Data generation method and apparatus, electronic device, and computer-readable medium

Abstract

This disclosure presents embodiments of a data generation method, apparatus, electronic device, and computer-readable medium. One specific embodiment of the data generation method includes: acquiring data requirement information for data to be queried; using a pre-built data processing platform to determine business units associated with the data to be queried, wherein the data processing platform processes indicators and their corresponding data through three levels: business domain, business theme, and business unit. Each business domain corresponds to at least one business theme, each business theme corresponds to at least one business unit, and each business unit corresponds to at least one data indicator; acquiring a pre-established detail table corresponding to the business unit; and generating the data to be queried based on the detail table and the data requirement information. This embodiment can efficiently and accurately generate data to be queried related to the data requirement information using the data processing platform and the data requirement information.

Description

Technical Field

[0001] Embodiments of this disclosure relate to the field of computer technology, and more particularly to data generation methods, apparatus, electronic devices, and computer-readable media. Background Technology

[0002] Currently, various enterprises may need data on a specific dimension of their target business area to further analyze the data and potentially adopt certain strategies. The common method for generating data on a specific dimension of a target business area is to directly query the detailed table related to that dimension, and then analyze the data from that table.

[0003] However, when generating the above data using the above method, the following technical problems often occur: the generated data is not reasonable or effective enough, resulting in low efficiency and accuracy. Summary of the Invention

[0004] The summary portion of this disclosure is intended to provide a brief overview of the concepts, which will be described in detail in the detailed description portion. This summary portion is not intended to identify key or essential features of the claimed technical solutions, nor is it intended to limit the scope of the claimed technical solutions.

[0005] Some embodiments of this disclosure provide data generation methods, apparatus, devices, and computer-readable media to address the technical problems mentioned in the background section above.

[0006] In a first aspect, some embodiments of this disclosure provide a data generation method, which includes: obtaining data requirement information of data to be queried; using a pre-built data processing platform to determine the business unit associated with the data to be queried, wherein the data processing platform processes indicators and the data corresponding to the indicators through three levels: business domain, business theme, and business unit, wherein the business domain corresponds to at least one business theme, the business theme corresponds to at least one business unit, and the business unit corresponds to at least one data indicator; obtaining a pre-established detail table corresponding to the business unit, wherein the detail table records the data information of each indicator in the business unit; and generating the data to be queried based on the detail table and the data requirement information.

[0007] Optionally, the above-mentioned method of using a pre-built data processing platform to determine the business unit associated with the data to be queried includes: using the pre-built data processing platform to determine the business domain associated with the data to be queried as a first target business domain; using the data processing platform to determine the business theme associated with the first target business domain as a first target business theme based on the data requirement information; and using the data processing platform to determine the business unit associated with the first target business theme based on the data requirement information.

[0008] Optionally, generating the data to be queried based on the above detailed table and the above data requirements includes: summarizing the above dimension table and the above detailed table to generate a data summary table; and filtering the data in the above data summary table according to the above data requirements to obtain the data to be queried.

[0009] Optionally, the business domains, business themes, business units, metrics, and data in the aforementioned data processing platform are added through the following steps: obtaining target data from the data source; determining whether there exists a business domain associated with the target data as a second target business domain in each business domain of the aforementioned data processing platform; in response to determining the existence of the second target business domain, determining each set of business themes associated with the second target business domain; determining whether there exists a business theme associated with the target data as a second target business theme in each set of business themes associated with the second target business domain; in response to determining the existence of the second target business theme, determining each business unit associated with the second target business theme; determining whether there exists a business unit associated with the target data as a second target business unit in each business unit associated with the second target business theme; and in response to determining the existence of the second target business unit, adding the target data to the detail table corresponding to the second target business unit according to a predetermined time.

[0010] Optionally, the method further includes: in response to determining that the second target business topic does not exist, adding the second target business topic to each business topic associated with the second target business domain; adding the second target business unit to the business unit associated with the second target business topic; creating at least one indicator corresponding to the second target business unit and a detailed table associated with the second target business unit; adding data indicator information corresponding to the target data to the detailed table associated with the second target business unit according to a predetermined time, and storing at least one indicator corresponding to the second target business unit.

