CN112989019A - Data processing method, device, computer system and readable storage medium - Google Patents
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- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
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- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
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Abstract
The embodiment of the disclosure discloses a data processing method, a device, a computer system and a readable storage medium, wherein the data processing method comprises the following steps: acquiring a query request of a user; determining first query data and associated data of the first query data based on the query request; and displaying operable controls of the first query data and the associated data in a visualization area.
Description
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to a data processing method, an apparatus, a computer system, and a readable storage medium.
Background
In the field of big data, the specific analysis of mass data is very important for users in different industries and different fields. However, current data analysis tools require users to have professional data analysis knowledge and skills, and it is difficult for ordinary users to easily and quickly use these data analysis tools to perform more complex data analysis.
Disclosure of Invention
In order to solve the problems in the related art, embodiments of the present disclosure provide a data processing method, an apparatus, a computer system, and a readable storage medium.
In a first aspect, an embodiment of the present disclosure provides a data processing method.
Specifically, the data processing method includes: acquiring a query request of a user by first query data;
determining first query data and associated data of the first query data based on the query request;
and displaying operable controls of the first query data and the associated data in a visualization area.
With reference to the first aspect, in a first implementation manner of the first aspect, the data processing method further includes:
and determining the operable control according to the data dimension of the associated data.
With reference to the first implementation manner of the first aspect, the present disclosure provides in a second implementation manner of the first aspect: the data dimension of the associated data of the first query data comprises any one or more of: a lower level associated data dimension of the first query data, an upper level associated data dimension of the first query data, a same level associated data dimension of the first query data; and/or
The operable control for displaying the associated data comprises: and respectively displaying the corresponding operable controls in the visual area according to a preset analysis mode.
With reference to the second implementation manner of the first aspect, in a third implementation manner of the first aspect, the data processing method further includes: acquiring selection operation of a user on the operable control;
determining one or more particular data dimensions of the associated data based on the selection operation;
determining second query data based on the first query data and the one or more particular data dimensions;
and displaying the second query data in the visualization area.
With reference to the third implementation manner of the first aspect, in a fourth implementation manner of the first aspect, the data processing method further includes: determining associated data of the second query data;
determining a data dimension of associated data of the second query data;
and displaying operable controls of the associated data of the second query data in the visualization area, wherein the operable controls of the associated data of the second query data are determined according to the data dimension of the associated data of the second query data.
With reference to the third implementation manner of the first aspect, in a fifth implementation manner of the first aspect, the determining the one or more specific data dimensions of the associated data includes: determining one or more subordinate associated data dimensions of the first query data; or
Determining one or more sibling associated data dimensions for the first query data; or
Determining one or more superior associated data dimensions of the first query data.
With reference to the first aspect, in a sixth implementation manner of the first aspect, the data processing method further includes: determining a data graph based on the query request, wherein the data graph comprises a plurality of nodes, the nodes correspond to data dimensions, the layout of the nodes represents the hierarchical relationship between the corresponding data dimensions, and connecting lines between the nodes represent the incidence relationship between the corresponding data dimensions;
and displaying the data map in the visualization area, wherein nodes in the data map are displayed as operable controls.
With reference to the sixth implementation manner of the first aspect, in a seventh implementation manner of the first aspect, the displaying the data map includes:
highlighting a first node in the data graph corresponding to a data dimension of the first query data.
With reference to the seventh implementation manner of the first aspect, in an eighth implementation manner of the first aspect, the data processing method further includes: receiving selection operation of a user on corresponding operable controls of one or more other nodes connected with the first node in the displayed data map;
determining a data dimension corresponding to the one or more other nodes based on the selection operation;
determining third query data from the first query data and data dimensions corresponding to the one or more other nodes;
and displaying the third query data.
With reference to the sixth implementation manner of the first aspect, in a ninth implementation manner of the first aspect, the data processing method further includes: in response to a selection operation made by a user of a corresponding operable control of any node in the data map, any one or more of the following items are presented: data dimension corresponding to the arbitrary node, measurement of the arbitrary node, and user operation corresponding to the arbitrary node.
In a second aspect, the disclosed embodiments provide a data processing apparatus.
Specifically, the data processing apparatus includes:
the query request acquisition module is used for acquiring a query request of a user;
a first query data and associated data determination module for determining first query data and associated data of the first query data based on the query request;
and the first query data and operable control display module is used for displaying the first query data and the operable control of the associated data in a visualization area.
First query data
With reference to the second aspect, in a first implementation manner of the second aspect, the data processing apparatus further includes:
and the operable control determining module is used for determining the operable control according to the data dimension of the associated data.
With reference to the first implementation manner of the second aspect, in a second implementation manner of the second aspect, the data dimension of the associated data of the first query data includes any one or more of the following: a lower level associated data dimension of the first query data, an upper level associated data dimension of the first query data, a same level associated data dimension of the first query data; and/or
The operable control for displaying the associated data comprises: and respectively displaying the corresponding operable controls in the visual area according to a preset analysis mode.
With reference to the second implementation manner of the second aspect, in a third implementation manner of the second aspect, the data processing apparatus further includes:
the first user selection operation receiving module is used for acquiring the selection operation of the user on the operable control;
a first data dimension determination module to determine one or more particular data dimensions of the associated data based on the selection operation;
a second query data determination module to determine second query data based on the first query data and the one or more particular data dimensions;
and the second query data display module is used for displaying the second query data in the visualization area.
With reference to the third implementation manner of the second aspect, in a fourth implementation manner of the second aspect, the data processing apparatus further includes:
the associated data determining module is used for determining associated data of the second query data;
a second data dimension determination module, configured to determine a data dimension of the associated data of the second query data;
and the operable control display module is used for displaying the operable control of the associated data of the second query data in the visualization area, and the operable control of the associated data of the second query data is determined according to the data dimension of the associated data of the second query data.
