Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
The Amendment filed on 01/12/26 has been received and entered. Application No. 18/765,791 of which claim 1-20 are pending in the application, all of which are ready for examination by the examiner.
Continued Examination under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 01/12/2026 has been entered.
Response to Amendment
Applicant’s arguments and remarks necessitated new grounds of rejection.
Applicant’s response, filed on 01/12/26, with respect to 101 rejections of claims 1-20 have been fully considered but are not persuasive. The rejections are maintained.
Response to Arguments
Applicant's arguments with respect to 35 USC § 101 rejections of claims 1-20 have been fully considered but they are not persuasive. Applicant made the following arguments:
Regarding claims 1-20, Applicant argues “Applicant respectfully submits that the claimed features above cannot practically be performed in the mind of a person, even with the help of a "general purpose computer." For example, the human mind cannot practically perform the steps of "receiving, by an extract, transform, and load engine, a request from a user account for specified data from a predetermined table of a database, the request including the predetermined table and an output file format," "accessing the database and navigating to the predetermined table of the database," "extracting the specified data from the predetermined table of the database and storing the specified data in temporary memory of a computing device executing the extract, transform, and load engine," "organizing the specified data in the temporary memory according to the output file format to create an output file containing the specified data as organized," and "storing the output file in a data storage other than the temporary memory, the data storage being accessible by a second computing device associated with the user account". The human mind, even with access to a general purpose computer, cannot practically perform the steps recited above, especially, extracting data from a table and storing the data into temporary memory of a computing device, organizing that data in the temporary memory to create an output file according to the output file format, and then store the output file in long term storage such as a hard drive or the like. Because the steps above cannot practically be performed in the mind of a person, the claims do not recite a mental process per MPEP 2106.04(a)(2)(11l)(A)”.
Examiner respectfully disagrees. The claimed limitations accessing the database and navigating to the predetermined table of the database; organizing the specified data in the temporary memory according to the output file format, as drafted, are processes that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting “method…,” nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the “method…,” “of “accessing…, organizing…,” in the context of these claims encompass the user manually accessing database, organizing specified data. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea. With respect to Applicant’s arguments on "receiving, by an extract, transform, and load engine, a request from a user account for specified data from a predetermined table of a database, the request including the predetermined table and an output file format", these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea. Therefore, Applicant’s arguments are not persuasive. See 101 rejections below.
Regarding claims 1-20, Applicant argues “Applicant respectfully submits that the claimed features reflect an improvement to existing migration and validation tools or systems by storing the data that is being validated from both the source database 116 and the target database 120 into temporary memory, organizing the data in the memory to be in the selected file format, and then generating the output file an storing that into long term memory on the hard drive. This unconventional means of validating migrated data integrates any alleged abstract idea into a practical application thereof because it provides a unique way of extracting, organizing, and outputting the validation data in a way that does not impact the source and destination databases and operates in a fast and efficient manner by utilizing temporary memory on the computing device”.
Examiner respectfully disagrees. The claimed limitations accessing the database and navigating to the predetermined table of the database; organizing the specified data in the temporary memory according to the output file format, as drafted, are processes that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting “method…,” nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the “method…,” “of “accessing…, organizing…,” in the context of these claims encompass the user manually accessing database, organizing specified data. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea. With respect to Applicant’s arguments on "the claimed features provide an improvement to existing migration tools or systems by responding to requests for specified data (that includes the output file format for the response to the request) with extracting the specified data, organizing it in a way that conforms with the requested output file format, and then storing the output file in a data store for the user that requested the data to obtain the data", – receiving…, extracting…, storing…, create…. limitations are insignificant extra-solution activity (mere data gathering and outputting, please see MPEP 2106.05g). Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The additional elements “receiving”, “extracting”, “storing”, and “create” is a well-understood, routine, and conventional activity (data gathering and outputting, see MPEP 2106.05d). The additional elements, individually and in combination cannot provide an inventive concept. Therefore, Applicant’s arguments are not persuasive. The claims are not patent eligible. Examiner points that improvement cannot be part of the abstract idea itself. See 101 rejections below.
Applicant’s arguments with respect to 35 USC § 103 rejections of claims 1-20 have been fully considered but are moot because the arguments do not apply to any of the references being used in the current rejection.
Claim Rejections - 35 USC §101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim 1 recites accessing the database and navigating to the predetermined table of the database; organizing the specified data in the temporary memory according to the output file format.
The limitations of accessing…, organizing…, as drafted, are processes that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting “method…,” nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the “method…,” “of “accessing…, organizing…,” in the context of these claims encompass the user manually accessing database, organizing specified data. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim only recites additional elements – receiving…, extracting…, storing…, create…. The “receiving”, “extracting”, “storing”, and “create” limitations are insignificant extra-solution activity (mere data gathering and outputting, please see MPEP 2106.05g). Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The additional elements “receiving”, “extracting”, “storing”, and “create” is a well-understood, routine, and conventional activity (data gathering and outputting, see MPEP 2106.05d). The additional elements, individually and in combination, also do not amount to significantly more than the abstract idea.