[0011] Optionally, the above method further includes: in response to determining that the second target business unit does not exist, adding the second target business unit to each business unit associated with the second target business topic; creating at least one indicator corresponding to the second target business unit and a detailed table associated with the second target business unit; adding data indicator information corresponding to the target data to the detailed table associated with the second target business unit according to a predetermined time, and storing at least one indicator corresponding to the second target business unit.

[0012] Optionally, the dimension tables and detail tables corresponding to the above business units are continuously updated according to a predetermined time period.

[0013] Secondly, some embodiments of this disclosure provide a data generation apparatus, comprising: a first acquisition unit configured to acquire data requirement information of data to be queried; a determination unit configured to determine, using a pre-built data processing platform, a business unit associated with the data to be queried, wherein the data processing platform processes indicators and the data corresponding to the indicators through three levels: business domain, business theme, and business unit, wherein the business domain corresponds to at least one business theme, the business theme corresponds to at least one business unit, and the business unit corresponds to at least one data indicator; a second acquisition unit configured to acquire a pre-established detail table corresponding to the business unit, wherein the detail table records data information of each indicator in the business unit; and a generation unit configured to generate the data to be queried based on the detail table and the data requirement information.

[0014] Optionally, the determining unit is further configured to: use a pre-built data processing platform to determine the business domain associated with the data to be queried as the first target business domain; use the data processing platform to determine the business theme associated with the first target business domain as the first target business theme based on the data requirement information; and use the data processing platform to determine the business unit associated with the first target business theme based on the data requirement information.

[0015] Optionally, the generation unit is further configured to: summarize the above-mentioned dimension table and the above-mentioned detail table to generate a data summary table; and filter the data in the above-mentioned data summary table according to the above-mentioned data requirements information to obtain the above-mentioned data to be queried.

[0016] Optionally, the apparatus further includes: adding the business domains, business themes, business units, metrics, and data in the aforementioned data processing platform through the following steps: obtaining target data from a data source; determining whether there exists a business domain associated with the target data as a second target business domain in each business domain of the aforementioned data processing platform; in response to determining the existence of the second target business domain, determining each set of business themes associated with the second target business domain; determining whether there exists a business theme associated with the target data as a second target business theme in each set of business themes associated with the second target business domain; in response to determining the existence of the second target business theme, determining each business unit associated with the second target business theme; determining whether there exists a business unit associated with the target data as a second target business unit in each business unit associated with the second target business theme; and in response to determining the existence of the second target business unit, adding the target data to the detail table corresponding to the second target business unit according to a predetermined time.

[0017] Optionally, the apparatus further includes: in response to determining that the second target business topic does not exist, adding the second target business topic to each business topic associated with the second target business domain; adding the second target business unit to the business unit associated with the second target business topic; creating at least one indicator corresponding to the second target business unit and a detail table associated with the second target business unit; adding data indicator information corresponding to the target data to the detail table associated with the second target business unit according to a predetermined time, and storing at least one indicator corresponding to the second target business unit.

[0018] Optionally, the apparatus further includes: in response to determining that the second target business unit does not exist, adding the second target business unit to each business unit associated with the second target business topic; creating at least one indicator corresponding to the second target business unit and a detailed table associated with the second target business unit; adding data indicator information corresponding to the target data to the detailed table associated with the second target business unit according to a predetermined time, and storing at least one indicator corresponding to the second target business unit.

[0019] Optionally, the device also includes: the dimension table corresponding to the above-mentioned business unit and the above-mentioned detail table are continuously updated according to a predetermined time period.

[0020] Thirdly, some embodiments of this disclosure provide an electronic device, including: one or more processors; and a storage device having one or more programs stored thereon, which, when executed by one or more processors, cause the one or more processors to implement any of the methods in the first aspect.

[0021] Fourthly, some embodiments of this disclosure provide a computer-readable medium having a computer program stored thereon, wherein the program, when executed by a processor, implements any of the methods in the first aspect.

