DETAILED ACTION
Amendment submitted January 2, 2026 has been considered by examiner. Claims 1-20 and 61-87 are pending.
Response to Arguments
Applicant's arguments filed January 2, 2026 have been fully considered but they are not persuasive.
The Applicant states that the cited art does not disclose “aggregate information from the similar columns and generate a unified report of the information across the first table and the second table based on the common data characteristic, wherein the unified report includes a non tabular visualization that aggregates information from the first table and the second table into a single, unified view," "present, via the user interface, the unified report in a manner associating the aggregate information from the similar columns for presentation in a non-tabular, dashboard view that is independent of new format different from the first table and the second table, the dashboard view including at least one graphical indication of the aggregated numerical data and at least one graphical-user element configured to enable interaction with the aggregated information,""wherein the at least one graphical-user element includes a selectable portion of the graphical indication representing a subset of the aggregated information, and responsive to selection of that portion, presents, within the dashboard view, underlying items from both the first table and the second table that contribute to the selected subset, with edits made to those listed underlying items applied back to the first table and the second table,""wherein in addition to the numerical data, the new format includes at least one graphic indication of the numerical data and at least one graphical user element, and wherein the manner of associating the aggregate information involves treating information contained in the similar columns as having a unified identity," and "upon user activation of the at least one graphical-user element, presenting corresponding items of the first table or the second table in a pop-up display within the new dashboard view format, and wherein particular cells displayed within the dashboard view new format are mirrored across corresponding cells of the first table and the second table to enable a change in data in the particular cells to cause a data change in the corresponding cells of the first table or the second table." The Examiner respectfully disagrees.
A response to the above argued features is found below in the order presented.
aggregate information from the similar columns and generate a unified report of the information across the first table and the second table based on the common data characteristic, wherein the unified report includes a non-tabular visualization that aggregates information from the first table and the second table into a single, unified view - Murray discloses [0111-0114] identifying columns in order to determine a relationship between the columns (i.e. similarity); Also, see at least Folting [0024, 0031] for aggregating similar columns and display results of the aggregation; Moreover, see at least Viegas [0033] for presenting similar type of information together (i.e. unified report). Furthermore, Folting teaches aggregate information from the similar columns (Folting, Figures 3A-B, [0024] [0031] whereas data analysis program 104 may provide aggregate column labels 412A, 412B for each column header area, according to one embodiment); Furthermore, Viegas [0032-0034, 0060] discloses aggregating data together to provide a unified report by at least providing charts of aggregated data. Providing at least a chart is in a format that is a “non-tabular new format different from the first table and the second table.”
present, via the user interface, the unified report in a non-tabular, dashboard view that is independent of new format different from the first table and the second table, the dashboard view including at least one graphical indication of the aggregated numerical data and at least one graphical-user element configured to enable interaction with the aggregated information – Viegas [0034, 0048] discloses aggregating data in at least a chart. Such a chart may be interacted with by the user, “Any interaction with the suggested bar chart 206…”
wherein the at least one graphical-user element includes a selectable portion of the graphical indication representing a subset of the aggregated information, and responsive to selection of that portion, presents, within the dashboard view, underlying items from both the first table and the second table that contribute to the selected subset, with edits made to those listed underlying items applied back to the first table and the second table – A new reference, Lee [0061, 0082], is brought in to show that once a chart is modified, the underlying data is modified as well.
wherein in addition to the numerical data, the new format includes at least one graphic indication of the numerical data and at least one graphical user element, and wherein the manner of associating the aggregate information involves treating information contained in the similar columns as having a unified identity – The Examiner would like to point out that the first portion of this argued limitation has been struck-out by the Applicant. As to the part that remains, the instant specification in para [0082] describes it as “having unified identity such that the data in the similar columns are summarized, aggregated, or reported in a single identity.” In view of the definition, see at least Murray [0111-0114] identifying columns in order to determine a relationship between the columns (i.e. similarity). Also, see Folting [Figs. 3A-3B, 0024, 0031] describes at least aggregating similar columns and display results of the aggregation. Such aggregation meets the above description of the unified entity.
upon user activation of the at least one graphical-user element, presenting corresponding items of the first table or the second table in a pop-up display within the new dashboard view format, and wherein particular cells displayed within the dashboard view new format are mirrored across corresponding cells of the first table and the second table to enable a change in data in the particular cells to cause a data change in the corresponding cells of the first table or the second table – The Examiner would like to point out that some of the argued features, such as at least the “pop-up display” has been struck-out by the Applicant. As to the part that remains, see at least Lee [0061, 0082] to show that once a chart is modified, the underlying data is modified as well. Also, see Srivastava (Fig. 17, Col 15 ln 15-38) discloses propagating a change (i.e mirroring) to each cell in different tables.