With reference to the third implementation manner of the second aspect, in a fifth implementation manner of the second aspect, the determining the one or more specific data dimensions of the associated data includes:
determining one or more subordinate associated data dimensions of the first query data; or
Determining one or more sibling associated data dimensions for the first query data; or
Determining one or more superior associated data dimensions of the first query data.
With reference to the second aspect, in a sixth implementation manner of the second aspect, the data processing apparatus further includes:
a data graph determining module, configured to determine a data graph based on the query request, where the data graph includes a plurality of nodes, the nodes correspond to data dimensions, a layout of the nodes represents a hierarchical relationship between the corresponding data dimensions, and connecting lines between the nodes represent an association relationship between the corresponding data dimensions;
and the data map display module is used for displaying the data map in the visualization area, and nodes in the data map are displayed as operable controls.
With reference to the sixth implementation manner of the second aspect, in a seventh implementation manner of the second aspect, the displaying the data map includes:
highlighting a first node in the data graph corresponding to a data dimension of the first query data.
With reference to the seventh implementation manner of the second aspect, in an eighth implementation manner of the second aspect, the data processing apparatus further includes:
the second user selection operation receiving module is used for receiving selection operations made by users on corresponding operable controls of one or more other nodes connected with the first node in the displayed data map;
a third data dimension determination module to determine a data dimension corresponding to the one or more other nodes based on the selection operation;
a third query data determination module to determine third query data from the first query data and data dimensions corresponding to the one or more other nodes;
and the third query data display module is used for displaying the third query data.
With reference to the sixth implementation manner of the second aspect, in a ninth implementation manner of the second aspect, the data processing apparatus further includes:
a specific node attribute showing module, configured to, in response to a selection operation made by a user from a corresponding operable control of any node in the data graph, show any one or more of the following: data dimension corresponding to the arbitrary node, measurement of the arbitrary node, and user operation corresponding to the arbitrary node.
In a third aspect, a computer system is provided in an embodiment of the present disclosure. Specifically, the computer system includes: a processor; a memory storing executable instructions that, when executed by the processor, perform the method steps of:
acquiring a query request of a user;
determining first query data and associated data of the first query data based on the query request;
and displaying operable controls of the first query data and the associated data in a visualization area.
With reference to the third aspect, in a first implementation manner of the third aspect, the data processing method further includes:
and determining the operable control according to the data dimension of the associated data.
With reference to the first implementation manner of the third aspect, the present disclosure provides in a second implementation manner of the third aspect: the data dimension of the associated data of the first query data comprises any one or more of: a lower level associated data dimension of the first query data, an upper level associated data dimension of the first query data, a same level associated data dimension of the first query data; and/or
The operable control for displaying the associated data comprises: and respectively displaying the corresponding operable controls in the visual area according to a preset analysis mode.
With reference to the second implementation manner of the third aspect, in a third implementation manner of the third aspect, the data processing method further includes: acquiring selection operation of a user on the operable control;
determining one or more particular data dimensions of the associated data based on the selection operation;
determining second query data based on the first query data and the one or more particular data dimensions;
and displaying the second query data in the visualization area.
With reference to the third implementation manner of the third aspect, in a fourth implementation manner of the third aspect, the data processing method further includes: determining associated data of the second query data;
determining a data dimension of associated data of the second query data;
and displaying operable controls of the associated data of the second query data in the visualization area, wherein the operable controls of the associated data of the second query data are determined according to the data dimension of the associated data of the second query data.
With reference to the third implementation manner of the third aspect, in a fifth implementation manner of the third aspect, the determining the one or more specific data dimensions of the associated data includes: determining one or more subordinate associated data dimensions of the first query data; or
Determining one or more sibling associated data dimensions for the first query data; or
Determining one or more superior associated data dimensions of the first query data.
With reference to the third aspect, in a sixth implementation manner of the third aspect, the data processing method further includes: determining a data graph based on the query request, wherein the data graph comprises a plurality of nodes, the nodes correspond to data dimensions, the layout of the nodes represents the hierarchical relationship between the corresponding data dimensions, and connecting lines between the nodes represent the incidence relationship between the corresponding data dimensions;
and displaying the data map in the visualization area, wherein nodes in the data map are displayed as operable controls.
With reference to the sixth implementation manner of the third aspect, in a seventh implementation manner of the third aspect, the displaying the data map includes:
highlighting a first node in the data graph corresponding to a data dimension of the first query data.
With reference to the seventh implementation manner of the third aspect, in an eighth implementation manner of the third aspect, the data processing method further includes: receiving selection operation of a user on corresponding operable controls of one or more other nodes connected with the first node in the displayed data map;
determining a data dimension corresponding to the one or more other nodes based on the selection operation;
determining third query data from the first query data and data dimensions corresponding to the one or more other nodes;
and displaying the third query data.
With reference to the sixth implementation manner of the third aspect, in a ninth implementation manner of the third aspect, the data processing method further includes: in response to a selection operation made by a user of a corresponding operable control of any node in the data map, any one or more of the following items are presented: data dimension corresponding to the arbitrary node, measurement of the arbitrary node, and user operation corresponding to the arbitrary node.
In a fourth aspect, a computer-readable storage medium is provided in embodiments of the present disclosure.
In particular, the computer-readable storage medium stores executable instructions that, when executed by a processor, implement the method according to any one of the first aspect, the first implementation manner of the first aspect, and the ninth implementation manner of the first aspect.