[0022] The various embodiments of this disclosure have the following beneficial effects: the data generation method of some embodiments of this disclosure can efficiently and accurately generate query data related to the data requirement information through a data processing platform and data requirement information. Specifically, the generated data is not reasonable or effective enough, resulting in low efficiency and accuracy. Based on this, the data generation method of some embodiments of this disclosure can first obtain the data requirement information of the query data as the basis for generating the query data. Then, using a pre-built data processing platform, the business units associated with the query data are determined. The data processing platform processes the indicators and the corresponding data through three levels: business domain, business theme, and business unit. The business domain corresponds to at least one business theme, the business theme corresponds to at least one business unit, and the business unit corresponds to at least one data indicator. Here, the data processing platform can efficiently and accurately process the data through the three levels of business domain, business theme, and business unit, making the data more refined. In practice, the data processing platform also links the data corresponding to each link through business scenarios. Then, a pre-established detailed table corresponding to the business unit is obtained. Finally, based on the detailed tables corresponding to the aforementioned business units and the aforementioned data requirements, the data to be queried can be accurately generated. Therefore, this method can efficiently and accurately generate query data related to the data requirements using a data processing platform and data requirements information. Attached Figure Description

[0023] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and the originals and elements are not necessarily drawn to scale.

[0024] Figure 1 This is a schematic diagram of an application scenario of the data generation method of some embodiments of this disclosure;

[0025] Figure 2 This is a flowchart of some embodiments of the data generation method according to this disclosure;

[0026] Figure 3 This is a schematic diagram of the data generation method according to some embodiments of the present disclosure being incorporated into a data processing platform;

[0027] Figure 4These are flowcharts of other embodiments of the data generation method according to this disclosure;

[0028] Figure 5 These are schematic diagrams illustrating the structure of some embodiments of the data generation apparatus according to this disclosure;

[0029] Figure 6 This is a schematic diagram of the structure of an electronic device suitable for implementing some embodiments of the present disclosure. Detailed Implementation

[0030] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0031] It should also be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings. Unless otherwise specified, the embodiments and features described in this disclosure can be combined with each other.

[0032] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are used only to distinguish different devices, modules or units, and are not used to limit the order of functions performed by these devices, modules or units or their interdependencies.

[0033] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0034] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

[0035] This disclosure will now be described in detail with reference to the accompanying drawings and embodiments.

[0036] Figure 1 This is a schematic diagram illustrating an application scenario of the data generation method according to some embodiments of this disclosure.

[0037] like Figure 1As shown, electronic device 101 can first obtain data requirement information 102 for the data to be queried 106. In this application scenario, the data requirement information 102 can be: "Statistics on the outbound logistics information of Huayu Logistics in Beijing from January to February". Then, using a pre-built data processing platform 103, the business unit 104 associated with the data to be queried 106 is determined. The data processing platform 103 processes indicators and their corresponding data through three levels: business domain, business theme, and business unit. The business domain corresponds to at least one business theme, the business theme corresponds to at least one business unit, and the business unit corresponds to at least one data indicator. In this application scenario, the business unit 104 can be an outbound business unit 104. Then, a pre-built detail table 105 corresponding to the business unit 104 is obtained. In this application scenario, the detail table 105 can be an outbound detail table 1051. Finally, based on the detail table 105 and the data requirement information 102, the data to be queried 106 is generated. In this application scenario, the data to be queried, 106, could be: "Outbound data of Huayu Logistics in Beijing from January to February".

[0038] It should be noted that the aforementioned electronic device 101 can be either hardware or software. When the electronic device is hardware, it can be implemented as a distributed cluster consisting of multiple servers or terminal devices, or as a single server or a single terminal device. When the electronic device is software, it can be installed in the hardware devices listed above. It can be implemented as, for example, multiple software programs or software modules used to provide distributed services, or as a single software program or software module. No specific limitations are made here.

[0039] It should be understood that Figure 1 The number of electronic devices shown is merely illustrative. Any number of electronic devices can be used depending on the implementation requirements.

[0040] Continue to refer Figure 2 The diagram illustrates a flow 200 of some embodiments of a data generation method according to the present disclosure. This data generation method includes the following steps:

[0041] Step 201: Obtain the data requirements information for the data to be queried.