No further specific arguments are provided.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-20, 61-70, 72, 74-77, 79-80, 82 and 86-87 are rejected under 35 U.S.C. 103 as being unpatentable over Murray et al (US Patent Application Publication 2018/0075115) in view of Folting (US Patent Application Publication 2010/0205521) further in view of Viegas et al (US Patent Application Publication 2018/0088753) further in view of Srivastava et al (US Patent 11,086,894) and further in view of Lee et al (US Patent Application Publication 2017/0300545).
As to Claims 1, 11 and 19, Murray teaches a system for merging data from differing tables, the system comprising:
at least one processor (Murray, Figure 25, [0045] whereas one or more processors) configured to:
maintain a data structure including a plurality of tables, each table of the plurality of tables including a plurality of rows and columns, with each of the plurality of columns having an associated column heading (Murray, [0059] whereas data structures including, without limitation, an array, a record, a relational database table, a hash table, a linked list, or other types of data structures, whereas data enrichment request can identify a data source and/or particular data such as tables, columns, files, or any other structured or unstructured data, and [0085] whereas column heading);
receive a request to consolidate information from at least two of the plurality of tables, wherein the at least two of the plurality of tables include similar columns with differing headings and a common data type, wherein the differing headings differ in at least one of content, format, language, font, shading, color, textual meaning, or semantic meaning, and wherein the similar columns include a first column of a first table of the at least two of the plurality of tables and a second column of a second table of the at least two of the plurality of tables (Murray, [0110] whereas data discovery engine 344 can process datasets from multiple data sources to determine a relationship between the datasets, whereas datasets may be processed as ingested from data sources, whereas all or a portion of any two datasets (tables) may be compared to identify a relationship, whereas the relationships between any two compared datasets may be used to determine one or more recommendations for merging (joining, blending, or aggregating) the data sets together, in conjunction with Figure 1, [0037] whereas data sources 104 such as particular tables, datasets, etc.);
perform an analysis to determine that data in the similar columns share a common data characteristic (Murray, [0035] whereas data from disparate sources can be ingested, analyzed, and processed to determine a relationship between the data [0062] whereas profile engine 326 can perform a column by column analysis of normalized data to identify the types of data stored in the columns), the analysis including at least one of:
searching for and comparing first metadata associated with the first column and second metadata associated with the second column to determine that the first metadata and the second metadata correspond to a common data type (Murray, [0076] whereas in some embodiments, data that is unstructured may be processed to analyze metadata-describing attributes in the data, whereas metadata itself may indicate information about the data, whereas metadata may be compared to identify similarities and/or to determine a type of the information, whereas the information identified based on the data may be compared to know types of data to identify the corresponding data); [[ analyzing content of the first column and content of the second column to determine that a data format corresponds to a predetermined template (Murray, [0006] whereas data in a particular format, such as tabular format (read on predetermined template), may aide in the identification and presentation of options for merging data); analyzing cells of the first column and the second column to determine that the cells of the first column and the second column share a common value (Murray, Figures 6A-B); OR analyzing column headings of the first column and the second column to determine that the column headings of the first column and the second column share a common value and to determine that corresponding non-heading cells of the first column and the second column share the common data type (Murray, Figures 6A-B); ]]
Murray does not explicitly teach aggregate information from the similar columns and generate a unified report of the information across the first table and the second table based on the common data characteristic, wherein the unified report includes a non-tabular visualization that aggregates information from the first table and the second table into a single, unified view; and wherein the manner of associating the aggregate information involves treating information contained in the similar columns as having a unified identity.
However, Murray discloses [0111-0114] identifying columns in order to determine a relationship between the columns (i.e. similarity); Also, see at least Folting [0024, 0031] for aggregating similar columns and display results of the aggregation; Moreover, see at least Viegas [0033] for presenting similar type of information together (i.e. unified report) and see at least Viegas [0033] for a non-tabular visualization. Furthermore, Folting teaches aggregate information from the similar columns (Folting, Figures 3A-B, [0024] [0031] whereas data analysis program 104 may provide aggregate column labels 412A, 412B for each column header area, according to one embodiment). Also, see Folting [Figs. 3A-3B, 0024, 0031] describes at least aggregating similar columns and display results of the aggregation. Such aggregation meets the above description of the unified entity.