Drawings
Other labels, objects and advantages of the present disclosure will become more apparent from the following detailed description of non-limiting embodiments when taken in conjunction with the accompanying drawings. In the drawings:
FIG. 1 shows a flow diagram of a data processing method according to an embodiment of the present disclosure;
FIG. 2 shows a flow diagram of a data processing method according to an embodiment of the present disclosure;
FIG. 3a shows a user interface schematic of a data processing method according to an embodiment of the present disclosure;
FIG. 3b shows a user interface schematic of a data processing method according to another embodiment of the present disclosure;
FIG. 4 shows a block diagram of a data processing apparatus according to an embodiment of the present disclosure;
FIG. 5 shows a block diagram of a data processing apparatus according to an embodiment of the present disclosure;
FIG. 6 shows a block diagram of a data processing apparatus according to an embodiment of the present disclosure;
FIG. 7 shows a block diagram of a data processing apparatus according to an embodiment of the present disclosure;
FIG. 8 shows a block diagram of a data processing apparatus according to an embodiment of the present disclosure;
FIG. 9 shows a block diagram of a computer system according to an embodiment of the present disclosure;
fig. 10 shows a schematic structural diagram of a computer system suitable for implementing a data processing method according to an embodiment of the present disclosure.
Detailed Description
Hereinafter, exemplary embodiments of the present disclosure will be described in detail with reference to the accompanying drawings so that those skilled in the art can easily implement them. Also, for the sake of clarity, parts not relevant to the description of the exemplary embodiments are omitted in the drawings.
In the present disclosure, it is to be understood that terms such as "including" or "having," etc., are intended to indicate the presence of the disclosed features, numbers, steps, behaviors, components, parts, or combinations thereof, and are not intended to preclude the possibility that one or more other features, numbers, steps, behaviors, components, parts, or combinations thereof may be present or added.
It should be further noted that the embodiments and features of the embodiments in the present disclosure may be combined with each other without conflict. The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
The embodiment of the disclosure provides a data display method, which enables a user to conveniently perform relatively complex multi-data dimension analysis by operating an operable control for displaying relevant data dimensions of target data, and supports realization of multi-dimensional interactive insight analysis in a complex application scene by means of correlation analysis of superior, subordinate and same-level dimensions of data dimensions.
Fig. 1 shows a flow diagram of a data processing method according to an embodiment of the present disclosure.
As shown in fig. 1, the data processing method includes steps S101 to S103.
In step S101, a query request of a user is acquired;
in step S102, determining first query data and associated data of the first query data based on the query request;
in step S103, the operable controls of the first query data and the associated data are displayed in a visualization area.
According to an embodiment of the present disclosure, the query request of the user may be a voice command issued by the user, a text command input, an option selected from a menu, an identifier clicked in a chart, and the like, but is not limited thereto.
For example, the user's query request may be a voice command "ask for query for brand a football shoe market share". By performing semantic analysis on the query request of the user, it is determined that the first query data that the user needs to obtain is the market share of the brand a football shoe, and therefore, a value of the market share of the brand a football shoe is retrieved from the database, or a value of the market share of the brand a football shoe, for example, 15% is calculated based on the retrieved data, and is used as the first query data.
Alternatively, the user's query request may be the literal instruction "please query for the past 5 years brand football shoe market share under brand a". By performing semantic analysis on the query request of the user, it is determined that the first query data that the user needs to obtain is data of the market share of the brand a football shoes in the last 5 years, and then the value of the market share of the brand a football shoes in the last 5 years can be retrieved from the database, or the value of the market share of the brand a football shoes in the last 5 years can be calculated based on the retrieved data and used as the first query data.
After determining the first query data, association data for the first query data may be determined. For example, for the first query data "value of brand a soccer shoe market share", the associated data may include various data associated with the first query data, such as "brand a soccer shoe market share for each city", "market share of brand a soccer shoes of different sizes", "market share of brand a soccer shoes in people of various age groups", "brand a footwear market share", "respective market share of brand a shoes", and so on.
After determining the associated data of the first query data, an operable control of the associated data may be exposed in the visualization area. The user can conveniently acquire the associated data of the first query data by operating the operable control.
According to an embodiment of the present disclosure, the operable control is further determined according to a data dimension of the associated data. The actionable controls can correspond to data dimensions of the associated data that, when selected by the user, equate to a selection of a data dimension of the associated data. Accordingly, the respective associated data may be determined according to the data dimension of the associated data.
According to an embodiment of the present disclosure, the data dimension of the associated data of the first query data includes any one or more of: a lower level associated data dimension of the first query data, an upper level associated data dimension of the first query data, and a peer level associated data dimension of the first query data.
According to an embodiment of the present disclosure, the lower-level associated data dimension of the first query data may comprise an in-depth analysis dimension of the first query data, e.g., a dimension of a smaller granularity than the dimension of the first query data. For example, when the first query data is a brand a football shoe market share, its subordinate associated data dimensions may include: channels, such as brand a football shoe market share for each channel; city, e.g., brand a football shoe market share for each city; size, e.g., market share of brand a soccer shoes of different sizes; the market share of people, such as brand a soccer shoes, among people of all ages, and so on.
According to an embodiment of the present disclosure, the upper-level associated data dimension of the first query data may include a summary analysis dimension of the first query data, for example, a dimension with a larger granularity than a dimension of the first query data. For example, when the first query data is a brand a football shoe market share, its upper associated data dimensions may include: industries such as brand a footwear market share, and the like.
In accordance with an embodiment of the present disclosure, the sibling associated data dimensions of the first query data may include the same level of granularity of the analysis dimensions of the first query data, e.g., the most closely related dimension with the granularity of the first query data. For example, when the first query data is a brand a soccer shoe market share, its peer associated data dimensions may include: brands, such as other brands football shoe market share; items such as the respective market share of brand a shoes, etc.