[0042] In some embodiments, the execution entity of the data generation method (e.g. Figure 1The electronic device 101 shown can obtain data requirement information for the data to be queried via wired or wireless connection. Here, the aforementioned data requirement information can be information requested by the user based on a specific business scenario and defined dimensions. For example, the aforementioned data requirement information could be: "In the logistics field, outbound data of Huayu Logistics in Beijing from January to February." Here, the aforementioned logistics field represents the business scenario. The geographical dimension can be "Beijing." The time dimension can be "January to February."

[0043] It should be noted that the aforementioned wireless connection methods may include, but are not limited to, 3G / 4G / 5G connections, WiFi connections, Bluetooth connections, WiMAX connections, Zigbee connections, UWB (ultra wideband) connections, and other currently known or future wireless connection methods.

[0044] Step 202: Using a pre-built data processing platform, identify the business units associated with the data to be queried.

[0045] In some embodiments, the aforementioned executing entity can utilize a pre-built data processing platform to determine the business units associated with the data to be queried. The data processing platform processes indicators and their corresponding data through three levels: business domain, business theme, and business unit. Each business domain corresponds to at least one business theme, each business theme corresponds to at least one business unit, and each business unit corresponds to at least one data indicator. Here, a business domain can refer to a business area. For example, a business domain could be a business area related to the target enterprise's development. For instance, a business area could be an enterprise business area or a business area related to user health. A business theme can be theme information planned for different business areas. Each business theme includes at least one business indicator. For example, a logistics-related business area could correspond to a delivery theme, a warehouse theme, etc. The business indicator information included in a transaction theme could be: order number indicator, number of transactions indicator, transaction amount indicator, etc. An outbound business unit corresponds to indicators such as outbound time indicator, outbound status indicator, outbound order number indicator, number of outbound items indicator, and outbound item name indicator.

[0046] Step 203: Obtain the pre-established detailed table corresponding to the above business unit.

[0047] In some embodiments, the aforementioned executing entity may obtain a pre-established detailed table corresponding to the aforementioned business unit via a wired or wireless connection. This detailed table records data information for various indicators within the aforementioned business unit.

[0048] It should be noted that the aforementioned wireless connection methods may include, but are not limited to, 3G / 4G / 5G connections, WiFi connections, Bluetooth connections, WiMAX connections, Zigbee connections, UWB (ultra wideband) connections, and other currently known or future wireless connection methods.

[0049] Step 204: Generate the data to be queried based on the above detailed table and the above data requirements.

[0050] In some embodiments, the executing entity may generate the data to be queried based on the detailed table and the data requirements. For example, the executing entity may sequentially filter the data from each indicator in the detailed table based on the data requirements.

[0051] In some optional implementations of certain embodiments, generating the data to be queried based on the above-mentioned detailed table and the above-mentioned data requirement information may include the following steps:

[0052] The first step is to summarize the above dimension tables and detail tables to generate a data summary table.

[0053] The second step is to filter the data in the data summary table according to the above data requirements to obtain the data to be queried.

[0054] Optionally, the dimension tables and detail tables corresponding to the above business units are continuously updated according to a predetermined time period.

[0055] In some optional implementations of certain embodiments, the business domains, business themes, business units, metrics, and data in the data processing platform described above are added through the following steps:

[0056] The first step is to obtain the target data from the data source. This data source consists of reports from various production systems, which continuously submit data daily. The data sources originate from both production systems and user-reported systems. For example, item information is entered into the procurement and sales database, and the user order process involves transmitting messages through various interfaces, which are then stored in the database.

[0057] The second step is to determine whether there exists a business domain in each business domain of the aforementioned data processing platform that is associated with the target data and can be considered as a second target business domain. For example, the executing entity can determine this by querying relevant databases.

[0058] The third step is to determine, in response to the determination that the second target business domain exists, to determine the various business subject sets associated with the second target business domain. As an example, in response to the determination that the second target business domain exists, the executing entity can determine the various business subject sets associated with the second target business domain by querying the relevant database.

[0059] The fourth step is to determine whether a business topic associated with the target data exists in each business topic set associated with the second target business domain as the second target business topic. For example, the executing entity can determine this by querying relevant databases.

[0060] Fifth, in response to determining the existence of the aforementioned second target business topic, the respective business units associated with the aforementioned second target business topic are identified. As an example, in response to determining the existence of the aforementioned second target business topic, the executing entity may query the relevant database to identify the respective business units associated with the aforementioned second target business topic.