Thus, it would have been obvious to one of ordinary skill in the art BEFORE the effective filling date of the claimed invention to combine the teachings since Folting and Murray are in the same field of endeavor such as data processing, data analysis and data summarization – to provide method and system which provide aggregation function on columns or rows (Folting, [0024]).
Murray alone does not explicitly disclose present, via the user interface, the unified report in a non-tabular, dashboard view that is independent of new format different from the first table and the second table, the dashboard view including at least one graphical indication of the aggregated numerical data and at least one graphical-user element configured to enable interaction with the aggregated information.
However, Murray [0110] discloses presenting data from different tables, but not necessarily only numerical data. The type of data presented is considered non-functional descriptive data because the overall functionality of displaying data does change based on type of data being displayed. Furthermore, it would have been obvious for one of ordinary skill in the art before the effective filing date to modify Murray to display numerical data if that is would be underlying data being analyzed.
Moreover, Viegas [Fig. 2, Fig. 6, 0028, 0034] discloses aggregating at least numeric data; Viegas [Figs. 2-3] also discloses displaying a graphic indication that shows at least numeric data. Furthermore, Viegas [0032-0034, 0060] discloses aggregating data together to provide a unified report by at least providing charts of aggregated data. Providing at least a chart is in a format that is a “non-tabular” format.
As such, it would have been obvious for one of ordinary skill in the art before the effective filing date to modify Murray with Viegas. One would have been motivated to do so in order to view aggregated data in a particular format such as a chart, pie, etc.
Murray alone does not explicitly disclose wherein the at least one graphical-user element includes a selectable portion of the graphical indication representing a subset of the aggregated information, and responsive to selection of that portion, presents, within the dashboard view, underlying items from both the first table and the second table that contribute to the selected subset, with edits made to those listed underlying items applied back to the first table and the second table.
However, Lee [0061, 0082] discloses that once a chart is modified, the underlying data is modified as well.
As such, it would have been obvious for one of ordinary skill in the art before the effective filing date to modify Murray with Lee. One would have been motivated to do so in order to be able to manipulate data in a particular format.
Murray alone does not explicitly disclose wherein particular cells displayed within the dashboard view are mirrored across corresponding cells of the first table or the second table to enable a change in data in the particular cells to cause a data change in the corresponding cells of the first table or the second table.
However, see at least Lee [0061, 0082] to show that once a chart is modified, the underlying data is modified as well. Also, see Srivastava (Fig. 17, Col 15 ln 15-38) discloses propagating a change (i.e mirroring) to each cell in different tables.
As such, it would have been obvious for one of ordinary skill in the art before the effective filing date to modify Murray with Lee and Srivastava. One would have been motivated to do so in order to make sure that changes are propagated throughout a system for most up to date data.
As to Claims 2 and 12, Murray as modified teaches wherein the at least one processor is further configured to identify the common data type through an identification of similar terms used in the similar columns (Murray, Figure 19, [0094] whereas determine the semantic similarity between two or more datasets [0097]).
As to Claim 3, Murray as modified teaches wherein the common data characteristic is a location in a common pre-stored library of related terms (Murray, [0065] whereas default name may include a name that is pre-determined, [0093] whereas data includes related data, e.g., location, etc. can be identified to enrich the dataset with the related data).
As to Claims 4 and 13, Murray as modified teaches wherein the at least one processor is configured to enable association of at least two of the plurality of columns having dissimilar headings (Murray, [0012] whereas joining the first dataset with the second dataset by columns in a different column pair of the plurality of column pairs).
As to Claims 5 and 14, Murray as modified teaches wherein the at least one processor is further configured to enable association of at least two of the plurality of columns containing data having dissimilar data characteristics (Murray, [0009] whereas merging or joining data from different datasets,).
As to Claims 6 and 15, Murray as modified teaches wherein the at least one processor is further configured to enable disassociation of at least two of the plurality of columns sharing common data characteristics (Murray, [0140] whereas a column pair is excluded based on determining that no join can be performed between the columns in the column pair, whereas the profile data may be used to make such a determination that there is no data overlap, or possibility of a join between columns in a column pair, [0148] whereas script may be executed against datasets from having a similar relationship).
As to Claims 7 and 16, Murray as modified teaches wherein the at least one processor is further configured to determine that at least two of the plurality of columns are similar based on shared column characteristics (Murray, [0151] whereas relationship may be identified for similar datasets).