The data dimensions of the first query data and the associated data of the first query data may then be presented on a user interface. For example, the text "the brand a soccer shoe market share is 15%" may be displayed, or a chart such as a bar chart, a pie chart, a graph, a multi-dimensional perspective chart, or the like may be displayed in conjunction with other data. At the same time, an operable control corresponding to the data dimension of the associated data of the first query data may also be displayed, and the data dimension of the associated data of the first query data may be, for example, any one or more of the following associated data dimensions of the first query data: a lower level associated data dimension, a same level associated data dimension, and an upper level associated data dimension.
By using the method, the corresponding first query data and the data dimension of the associated data of the first query data can be determined according to the first input of the user, and the operable control of the data dimension is presented to the user, so that convenience is provided for the user to carry out deep and multi-dimensional data analysis.
According to the embodiment of the disclosure, displaying the operable control of the associated data includes displaying the corresponding operable control according to a preset analysis mode. For example, for the analysis mode "drill-up", an operable control of associated data corresponding to an upper-level data dimension of the first query data may be presented, for the analysis mode "drill-down" and "multi-dimensional overlay", an operable control of associated data corresponding to a lower-level data dimension of the first query data may be presented, and for the analysis mode "associated dimension", an operable control of associated data corresponding to a same-level data dimension of the first query data may be presented. Therefore, the user can conveniently select the corresponding data dimension control according to the required operation mode, so that the user without professional knowledge can conveniently use the analysis tool to perform more complex analysis.
Fig. 2 shows a flow diagram of a data processing method according to an embodiment of the present disclosure.
As shown in fig. 2, the data processing method includes steps S104 to S111 in addition to steps S101 to S103 shown in fig. 1;
in step S104, determining the operable control according to the data dimension of the associated data;
in step S105, a selection operation made by a user on the operable control is acquired;
in step S106, determining one or more specific data dimensions of the associated data based on the selection operation;
in step S107, determining second query data based on the first query data and the one or more particular data dimensions;
in step S108, presenting the second query data in the visualization area;
in step S109, determining associated data of the second query data;
in step S110, determining a data dimension of the associated data of the second query data;
in step S111, displaying, in the visualization area, an operable control of the associated data of the second query data, where the operable control of the associated data of the second query data is determined according to a data dimension of the associated data of the second query data.
According to the embodiment of the present disclosure, the selection operation of the user may be a selection operation of the user on the operable control, for example, a selection operation performed by an action such as clicking or dragging on the operable control, and the like, but is not limited thereto.
According to the embodiment of the disclosure, one or more lower-level associated data dimensions of the first query data, or an upper-level associated data dimension of the first query data, or one or more peer-level associated data dimensions of the first query data may be selected according to a selection operation of a user.
According to an embodiment of the present disclosure, the selecting one or more specific associated data dimensions of the first query data comprises: selecting one or more subordinate associated data dimensions of the first query data; or selecting one or more sibling associated data dimensions of the first query data; or selecting one or more superior associated data dimensions of the first query data.
For example, assuming that the first query data is "brand a soccer shoe market share", its subordinate associated data dimension "channel" may be selected for drill-down analysis, thereby determining the second query data "brand a soccer shoe market share of each channel". Alternatively, the lower-level associated data dimensions "channel" and "city" may be selected for multidimensional overlay analysis, thereby determining the second query data "market share of brand a soccer shoes in each city of each channel".
For example, assuming that the first query data is "brand a football shoe market share," its upper associated data dimension "industry" may be selected for upward analysis to determine the second query data "brand a shoe market share. Alternatively, its superior associated data dimension "categories" may be selected for upward analysis to determine the second query data "brand a footwear and apparel market share".
For example, assuming that the first query data is "market share of football shoes of brand a", its peer association data dimension "brand" may be selected for association dimension analysis, thereby determining the second query data "respective market shares of football shoes of other brands". Alternatively, its peer association data dimension "category" may be selected for association dimension analysis to determine the second query data "corresponding market share for each category of footwear under brand A".
According to the embodiment of the present disclosure, after the second query data is determined, the associated data dimension of the second query data can be determined similarly to the case of the first query data.
The second query data and/or associated data dimensions of the second query data and corresponding actionable controls may then be exposed.
By displaying the operable control of the data dimension associated with the target data while displaying the target data, a user can intuitively know which data dimensions the target data is related to, and the user is allowed to conveniently expand and superpose analysis dimensions, switch the dimensions, perform drill-down analysis and cause-finding analysis of the data and the like by operating the operable control, and perform global interactive insight while analyzing.
The data processing method according to the embodiment of the present disclosure further includes determining a data graph based on the query request, where the data graph includes a plurality of nodes, the nodes correspond to data dimensions, a layout of the nodes represents a hierarchical relationship between the corresponding data dimensions, and a connecting line between the nodes represents an association relationship between the corresponding data dimensions; and displaying the data map in the visualization area, wherein nodes in the data map are displayed as operable controls.
According to the embodiment of the present disclosure, an entire graph or a plurality of different data graphs may be formed and stored in advance, or an association relationship between nodes used for forming a graph may be stored, and a suitable data graph or a part of the entire graph may be selected according to a first input of a user, or a data graph may be generated according to an association relationship between nodes. The data map may then be presented to the user. The data map comprises a plurality of nodes, and the nodes correspond to different data dimensions. The hierarchical relationship between the data dimensions is represented by the layout of the nodes. For example, nodes closer to the map center have higher levels, and nodes farther from the map center have lower levels, and nodes equidistant from the common center belong to the same level nodes. The connecting lines between the nodes represent the correlation relationship between the corresponding data dimensions. For example, a node corresponding to the data dimension "market share of a brand football shoe in the past 5 years" and a node having a connection relationship therewith correspond to the data dimension of the upper level, the lower level and the same level of "market share of a brand football shoe in the past 5 years". According to the embodiment of the disclosure, the nodes in the data graph can be displayed as operable controls, so that interactive operation of a user is facilitated.