[0061] The sixth step is to determine whether any of the business units associated with the aforementioned second target business topic are business units related to the aforementioned target data and thus qualify as second target business units. For example, the executing entity can query relevant databases to determine whether any of the business units associated with the aforementioned target data are business units associated with the aforementioned target data and thus qualify as second target business units.

[0062] Step 7: In response to the confirmation that the second target business unit exists, the target data is added to the detail table corresponding to the second target business unit according to a predetermined time.

[0063] As an example, such as Figure 3 As shown, the target data can be: "Today's shipment information for target items of Tongyi Logistics". Then, the data processing platform has a corresponding business domain: "Logistics Domain". Next, based on the target data and the "Logistics Domain", the data processing platform can be identified as having a corresponding business theme: "Transaction Theme". Furthermore, based on the target data and the "Transaction Theme", the data processing platform can be identified as having a corresponding business unit: "Shipping Business Unit". Finally, the aforementioned target data is added to the detail table corresponding to the aforementioned "Shipping Business Unit".

[0064] Optionally, the above steps also include:

[0065] The first step is to add the second target business topic to each business topic associated with the second target business domain in response to the determination that the second target business topic does not exist.

[0066] The second step is to add the aforementioned second target business unit to the business units associated with the aforementioned second target business theme.

[0067] The third step is to create at least one indicator corresponding to the aforementioned second target business unit and a detailed table associated with the aforementioned second target business unit.

[0068] The fourth step is to add the data indicator information corresponding to the target data to the detailed table associated with the second target business unit according to the predetermined time, and to store at least one indicator corresponding to the second target business unit.

[0069] Optionally, the above steps also include:

[0070] The first step is to add the second target business unit to each business unit associated with the second target business topic in response to the determination that the second target business unit does not exist.

[0071] The second step is to create at least one indicator corresponding to the aforementioned second target business unit and a detailed table associated with the aforementioned second target business unit.

[0072] The third step is to add the data indicator information corresponding to the target data to the detailed table associated with the second target business unit according to the predetermined time, and to store at least one indicator corresponding to the second target business unit.

[0073] The various embodiments of this disclosure have the following beneficial effects: the data generation method of some embodiments of this disclosure can efficiently and accurately generate query data related to the data requirement information through a data processing platform and data requirement information. Specifically, the generated data is not reasonable or effective enough, resulting in low efficiency and accuracy. Based on this, the data generation method of some embodiments of this disclosure can first obtain the data requirement information of the query data as the basis for generating the query data. Then, using a pre-built data processing platform, the business units associated with the query data are determined. The data processing platform processes the indicators and the corresponding data through three levels: business domain, business theme, and business unit. The business domain corresponds to at least one business theme, the business theme corresponds to at least one business unit, and the business unit corresponds to at least one data indicator. Here, the data processing platform can efficiently and accurately process the data through the three levels of business domain, business theme, and business unit, making the data more refined. In practice, the data processing platform also links the data corresponding to each link through business scenarios. Then, a pre-established detailed table corresponding to the business unit is obtained. Finally, based on the detailed tables corresponding to the aforementioned business units and the aforementioned data requirements, the data to be queried can be accurately generated. Therefore, this method can efficiently and accurately generate query data related to the data requirements using a data processing platform and data requirements information.

[0074] Continue to refer to Figure 4 The diagram illustrates a flow 400 of another embodiment of the data generation method according to this disclosure. This data generation method includes the following steps:

[0075] Step 401: Obtain the data requirements information for the data to be queried.

[0076] Step 402: Using a pre-built data processing platform, determine the business domain associated with the above-mentioned data to be queried as the first target business domain.

[0077] In some embodiments, the executing entity (e.g. Figure 1 The electronic device 101 shown can use a pre-built data processing platform to determine the business domain associated with the above-mentioned data to be queried as the first target business domain.

[0078] Step 403: Based on the above data requirements, use the above data processing platform to determine the business theme associated with the first target business domain as the first target business theme.

[0079] In some embodiments, the aforementioned executing entity may, based on the aforementioned data requirement information and using the aforementioned data processing platform, determine the business subject associated with the aforementioned first target business domain as the first target business subject.

