart, can be implemented by a dedicated hardware-based system for performing the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0172] Those skilled in the art can understand that the features recited in the various embodiments and / or claims of the present disclosure can be combined or combined in various ways, even if such combinations or combinations are not explicitly recited in the present disclosure. In particular, without departing from the spirit and teachings of the present disclosure, the features recited in the various embodiments and / or claims of the present disclosure can be combined and combined in various ways. All such combinations and / or combinations fall within the scope of the present disclosure.

[0173] The embodiments of the present disclosure have been described above. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of the present disclosure. Although the embodiments have been described separately above, this does not mean that the measures in each embodiment cannot be used advantageously in combination. The scope of the present disclosure is defined by the appended claims and their equivalents. Without departing from the scope of the present disclosure, those skilled in the art can make various substitutions and modifications, and all such substitutions and modifications should fall within the scope of the present disclosure.

Claims

1. An index configuration method, characterized in that, it includes: Extract metadata information to obtain business data items, where the business data items include table data items and field data items; Build a business data table based on the business data items, the business data table includes a table data item table and a field data item table, and the table data item table and the field data item table are associated through a table identifier; Configure the mapping relationship between the metadata detail table and the common dimension table to build a first mapping table, where the metadata detail table is associated with the table data item table through a table identifier; Configure the mapping relationship between the common dimension table and the index result table to build a second mapping table; Build an index model and an index definition based on the dual mapping relationship, where the index definition is built based on the index model, and the index model includes a dimension set; Among them, the index definition, the business data table, the first mapping table and the second mapping table are used to configure and generate index result data.

2. The method according to claim 1, wherein, The index model is associated with a metadata detail sub-table, a dimension set, a metric set, and a filtering condition, and the metadata detail sub-table is a subset of the metadata detail table.

3. The method according to claim 2, wherein, The building of the index model and the index definition includes: Build a single model based on the business data table and the metadata detail sub-table; Build a single index definition based on the single model; Build a derivative model based on the single index definition and a preset processing rule; and Build a derivative index definition based on the derivative model.

4. The method according to claim 3, wherein, Building a single index definition based on the single model includes: Select a single model for building the single index definition; Select a dimension subset, a metric subset, and a filtering condition associated with the selected single model; Build the index definition based on the metadata detail sub-table, the dimension subset, the metric subset, and the filtering condition associated with the selected single model, where the dimension subset is a subset of the dimension set, and the metric subset is a subset of the metric set.

5. The method according to claim 4, wherein, Building a derivative index definition based on the derivative model includes: Select a derivative model for building the derivative index definition; Select a dimension subset and a processing rule associated with the selected derivative model; Build the derivative index definition based on the dimension subset and the processing rule associated with the selected derivative model.

6. The method according to claim 1, characterized in that, The method further includes: Build an index permission table, and the index permission table is associated with the index definition.

7. The method according to claim 6, characterized in that, The method further includes: Build a data permission table, and the data permission table is associated with the index definition.

8. A data acquisition method, characterized in that, it includes: Obtain a data extraction instruction, and the data extraction instruction contains an index definition; Associate the business data table and the common dimension table based on the index definition; Associate the metadata detail sub-table based on the business data table; Associate the first mapping table and the second mapping table based on the common dimension table; Establish the mapping relationship between the metadata detail sub-table and the index result table based on the first mapping table and the second mapping table; Obtain index result data based on the index result table. Among them, the index definition, the business data table, the first mapping table, and the second mapping table are constructed according to the index configuration method described in any one of claims 1-7.

9. According to the method described in claim 8, wherein, the method further includes: Regularly extract metadata information based on a preset job scheduling period; Update the configured index definition based on the metadata information.

10. According to the method described in claim 8, wherein, After obtaining the index result data, the method further includes: Process the index result data based on the index weight item table to extract the first visible index data.

11. According to the method described in claim 9, wherein, After extracting the first visible index data, the method further includes: Process the index result data based on the data permission table to extract the second visible index data.

12. An index configuration device, characterized in that, it includes: An acquisition module configured to extract metadata information and obtain business data items, where the business data items include table data items and field data items; A first construction module configured to construct a business data table based on the business data items. The business data table includes a table data item table and a field data item table, and the table data item table and the field data item table are associated through a table identifier; A second construction module configured to configure the mapping relationship between the metadata detail table and the common dimension table and construct a first mapping table, where the metadata detail table is associated with the table data item table through a table identifier; A third construction module configured to configure the mapping relationship between the common dimension table and the index result table and construct a second mapping table; A fourth construction module configured to construct an index model and an index definition based on a dual mapping relationship, where the index definition is constructed based on the index model, and the index model includes a dimension set; Among them, the index definition, the business data table, the first mapping table, and the second mapping table are used to configure and generate index result data.

13. A data acquisition device, characterized in that, it includes: A receiving module configured to obtain a data extraction instruction, and the data extraction instruction includes an index definition; A first processing module configured to associate the business data table and the common dimension table based on the index definition; A second processing module configured to associate the metadata detail sub-table based on the business data table; A third processing module configured to associate the first mapping table and the second mapping table based on the common dimension table; A fourth processing module configured to establish the mapping relationship between the metadata detail sub-table and the index result table based on the first mapping table and the second mapping table; A generation module configured to obtain index result data based on the index result table, wherein, the index definition, the business data table, the first mapping table, and the second mapping table are constructed according to the module described in claim 12.

14. An electronic device, including: One or more processors; A storage device for storing one or more programs, wherein, when the one or more programs are executed by the one or more processors, the one or more processors are caused to execute the method according to any one of claims 1 to 11.

15. A computer-readable storage medium having executable instructions stored thereon, which when executed by a processor cause the processor to execute the method according to any one of claims 1 to 11.

16. A computer program product comprising a computer program, which when executed by a processor implements the method according to any one of claims 1 to 11.

Images