According to an embodiment of the present disclosure, said displaying said data map comprises: highlighting a first node in the data graph corresponding to a data dimension of the first query data.
And highlighting a first node corresponding to the data dimension of the first query data so as to facilitate subsequent operation of a user.
Fig. 3a shows a user interface schematic of a data processing method according to an embodiment of the present disclosure.
In fig. 3a, the user interface 300 of the data processing method comprises a visualization area comprising: a user input area 310, a first query data presentation area 320, a data map area 330, an actionable controls area 340, an associated data dimension data presentation area 350, and an operational action area 360. It should be noted that the division of the visualization area in fig. 3a is merely exemplary, and the disclosure is not limited thereto.
The user input area 310 is used for a user to perform a query operation, such as inputting query text; the first query data display area 320 is used for displaying first query data obtained based on query text input by a user; the data graph area 330 is configured to display a data graph corresponding to the first query data and the data dimension associated therewith, where the data graph includes nodes displayed as operable controls; the operable control area 340 is used for showing operable controls corresponding to the associated data dimensions of the first query data; the associated data dimension data display area 350 is used for visually displaying the obtained data of the associated data dimension after the user selects the operable control in the operable control area 340; the operation action area 360 is used for the user to perform operations other than data analysis on the data presented on the user interface.
For example, after the user inputs the query text "please query for the market share of brand a football shoes in the last 5 years" in the user input area 310, the first query data is obtained through analysis: the market share of brand a soccer shoes was 15% in the last 5 years, and "shoes/soccer shoes/brand a/5 years market share was 15% is displayed in the first query data display area 320. The data dimension of the first query data is "market share of brand a football shoes in the last 5 years", and a corresponding data map is exhibited in data map area 330.
In data map region 330, the data dimension "Brand A football shoes market share over the last 5 years" corresponds to node 331. The data dimension "last 5 years brand football shoe market share" is the upper level data dimension "last 5 years brand shoe market share", corresponding to node 332. The data dimension "football shoe market share of brand a in the last 5 years" is the same level data dimension as "football shoe market share of each brand in the last 5 years", for example, football shoe market share of a plurality of brands such as brand a, brand B, brand C in the last 5 years, corresponding to node 333-1; and "market share of each item of footwear of brand a in the past 5 years", e.g., market share of soccer shoes, basketball shoes, tennis shoes, etc. of brand a in the past 5 years, corresponds to node 333-2. The lower-level data dimension of the data dimension 'market share of the football shoes of the brand A in the last 5 years' is 'market share of different channels of the football shoes of the brand A in the last 5 years', such as an e-commerce channel, an off-line channel and a corresponding node 334-1; "market share for different cities of brand a soccer shoes in the past 5 years", e.g., first-line city, second-line city, third-line city, corresponding node 334-2; "market share for different sizes of football boots of brand A in the last 5 years", corresponding to node 334-3; "market share of different populations of brand a soccer shoes in the past 5 years", such as children, young, middle-aged, and elderly, corresponds to node 334-4.
In the data map region 330, the relationships of upper level, lower level and same level among nodes are represented in a concentric dotted line circle manner, nodes on the same dotted line circle correspond to the same level data dimension, nodes on the outer layer dotted line circle correspond to the lower level data dimension, and nodes on the inner layer dotted line circle correspond to the upper level data dimension. By presenting the data map to the user, the user can more intuitively understand the association between data and select the desired analysis dimension. In addition, for the data maps with more levels, a user can quickly explore the summary and track the reason down by observing the connecting lines in the maps, and the efficiency of data analysis is obviously improved. Data dimension "last 5 years brand a footwear market share" is the superior data dimension of data dimension "last 5 years brand a soccer footwear market share," with node 331 on dashed circle I and node 332 at the center of the circle. Nodes 333-1, 333-2 corresponding to the sibling data dimension of the data dimension "market share of brand a football shoes in the last 5 years" are on the same dashed circle I as node 331. Nodes 334-1, 334-2, 334-3, 334-4 corresponding to the lower level data dimension of the data dimension "market share of brand a football shoes in the last 5 years" are on the dotted circle II outside the circle I.
In addition to presenting the data map in data map area 330, the actionable controls used for the "multidimensional overlay" analysis of the data dimension "market share of brand a football shoes for the past 5 years" may be presented in actionable controls area 340: channel 344-1, city 344-2, size 344-3, and crowd 344-4 correspond to nodes 334-1, 334-2, 334-3, and 334-4 in data map region 330, respectively. The operable controls used in the "associated dimension" analysis of the data dimension "market share of brand a football shoes for the last 5 years" may also be presented in the operable controls area 340: brand 343-1, category 343-2, correspond to nodes 333-1, 333-2, respectively, in data-graph region 330.
According to the embodiment of the disclosure, a selection operation made on the operable control based on a user is obtained, one or more specific data dimensions in the data dimensions of the associated data are determined based on the selection operation, second query data are determined based on the first query data and the one or more specific data dimensions, and the second query data are displayed in the visualization area.
For example, the user may select a data dimension channel and a city related to the first query data "market share of brand a football shoes in the past 5 years" as the selection operation by selecting "multidimensional overlay" control "channel" 344-1, "city" 344-2 in the operable control area 340, and determine that the second query data is "market share of each city of each channel of brand a football shoes in the past 5 years". The second query data may then be presented, for example, in a graph, in an associated data dimension data presentation area 350.
According to the embodiment of the disclosure, receiving selection operation made by a user on corresponding operable controls of one or more other nodes connected with the first node in the displayed data map; determining a data dimension corresponding to the one or more other nodes based on the selection operation; determining third query data from the first query data and data dimensions corresponding to the one or more other nodes; and displaying the third query data. According to the embodiment of the disclosure, the nodes in the data graph can be displayed as operable controls, and a user can select the data dimension of the corresponding node by selecting the operable controls in the data graph.