[0080] Step 404: Based on the above data requirements, use the above data processing platform to determine the business units associated with the above first target business theme.

[0081] In some embodiments, the aforementioned executing entity may determine the business unit associated with the aforementioned first target business topic by utilizing the aforementioned data processing platform, based on the aforementioned data requirement information.

[0082] Step 405: Obtain the pre-established detailed table corresponding to the above business unit.

[0083] Step 406: Generate the above-mentioned data to be queried based on the above-mentioned detailed table and the above-mentioned data requirements.

[0084] In some embodiments, the specific implementation of steps 401 and 405-406 and the resulting technical effects can be found in [reference needed]. Figure 2 Steps 201 and 203-204 in the corresponding embodiments will not be repeated here.

[0085] from Figure 4 It can be seen from this that, with Figure 2 Compared to the description of some corresponding embodiments, Figure 4 The data generation method flow 400 in some corresponding embodiments embodies the steps of determining the business unit associated with the aforementioned data to be queried. Thus, the schemes described in these embodiments enable the data processing platform to process data efficiently and accurately through three levels: business domain, business theme, and business unit, resulting in more refined data. In practice, the data processing platform also links the data corresponding to each stage through business scenarios.

[0086] Continue to refer to Figure 5 As an implementation of the methods described in the above figures, this disclosure provides some embodiments of a data generation apparatus, which are similar to... Figure 2 Corresponding to the above-described method embodiments, the device can be specifically applied to various electronic devices.

[0087] like Figure 5As shown, a data generation apparatus 500 in some embodiments includes: a first acquisition unit 501, a determination unit 502, a second acquisition unit 503, and a generation unit 504. The first acquisition unit 501 is configured to acquire data requirement information of the data to be queried. The determination unit 502 is configured to use a pre-built data processing platform to determine the business unit associated with the data to be queried. The data processing platform processes indicators and their corresponding data through three levels: business domain, business theme, and business unit. Each business domain corresponds to at least one business theme, each business theme corresponds to at least one business unit, and each business unit corresponds to at least one data indicator. The second acquisition unit 503 is configured to acquire a pre-established detail table corresponding to the business unit. The detail table records data information of each indicator within the business unit. The generation unit 504 is configured to generate the data to be queried based on the detail table and the data requirement information.

[0088] In some optional implementations of certain embodiments, the determining unit 502 of the data generation apparatus 500 may be further configured to: use a pre-built data processing platform to determine a business domain associated with the data to be queried as a first target business domain; use the data processing platform to determine a business theme associated with the first target business domain as a first target business theme based on the data requirement information; and use the data processing platform to determine a business unit associated with the first target business theme based on the data requirement information.

[0089] In some optional implementations of certain embodiments, the generation unit 504 of the data generation apparatus 500 may be further configured to: summarize the aforementioned dimension table and the aforementioned detail table to generate a data summary table; and filter the data in the aforementioned data summary table according to the aforementioned data requirement information to obtain the aforementioned data to be queried.

[0090] In some optional implementations of certain embodiments, the business domains, business themes, business units, metrics, and data in the data processing platform are added through the following steps: obtaining target data from a data source; determining whether a business domain associated with the target data exists as a second target business domain in each business domain of the data processing platform; in response to determining the existence of the second target business domain, determining each set of business themes associated with the second target business domain; determining whether a business theme associated with the target data exists as a second target business theme in each set of business themes associated with the second target business domain; in response to determining the existence of the second target business theme, determining each business unit associated with the second target business theme; determining whether a business unit associated with the target data exists as a second target business unit in each set of business units associated with the second target business theme; and in response to determining the existence of the second target business unit, adding the target data to the detail table corresponding to the second target business unit according to a predetermined time. In some optional implementations of certain embodiments, the decision tree is one of the following: a decision tree that determines the attribute to be partitioned based on information gain, a decision tree that determines the attribute to be partitioned based on information gain ratio, or a decision tree that determines the attribute to be partitioned based on the Gini coefficient.

[0091] In some optional implementations of certain embodiments, the data generation apparatus 500 further includes: in response to determining that the second target business topic does not exist, adding the second target business topic to each business topic associated with the second target business domain; adding the second target business unit to the business unit associated with the second target business topic; creating at least one indicator corresponding to the second target business unit and a detail table associated with the second target business unit; adding data indicator information corresponding to the target data to the detail table associated with the second target business unit according to a predetermined time, and storing at least one indicator corresponding to the second target business unit.