As to Claims 8, 17 and 20, Murray as modified teaches wherein the column characteristics include relative column positions (Murray, [0012] whereas a method may include identifying, based on the first profile metadata and second profile metadata, a plurality of column pairs between the first dataset and the second dataset, where columns in each of the plurality of column pairs have a relationship, [0013] whereas the columns in the first column pairs are joined between the first dataset and the second dataset that read on relative column positions).
As to Claims 9 and 18, Murray as modified teaches wherein the column characteristics include data type contained in the at least two of the plurality of columns (Murray, [0042] whereas NL processors determine the type of data in a particular column, name the column, and/or provide metadata describing the columns).
As to Claim 10, Murray as modified teaches wherein the at least one processor is further configured to cause a presentation of default options for merging column data (Murray, [0009] whereas system can provide an intuitive way to enable provide options for merging or joining data, whereas representation may further illustrate one or more types of joins and information about the data, such as rows where data may be joined based on the type of join for the relationship by columns).
As to Claim 61, Murray as modified teaches wherein the at least one processor is configured to determine that the data in the similar columns share the common data characteristic by analyzing content of the similar columns and determining that the data in the similar columns shares a common content characteristic (Folting, [0024] whereas Figure 3A illustrates data in similar column shares a common content characteristic such as data values for the types "BICYCLES," COMPUTERS," "TOASTERS," etc. are aggregated under the category of "NON-FOOD," while the data values for types "MEAT," "PASTA," "SPICES," etc. are aggregated under the category "FOOD.", whereas the column header area 308 comprises labels for quarters columns which roll-up into their respective years).
As to Claim 62, Murray as modified teaches wherein the at least one processor is configured to determine that the data in the similar columns does not share a common content characteristic, and to present an option to review and select alternative columns for use as alternative similar columns (Folting, [0022] whereas data analysis program 104 may further allow the user to specify multiple, distinct sets of row label fields and/or column label fields, allowing the data analysis program to display multiple row header areas and multiple column header areas in the summary table ).
As to Claim 63, Murray as modified teaches wherein the at least one processor is further configured to output the aggregation of information in graphical form within the dashboard view (Folting, Figures 3-5, [0031] whereas the summary of Figure 4 illustrates a graphical display of aggregation of information. Also, see Viegas [0032-0034).
As to Claim 64, Murray as modified teaches wherein the at least one processor is further configured to: in response to a change in the at least two of the plurality of tables, update the aggregation of information (Folting, Figures 3-6, [0029] whereas Figure 3B illustrates table level operations applied to the summary table 304, such as table level data filters, modification of the selected data value fields, or application of summarization functions to the data values); and alter the graphical display to present the updated aggregation of information (Folting, Figures 3-6, [0029] whereas modification of the selected data value fields, or application of summarization functions to the data values, will equally affect all row header areas 306A, 306B of the summary table, according to a further embodiment).
As to Claim 65, Murray as modified teaches determine a subset of columns, from the plurality of columns, sharing similarities, and merging column data from the subset of columns (Murray, Figure 19, [0094] whereas determine the semantic similarity between two or more datasets [0097]).
As to Claim 66, Murray as modified teaches wherein the user interface includes one of a floating panel, a popup window, a drop-down menu, or a webpage [See at least Viegas [0035]].
As to Claim 67, Murray as modified teaches wherein the text classification further includes determining a score for the common data characteristic and determining that the score exceeds a particular threshold (Murray [0140] describes at least using a threshold score to identify similar characteristics.)
As to Claim 68, Murray as modified in view of Viegas teaches wherein the at least two of the plurality of tables include similar columns with differing headings and a common data type, the common data type having one or more dissimilar characteristics, and wherein the at least one processor is configured to associate the similar columns with differing headings and aggregate data from the similar columns despite the one or more dissimilar characteristics (Murray [0140] describes at least using a threshold score to identify similar characteristics; And Viegas [0045] discloses associating columns with different heading (which means at least dissimilar characteristics) and Viegas [Fig. 2, Fig. 6, 0028, 0034] discloses aggregating at least such data.]
As to Claim 69: Murray as modified in view of Srivastava teaches wherein the at least one processor is configured to cause the data change in the corresponding cells of the first table or the second table in response to the change in data in the particular cells, without providing a simultaneous display of the first table or the second table [See at least Srivastava (Col 15 ln 15-38) for propagating a change (i.e mirroring) to each cell in different tables. The data is not displayed simultaneously).