For example, the user clicks on node 334-1 and node 334-2 as a selection operation, which is equivalent to selecting the operable control channel 344-1, city 344-2, thereby determining that the third query data is a numerical value of "market share of each city of each channel of brand A football shoes in the past 5 years". In the associated data dimension data presentation area 350, the third query data may be presented, for example, in the form of a graph.
The cause-following analysis of the data can be conveniently carried out through the data map. Links between nodes may indicate associations between data dimensions, with shorter links indicating a higher degree of association. The user can easily find out which leaf nodes are associated with certain data, namely the degree of closeness of the association by observing the connecting lines between the nodes, thereby determining the factors influencing the data.
According to the embodiment of the disclosure, in response to a selection operation made by a user through a corresponding operable control of any node in the data map, any one or more of the following items are displayed: data dimension corresponding to the arbitrary node, measurement of the arbitrary node, and user operation corresponding to the arbitrary node.
For example, the selection operation may be a cursor hovering over a node, although the disclosure is not so limited. For example, when the user hovers the cursor over node 331, the data dimension of node 331 may be shown as "Brand A football shoe market share over the last 5 years," and the metric of node 331 is a percentage.
According to an embodiment of the present disclosure, a user may select an operation action sharing co-worker 361, an addition monitor 362, and the like in the operation action area 360, share a data analysis result to the co-worker, or monitor the data analysis result to obtain real-time data.
By presenting the data map to the user, the user can more intuitively understand the association between data and select the desired analysis dimension. In addition, for the data maps with more levels, a user can quickly explore the summary and track the reason down by observing the connecting lines in the maps, and the efficiency of data analysis is obviously improved.
Fig. 3b shows a user interface schematic of a data processing method according to another embodiment of the present disclosure.
The difference between fig. 3b and fig. 3a is that the operable control area 340 of fig. 3b includes an operable control used in the "drill-down" analysis mode: channel 344-1, city 344-2, size 344-3, and crowd 344-4 correspond to nodes 334-1, 334-2, 334-3, and 334-4 in data map region 330, respectively. The actionable controls area 340 also includes actionable controls for "probe up" analysis: footwear 342, corresponding with node 332 in data-map region 330. The drill-down is used for tracking reasons of a single lower level correlation dimension, and the drill-up is used for totaling of an upper level correlation dimension. For example, when the user selects the operability control channel 344-1, the numerical value of the data dimension "different channel market share for Brand A football shoes over the past 5 years" is presented in the associated data dimension data presentation area 350. The information and operation aiming at different nodes are often different, and by the mode, when a user selects a specific node, various information related to the node and user operation information can be visually displayed, the user does not need to be troubled to look up related documents or manuals, and great convenience is brought to the user.
Fig. 4 shows a block diagram of a data processing apparatus according to an embodiment of the present disclosure.
As shown in fig. 4, a data processing apparatus 400 according to an embodiment of the present disclosure includes:
a query request obtaining module 401, configured to obtain a query request of a user;
a first query data and associated data determination module 402 for determining first query data and associated data of the first query data based on the query request;
a query data and operable control presentation module 403, configured to present the first query data and the operable control of the associated data in a visualization area.
According to an embodiment of the present disclosure, the data dimension of the associated data of the first query data includes any one or more of: a lower level associated data dimension of the first query data, an upper level associated data dimension of the first query data, a same level associated data dimension of the first query data; and/or
The operable control for displaying the associated data comprises: and respectively displaying the corresponding operable controls in the visual area according to a preset analysis mode.
Fig. 5 shows a block diagram of a data processing apparatus according to an embodiment of the present disclosure.
The data processing apparatus 500 in FIG. 5 includes additional modules in addition to the same modules 401-403 as in FIG. 4:
an operable control determining module 404, configured to determine the operable control according to the data dimension of the associated data;
a first user selection operation receiving module 405, configured to obtain a selection operation made by a user on the operable control;
a first data dimension determination module 406 to determine one or more particular data dimensions of the associated data based on the selection operation;
a second query data determination module 407 for determining second query data based on the first query data and the one or more particular data dimensions;
a second query data display module 408, configured to display the second query data in the visualization area;
an associated data determining module 409, configured to determine associated data of the second query data;
a second data dimension determination module 410, configured to determine a data dimension of the associated data of the second query data;
an operable control displaying module 411, configured to display, in the visualization area, an operable control of the associated data of the second query data, where the operable control of the associated data of the second query data is determined according to a data dimension of the associated data of the second query data.
According to an embodiment of the present disclosure, the determining the one or more particular data dimensions of the associated data includes: determining one or more subordinate associated data dimensions of the first query data; or determining one or more sibling associated data dimensions of the first query data; or determining one or more superior associated data dimensions of the first query data.
Fig. 6 shows a block diagram of a data processing apparatus according to an embodiment of the present disclosure.
The data processing apparatus 600 in FIG. 6 comprises, in addition to the same modules 401-403 as in FIG. 4, additional modules:
a data graph determining module 412, configured to determine a data graph based on the query request, where the data graph includes a plurality of nodes, the nodes correspond to data dimensions, a layout of the nodes represents a hierarchical relationship between the corresponding data dimensions, and connecting lines between the nodes represent an association relationship between the corresponding data dimensions;
a data graph displaying module 413, configured to display the data graph in the visualization area, where nodes in the data graph are displayed as operable controls.
According to an embodiment of the present disclosure, said displaying said data map comprises: highlighting a first node in the data graph corresponding to a data dimension of the first query data.
Fig. 7 shows a block diagram of a data processing apparatus according to an embodiment of the present disclosure.