[0092] In some optional implementations of certain embodiments, the data generation apparatus 500 further includes: in response to determining that the second target business unit does not exist, adding the second target business unit to each business unit associated with the second target business topic; creating at least one indicator corresponding to the second target business unit and a detailed table associated with the second target business unit; adding data indicator information corresponding to the target data to the detailed table associated with the second target business unit according to a predetermined time, and storing at least one indicator corresponding to the second target business unit.

[0093] In some optional implementations of certain embodiments, the dimension table and the detail table corresponding to the above-mentioned business unit are continuously updated according to a predetermined time period.

[0094] It is understandable that the units described in the device 500 are related to the reference. Figure 2 The steps in the described method correspond accordingly. Therefore, the operations, features, and beneficial effects described above for the method also apply to the device 500 and the units contained therein, and will not be repeated here.

[0095] Reference below Figure 6 It shows a schematic diagram of the structure of an electronic device 600 suitable for implementing some embodiments of the present disclosure. Figure 6 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments of this disclosure.

[0096] like Figure 6 As shown, electronic device 600 may include a processing device (e.g., a central processing unit, a graphics processor, etc.) 601, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 602 or a program loaded from storage device 608 into random access memory (RAM) 603. RAM 603 also stores various programs and data required for the operation of electronic device 600. Processing device 601, ROM 602, and RAM 603 are interconnected via bus 604. Input / output (I / O) interface 605 is also connected to bus 604.

[0097] Typically, the following devices can be connected to I / O interface 605: input devices 606 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 607 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 608 including, for example, magnetic tapes, hard disks, etc.; and communication devices 609. Communication device 609 allows electronic device 600 to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 6 An electronic device 600 with various devices is shown; however, it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed alternatively. Figure 6 Each box shown can represent a device or multiple devices as needed.

[0098] In particular, according to some embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, some embodiments of this disclosure include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 609, or installed from a storage device 608, or installed from a ROM 602. When the computer program is executed by the processing device 601, it performs the functions defined above in the methods of some embodiments of this disclosure.

[0099] It should be noted that, in some embodiments of this disclosure, the computer-readable medium described above may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium may be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In some embodiments of this disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In some embodiments of this disclosure, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0100] In some implementations, clients and servers can communicate using any currently known or future-developed network protocol such as HTTP (Hypertext Transfer Protocol) and can interconnect with digital data communication (e.g., communication networks) of any form or medium. Examples of communication networks include local area networks (“LANs”), wide area networks (“WANs”), the Internet (e.g., the Internet of Things), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future-developed networks.

[0101] The aforementioned computer-readable medium may be included in the aforementioned device or may exist independently, not assembled into the electronic device. The aforementioned computer-readable medium carries one or more programs that, when executed by the electronic device, cause the electronic device to: acquire data requirement information for the data to be queried; utilize a pre-built data processing platform to determine the business unit associated with the data to be queried, wherein the data processing platform processes indicators and the data corresponding to the indicators through three levels: business domain, business theme, and business unit; the business domain corresponds to at least one business theme, the business theme corresponds to at least one business unit, and the business unit corresponds to at least one data indicator; acquire a pre-established detail table corresponding to the business unit, wherein the detail table records data information for each indicator in the business unit; and generate the data to be queried based on the detail table and the aforementioned data requirement information.

[0102] Computer program code for performing operations of some embodiments of this disclosure can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0103] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0104] The units described in some embodiments of this disclosure can be implemented in software or hardware. The described units can also be housed in a processor; for example, a processor may be described as including a first acquisition unit, a determining unit, a second acquisition unit, and a generating unit. The names of these units do not necessarily limit the specific unit; for example, the second acquisition unit may also be described as "a unit that acquires a pre-established detail table corresponding to the aforementioned business unit."

[0105] The functions described above in this document can be performed, at least in part, by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: Field Programmable Gate Arrays (FPGAs), Application-Specific Integrated Circuits (ASICs), Application Standard Products (ASSPs), System-on-Chip (SoCs), Complex Programmable Logic Devices (CPLDs), and so on.