As to Claim 70: Murray as modified in view of Srivastava teaches wherein the at least one processor is configured to cause changes to the particular cells based on changes to the corresponding cells, without providing a simultaneous display of the dashboard view [See at least Srivastava (Col 15 ln 15-38) for propagating a change (i.e mirroring) to each cell in different tables. The data is not displayed simultaneously).
As to Claim 75: Murray as modified in view of Folting teaches wherein the at least one processor is further configured such that upon user activation of the at least one graphical user element, the aggregate information in the unified report is adjusted by a user selection of a third column from the first or second table that is different from the first column or the second column (Folting, Figures 3A-B, [0031]. Multiple columns may be selected for aggregation. Each additional data point for aggregation will change aggregated results.]
As to Claim 79: Murray as modified in view of Folting teaches receiving input for causing the change in the data in the particular cells [0029].
As to Claim 80: Murray as modified in view of Viegas teaches presenting an updated unified report following the receipt of the input [0032-0034, 0060]
As to Claim 82: Murray as modified further discloses wherein the at least one processor is further configured to determine a data type of each column in the at least two of the plurality of tables using natural language processing [0042].
As to Claim 86: Murray as modified in view of Folting further discloses wherein treating information contained in the similar columns as having a unified identity comprises generating metadata that associates differing column headings and/or values with a common semantic category, the metadata being used as a query layer to select underlying items from the first and second tables for aggregation without creating an interim merged table [See at least Murray [0097] for semantic similarity and Murray [0110] for merging sets together without an interim table. Merging is a query operation.]
Claim 87: Murray as modified in view of Viegas teaches wherein the dashboard view simultaneously visualizes consolidated data derived from both the first and the second tables, rather than presenting the tables side-by-side [0020].
Claims 72, 74 and 76-77 are rejected under 35 U.S.C. 103 as being unpatentable over Murray et al (US Patent Application Publication 2018/0075115) in view of Folting (US Patent Application Publication 2010/0205521) further in view of Viegas et al (US Patent Application Publication 2018/0088753) further in view of Srivastava et al (US Patent 11,086,894) further in view of Lee et al (US Patent Application Publication 2017/0300545) and further in view of Reminick et al (US Patent Application Publication 2016/0335604).
As to Claim 72: Murray as modified does not explicitly disclose wherein the at least one processor is further configured such that the at least one graphic indication is rendered on a calendar and associated with at least one particular calendar day
However, Reminck [0043] discloses a calendar view of underlying data.
As such, it would have been obvious for one of ordinary skill in the art before the effective filing date to modify Murray with Reminick. One would have been motivated to do so in order to provide a user a desired way of displaying information.
As to Claim 74: Murray as modified in view of Reminck teaches at least a first graphic indication of the numerical data and a second graphic indication of the numerical data, wherein the first graphic indication is rendered to appear different from the second graphic indication [Fig. 4]. [See at least different types of numbers on a calendar grid.]
As to Claim 76: Murray as modified in view of Reminck teaches wherein the dashboard view at least partially overlays the new format [Fig. 4].
As to Claim 77: Murray as modified in view of Reminck teaches wherein the dashboard view is presented as a display overlaying the user interface [Fig. 4].
Claim 71 is rejected under 35 U.S.C. 103 as being unpatentable over Murray et al (US Patent Application Publication 2018/0075115) in view of Folting (US Patent Application Publication 2010/0205521) further in view of Viegas et al (US Patent Application Publication 2018/0088753) further in view of Srivastava et al (US Patent 11,086,894) further in view of Lee et al (US Patent Application Publication 2017/0300545) and further in view of Deodhar et al (US Patent Application Publication 2014/0058801).
As to Claim 71: Murray as modified does not explicitly disclose wherein the common data characteristic is a calendar-related data characteristic, and wherein the dashboard view further provides a high- level summary including aggregate calendar-related information common to the first table and the second table.
However, Deodhar [0204] discloses aggregating calendar-related data from different calendaring applications.
As such, it would have been obvious for one of ordinary skill in the art before the effective filing date to modify Murray with Deodhar. One would have been motivated to do so in order to view aggregated data from different applications in order to track particular data such as at least time spent working.
Claim 73 is rejected under 35 U.S.C. 103 as being unpatentable over Murray et al (US Patent Application Publication 2018/0075115) in view of Folting (US Patent Application Publication 2010/0205521) further in view of Viegas et al (US Patent Application Publication 2018/0088753) further in view of Srivastava et al (US Patent 11,086,894) further in view of Lee et al (US Patent Application Publication 2017/0300545) and further in view of Choe (US Patent Application Publication 2015/0046209).