The data processing apparatus 700 in FIG. 7 comprises the same modules 401 to 403, 412, 413 as in FIG. 6, and further comprises additional modules:
a second user selection operation receiving module 414, configured to receive a user selection operation made on a corresponding operable control of one or more other nodes connected to the first node in the displayed data graph;
a third data dimension determination module 415 configured to determine a data dimension corresponding to the one or more other nodes based on the selection operation;
a third query data determination module 416 for determining third query data from the first query data and data dimensions corresponding to the one or more other nodes;
and a third query data display module 417, configured to display the third query data.
Fig. 8 shows a block diagram of a data processing apparatus according to an embodiment of the present disclosure.
The data processing apparatus 800 in FIG. 8 comprises, in addition to the same modules 401 to 403, 412, 413 as in FIG. 6, additional modules:
a node-specific attribute presenting module 418, configured to present, in response to a selection operation made by a user from the corresponding operable control of any node in the data graph, any one or more of the following: data dimension corresponding to the arbitrary node, measurement of the arbitrary node, and user operation corresponding to the arbitrary node.
Fig. 9 shows a block diagram of a computer system according to an embodiment of the present disclosure.
As shown in fig. 9, the computer system 900 may include one or more processors 901 and one or more memories 902. The one or more memories 902 are used to store one or more executable instructions that, when executed by the one or more processors 901, may perform the following steps:
a data processing method, comprising:
acquiring a query request of a user;
determining first query data and associated data of the first query data based on the query request;
and displaying operable controls of the first query data and the associated data in a visualization area.
According to an embodiment of the present disclosure, the steps further include:
and determining the operable control according to the data dimension of the associated data.
According to an embodiment of the present disclosure, the data dimension of the associated data of the first query data includes any one or more of: a lower level associated data dimension of the first query data, an upper level associated data dimension of the first query data, a same level associated data dimension of the first query data; and/or
The operable control for displaying the associated data comprises: and respectively displaying the corresponding operable controls in the visual area according to a preset analysis mode.
According to an embodiment of the present disclosure, the steps further include: acquiring selection operation of a user on the operable control;
determining one or more particular data dimensions of the associated data based on the selection operation;
determining second query data based on the first query data and the one or more particular data dimensions;
and displaying the second query data in the visualization area.
According to an embodiment of the present disclosure, the steps further include: determining associated data of the second query data;
determining a data dimension of associated data of the second query data;
and displaying operable controls of the associated data of the second query data in the visualization area, wherein the operable controls of the associated data of the second query data are determined according to the data dimension of the associated data of the second query data.
According to an embodiment of the present disclosure, the determining the one or more particular data dimensions of the associated data includes:
determining one or more subordinate associated data dimensions of the first query data; or
Determining one or more sibling associated data dimensions for the first query data; or
Determining one or more superior associated data dimensions of the first query data.
According to an embodiment of the present disclosure, the steps further include: determining a data graph based on the query request, wherein the data graph comprises a plurality of nodes, the nodes correspond to data dimensions, the layout of the nodes represents the hierarchical relationship between the corresponding data dimensions, and connecting lines between the nodes represent the incidence relationship between the corresponding data dimensions;
and displaying the data map in the visualization area, wherein nodes in the data map are displayed as operable controls.
According to an embodiment of the present disclosure, said displaying said data map comprises:
highlighting a first node in the data graph corresponding to a data dimension of the first query data.
According to an embodiment of the present disclosure, the steps further include: receiving selection operation of a user on corresponding operable controls of one or more other nodes connected with the first node in the displayed data map;
determining a data dimension corresponding to the one or more other nodes based on the selection operation;
determining third query data from the first query data and data dimensions corresponding to the one or more other nodes;
and displaying the third query data.
According to an embodiment of the present disclosure, the steps further include: in response to a selection operation made by a user of a corresponding operable control of any node in the data map, any one or more of the following items are presented: data dimension corresponding to the arbitrary node, measurement of the arbitrary node, and user operation corresponding to the arbitrary node.
Fig. 10 shows a schematic structural diagram of a computer system suitable for implementing a data processing method according to an embodiment of the present disclosure.
As shown in fig. 10, the computer system 1000 includes a Central Processing Unit (CPU)1001 that can execute various processes in the above-described embodiments in accordance with a program stored in a Read Only Memory (ROM)1002 or a program loaded from a storage section 1009 into a Random Access Memory (RAM) 1003. In the RAM1003, various programs and data necessary for the operation of the system 1000 are also stored. The CPU1001, ROM1002, and RAM1003 are connected to each other via a bus 1004. An input/output (I/O) interface 1005 is also connected to bus 1004.
The following components are connected to the I/O interface 1005: an input section 1006 including a keyboard, a mouse, and the like; an output section 1007 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage portion 1008 including a hard disk and the like; and a communication section 1009 including a network interface card such as a LAN card, a modem, or the like. The communication section 1009 performs communication processing via a network such as the internet. The driver 1010 is also connected to the I/O interface 1005 as necessary. A removable medium 1011 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 1010 as necessary, so that a computer program read out therefrom is mounted into the storage section 1008 as necessary.
In particular, the above described methods may be implemented as computer software programs according to embodiments of the present disclosure. For example, embodiments of the present disclosure include a computer program product comprising a computer program tangibly embodied on a readable medium thereof, the computer program containing program code for performing the above-described data management and/or access methods. In such an embodiment, the computer program may be downloaded and installed from a network through the communication part 1009 and/or installed from the removable medium 1011.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowcharts or block diagrams may represent a module, a program segment, or a portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units or modules described in the embodiments of the present disclosure may be implemented by software or by programmable hardware. The units or modules described may also be provided in a processor, and the names of the units or modules do not in some cases constitute a limitation of the units or modules themselves.
As another aspect, the present disclosure also provides a readable storage medium, which may be a readable storage medium contained in the electronic device or the computer system in the above embodiments; or may be a separately present, non-built-in, readable storage medium. The readable storage medium stores one or more programs for use by one or more processors in performing the methods described in the present disclosure.