[0106] The above description is merely a selection of preferred embodiments of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in the embodiments of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described inventive concept. For example, technical solutions formed by substituting the above-described features with (but not limited to) technical features with similar functions disclosed in the embodiments of this disclosure.

Claims

1. A data generation method, comprising: Retrieve the data requirements information for the data to be queried; Using a pre-built data processing platform, business units associated with the data to be queried are identified. The data processing platform processes indicators and the data corresponding to the indicators through three levels: business domain, business theme, and business unit. Each business domain corresponds to at least one business theme, each business theme corresponds to at least one business unit, and each business unit corresponds to at least one data indicator. Obtain the pre-established detailed table corresponding to the business unit, wherein the detailed table records the data information of each indicator in the business unit; The process of generating the data to be queried based on the detailed table and the data requirements includes: summarizing the dimension table and the detailed table to generate a data summary table; and filtering the data in the data summary table according to the data requirements to obtain the data to be queried.

2. The method according to claim 1, wherein, The step of using a pre-built data processing platform to determine the business units associated with the data to be queried includes: Using a pre-built data processing platform, the business domain associated with the data to be queried is identified as the first target business domain; Based on the data requirements, the data processing platform is used to determine the business theme associated with the first target business domain as the first target business theme; Based on the data requirements, the data processing platform is used to determine the business units associated with the first target business theme.

3. The method according to claim 1, wherein, The business domains, business themes, business units, metrics, and data in the data processing platform are added through the following steps: Retrieve target data from the data source; Determine whether there exists a business domain associated with the target data in each business domain of the data processing platform as a second target business domain; In response to determining the existence of the second target business domain, determine the various business topic sets associated with the second target business domain; Determine whether there exists a business topic associated with the target data in each business topic set associated with the second target business domain as the second target business topic; In response to determining that the second target business topic exists, the various business units associated with the second target business topic are determined; Determine whether there is a business unit associated with the target data among the various business units associated with the second target business topic as the second target business unit; In response to the determination that the second target business unit exists, the target data is added to the detail table corresponding to the second target business unit according to a predetermined time.

4. The method according to claim 3, wherein, The method further includes: In response to determining that the second target business topic does not exist, the second target business topic is added to each business topic associated with the second target business domain; Add the second target business unit to the business units associated with the second target business topic; Create at least one indicator corresponding to the second target business unit and a detailed table associated with the second target business unit; According to a predetermined time, the data indicator information corresponding to the target data is added to the detail table associated with the second target business unit, and at least one indicator corresponding to the second target business unit is stored.

5. The method according to claim 3, wherein, The method further includes: In response to determining that the second target business unit does not exist, the second target business unit is added to each business unit associated with the second target business topic; Create at least one indicator corresponding to the second target business unit and a detailed table associated with the second target business unit; According to a predetermined time, the data indicator information corresponding to the target data is added to the detail table associated with the second target business unit, and at least one indicator corresponding to the second target business unit is stored.

6. The method according to claim 2, wherein, The dimension table and the detail table corresponding to the business unit are continuously updated according to a predetermined time period.

7. A data generation apparatus, comprising: The first acquisition unit is configured to acquire the data requirement information of the data to be queried. The determining unit is configured to use a pre-built data processing platform to determine the business unit associated with the data to be queried. The data processing platform processes the indicators and the data corresponding to the indicators through three levels: business domain, business theme, and business unit. The business domain corresponds to at least one business theme, the business theme corresponds to at least one business unit, and the business unit corresponds to at least one data indicator. The second acquisition unit is configured to acquire a pre-established detail table corresponding to the business unit, wherein the detail table records the data information of each indicator in the business unit; The generation unit is configured to generate the data to be queried based on the detail table and the data requirement information, including: summarizing the dimension table and the detail table to generate a data summary table; and filtering the data in the data summary table according to the data requirement information to obtain the data to be queried.

8. An electronic device, comprising: one or more processors; Storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors cause the one or more processors to implement the method as described in any one of claims 1-6.

9. A computer-readable medium having a computer program stored thereon, wherein, When the program is executed by the processor, it implements the method as described in any one of claims 1-6.

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