As to Claim 73: Murray as modified does not explicitly disclose wherein the at least one processor is further configured such that corresponding items of the first table or the second table are displayed upon user activation of the activatable graphical user element, and wherein the calendar is updated via a manipulation of the displayed corresponding items of the first table or second table.
However, Choe [0026, 0059] discloses viewing and updating a calendar entry. The entries do not exist in a vacuum, but rather stored in at least data structures such as tables.
As such, it would have been obvious for one of ordinary skill in the art before the effective filing date to modify Murray with Choe. One would have been motivated to do so in order to make sure that a calendar contains latest and accurate data.
Claim 78, 81 and 83 are rejected under 35 U.S.C. 103 as being unpatentable over Murray et al (US Patent Application Publication 2018/0075115) in view of Folting (US Patent Application Publication 2010/0205521) further in view of Viegas et al (US Patent Application Publication 2018/0088753) further in view of Srivastava et al (US Patent 11,086,894) further in view of Lee et al (US Patent Application Publication 2017/0300545) and further in view of Church et al (US Patent Application Publication 2020/0401583).
As to Claim 81: Murray as modified does not explicitly disclose wherein the user interface displays default options for selecting columns having the determined common data characteristic.
However, Church [Fig 4H, 0040] discloses a user selecting columns for a report. The columns are default as it is what is available to the user. The columns also have common data characteristic because they contain information about people (i.e. First and Last name, Location options, etc.).
As such, it would have been obvious for one of ordinary skill in the art before the effective filing date to modify Murray with Church. One would have been motivated to do so in order to provide a user options for selection of data to generate a report.
As to Claim 83: Murray as modified in view of Viegas and Church discloses wherein the request to consolidate information includes a user selection of a subset of the numerical data via a floating panel, popup window, drop-down menu, or webpage display [See Murray [0110] as discussed above for consolidating information; See Viergas [Fig. 2, Fig. 6, 0028, 0034] discloses aggregating at least numeric data; And see Church [Fig 4H, 0040], for the same reasons as above, for a user selecting data with at least a webpage display.]
As to Claim 78: Murray as modified in view Church, for the same reasons as above, discloses in response to a selection of an alternative data type via the floating panel, popup display, drop-down menu or webpage display adjusting the information aggregated from the first table and the second table presented in the unified report based on the selection of the alternative data type [Murray [0042] discloses identifying different data type; Viegas [Fig. 2, Fig. 6, 0028, 0034] discloses aggregating at least such data; Also see Church Fig 4H, 0040] for where a user selects different data in a webpage and the report is presented based on the different data.]
Claim 84 is rejected under 35 U.S.C. 103 as being unpatentable over Murray et al (US Patent Application Publication 2018/0075115) in view of Folting (US Patent Application Publication 2010/0205521) further in view of Viegas et al (US Patent Application Publication 2018/0088753) further in view of Srivastava et al (US Patent 11,086,894) further in view of Lee et al (US Patent Application Publication 2017/0300545) and further in view of Donaldson et al (US Patent Application Publication 2021/0019374).
Claim 84: Murray as modified does not explicitly disclose wherein determining that the similar columns share the common data characteristic includes using natural language processing to identify similar terms across different languages.
However, Donaldson [0116] discloses processing natural language strings and identifying similar terms in different languages.
As such, it would have been obvious for one of ordinary skill in the art before the effective filing date to modify Murray with Donaldson. One would have been motivated to do so in order to provide accurate output for a user.
Claim 85 is rejected under 35 U.S.C. 103 as being unpatentable over Murray et al (US Patent Application Publication 2018/0075115) in view of Folting (US Patent Application Publication 2010/0205521) further in view of Viegas et al (US Patent Application Publication 2018/0088753) further in view of Srivastava et al (US Patent 11,086,894) further in view of Lee et al (US Patent Application Publication 2017/0300545) and further in view of Bendig et al (US Patent Application Publication 2017/0140047).
Claim 85: Murray as modified does not explicitly disclose wherein the dashboard includes a floating panel, popup window, or drop-down menu for selecting column data types and columns.
However, Bendig [0041] discloses using a pop-up menu to select columns and its data.
As such, it would have been obvious for one of ordinary skill in the art before the effective filing date to modify Murray with Bendig. One would have been motivated to do so in order to visualize particular user specified data.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/ALEX GOFMAN/Primary Examiner, Art Unit 2163