The foregoing description is only exemplary of the preferred embodiments of the disclosure and is illustrative of the principles of the technology employed. It will be appreciated by a person skilled in the art that the scope of the invention as referred to in the present disclosure is not limited to the specific combination of the above-mentioned features, but also covers other embodiments formed by any combination of the above-mentioned features or their equivalents without departing from the inventive concept. For example, the above features and (but not limited to) the features disclosed in this disclosure having similar functions are replaced with each other to form the technical solution.
Claims (19)
1. A data processing method, comprising:
acquiring a query request of a user;
determining first query data and associated data of the first query data based on the query request;
and displaying operable controls of the first query data and the associated data in a visualization area.
2. The method of claim 1, further comprising:
and determining the operable control according to the data dimension of the associated data.
3. The method of claim 2, wherein:
the data dimension of the associated data of the first query data comprises any one or more of: a lower level associated data dimension of the first query data, an upper level associated data dimension of the first query data, a same level associated data dimension of the first query data; and/or
The operable control for displaying the associated data comprises: and respectively displaying the corresponding operable controls in the visual area according to a preset analysis mode.
4. The method of claim 3, further comprising:
acquiring selection operation of a user on the operable control;
determining one or more particular data dimensions of the associated data based on the selection operation;
determining second query data based on the first query data and the one or more particular data dimensions;
and displaying the second query data in the visualization area.
5. The method of claim 4, further comprising:
determining associated data of the second query data;
determining a data dimension of associated data of the second query data;
and displaying operable controls of the associated data of the second query data in the visualization area, wherein the operable controls of the associated data of the second query data are determined according to the data dimension of the associated data of the second query data.
6. The method of claim 4, wherein the determining the one or more particular data dimensions of the associated data comprises:
determining one or more subordinate associated data dimensions of the first query data; or
Determining one or more sibling associated data dimensions for the first query data; or
Determining one or more superior associated data dimensions of the first query data.
7. The method of claim 1, further comprising:
determining a data graph based on the query request, wherein the data graph comprises a plurality of nodes, the nodes correspond to data dimensions, the layout of the nodes represents the hierarchical relationship between the corresponding data dimensions, and connecting lines between the nodes represent the incidence relationship between the corresponding data dimensions;
and displaying the data map in the visualization area, wherein nodes in the data map are displayed as operable controls.
8. The method of claim 7, wherein said presenting said data map comprises:
highlighting a first node in the data graph corresponding to a data dimension of the first query data.
9. The method of claim 8, further comprising:
receiving selection operation of a user on corresponding operable controls of one or more other nodes connected with the first node in the displayed data map;
determining a data dimension corresponding to the one or more other nodes based on the selection operation;
determining third query data from the first query data and data dimensions corresponding to the one or more other nodes;
and displaying the third query data.
10. The method of claim 7, further comprising:
in response to a selection operation made by a user of a corresponding operable control of any node in the data map, any one or more of the following items are presented: data dimension corresponding to the arbitrary node, measurement of the arbitrary node, and user operation corresponding to the arbitrary node.
11. A data processing apparatus, comprising:
the query request acquisition module is used for acquiring a query request of a user;
a first query data and associated data determination module for determining first query data and associated data of the first query data based on the query request;
and the first query data and operable control display module is used for displaying the first query data and the operable control of the associated data in a visualization area.
12. The apparatus of claim 11, further comprising:
and the operable control determining module is used for determining the operable control according to the data dimension of the associated data.
13. The apparatus of claim 12, further comprising:
the first user selection operation receiving module is used for acquiring the selection operation of the user on the operable control;
a first data dimension determination module to determine one or more particular data dimensions of the associated data based on the selection operation;
a second query data determination module to determine second query data based on the first query data and the one or more particular data dimensions;
and the second query data display module is used for displaying the second query data in the visualization area.
14. The apparatus of claim 13, further comprising:
the associated data determining module is used for determining associated data of the second query data;
a second data dimension determination module, configured to determine a data dimension of the associated data of the second query data;
and the operable control display module is used for displaying the operable control of the associated data of the second query data in the visualization area, and the operable control of the associated data of the second query data is determined according to the data dimension of the associated data of the second query data.
15. The apparatus of claim 11, further comprising:
a data graph determining module, configured to determine a data graph based on the query request, where the data graph includes a plurality of nodes, the nodes correspond to data dimensions, a layout of the nodes represents a hierarchical relationship between the corresponding data dimensions, and connecting lines between the nodes represent an association relationship between the corresponding data dimensions;
and the data map display module is used for displaying the data map in the visualization area, and nodes in the data map are displayed as operable controls.
16. The apparatus of claim 15, further comprising:
the second user selection operation receiving module is used for receiving selection operations made by users on corresponding operable controls of one or more other nodes connected with the first node in the displayed data map;
a third data dimension determination module to determine a data dimension corresponding to the one or more other nodes based on the selection operation;
a third query data determination module to determine third query data from the first query data and data dimensions corresponding to the one or more other nodes;
and the third query data display module is used for displaying the third query data.
17. The apparatus of claim 15, further comprising:
a specific node attribute showing module, configured to, in response to a selection operation made by a user from a corresponding operable control of any node in the data graph, show any one or more of the following: data dimension corresponding to the arbitrary node, measurement of the arbitrary node, and user operation corresponding to the arbitrary node.
18. A computer system comprising a memory and a processor; wherein the memory is to store one or more computer instructions, wherein the one or more computer instructions are to be executed by the processor to implement the method steps of any one of claims 1-10.
19. A readable storage medium having stored thereon computer instructions, characterized in that the computer instructions, when executed by a processor, carry out the method steps of any of claims 1-10.
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