The claims 2, 9 and 17 recite wherein the specified data includes one or more predetermined columns of data from the predetermined table of the database. The limitations only recite additional elements at a high level of generality. The limitations only recite additional elements recited at a high level of generality. Accordingly, this additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea. The additional elements, individually and in combination, also do not amount to significantly more than the abstract idea.
The claims 3 and 10 recite wherein the database is a source database or a target database, wherein the source database is the database from which data has been migrated, and the target database is the database to which data has been migrated. The limitations only recite additional elements at a high level of generality. The limitations only recite additional elements recited at a high level of generality. Accordingly, this additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea. The additional elements, individually and in combination, also do not amount to significantly more than the abstract idea.
The claims 4 and 11 recite wherein a portion of the data migrated from the source database to the target database is tokenized such that the portion of the data in the target database that should correspond to a second portion of data in the source database has been masked with a tokenized version of the second portion of data from the source database. The limitations only recite additional elements at a high level of generality. The limitations only recite additional elements recited at a high level of generality. Accordingly, this additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea. The additional elements, individually and in combination, also do not amount to significantly more than the abstract idea.
The claim 5 recites wherein the source database is a first type of database and the destination database is a second type of database different from the first type of database. The limitations only recite additional elements at a high level of generality. The limitations only recite additional elements recited at a high level of generality. Accordingly, this additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea. The additional elements, individually and in combination, also do not amount to significantly more than the abstract idea.
The claims 6, 13 and 20 recite wherein the file format for the specified data is selected from one of comma separated value (CSV), Java script object notation (JSON), and Parquet file formats. The limitations only recite additional elements at a high level of generality. The limitations only recite additional elements recited at a high level of generality. Accordingly, this additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea. The additional elements, individually and in combination, also do not amount to significantly more than the abstract idea.
The claim 7 recites wherein the portion of the data that is tokenized in the target database includes confidential data that is untokenized in the second portion of the data in the source database; and wherein the request is a request for the confidential data from the source database. The limitations only recite additional elements at a high level of generality. These limitations are recited at a high-level of generality (i.e., organizing, storing) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea. The additional elements, individually and in combination, also do not amount to significantly more than the abstract idea.
The claim 8 recites process a request from a user device for specified data from one or more tables of a source database or a target database, the request including identifiers of the one or more tables and an output file format of an output file to be created using the specified data; query the source database or the target database and identify one of the one or more tables within the source database or the target database.
The limitations of process…, query…, identify…, as drafted, are processes that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting “apparatus…,” nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the “apparatus…,” “of “process…, query…, identify…,” in the context of these claims encompass the user manually process a request, query database, identify one or more tables. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim only recites additional elements – retrieve…, create…, store…. The “retrieve”, “create”, and “store” limitations are insignificant extra-solution activity (mere data gathering and outputting, please see MPEP 2106.05g). Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The additional elements “retrieve”, “create”, and “store” is a well-understood, routine, and conventional activity (data gathering and outputting, see MPEP 2106.05d). The additional elements, individually and in combination, also do not amount to significantly more than the abstract idea.
The claims 12 and 19 recite wherein the source database is a first type of database and the destination database is a second type of database different from the first type of database. The limitations only recite additional elements at a high level of generality. The limitations only recite additional elements recited at a high level of generality. Accordingly, this additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea. The additional elements, individually and in combination, also do not amount to significantly more than the abstract idea.
The claim 14 recites wherein the portion of the data that is tokenized in the target database includes confidential data that is untokenized in the second portion of the data in the source database; and wherein the request is a request for untokenized confidential data from the source database. The limitations only recite additional elements at a high level of generality. These limitations are recited at a high-level of generality (i.e., creating) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea. The additional elements, individually and in combination, also do not amount to significantly more than the abstract idea.
The claim 15 recites wherein the output file is stored in a cloud server. The limitations only recite additional elements at a high level of generality. The limitations only recite additional elements recited at a high level of generality. Accordingly, this additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea. The additional elements, individually and in combination, also do not amount to significantly more than the abstract idea.
The claim 16 recites process a request from a user device for specified data from one or more tables of a database, the request including identifiers of the one or more tables and an output file format of an output file to be created using the specified data; query the database and identify one of the one or more tables within the source database or the target database; organize the specified data according to the output file format.
The limitations of process…, query…, identify…, organize…, as drafted, are processes that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting “storage medium…,” nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the “storage medium…,” “of “process…, query…, identify…, organize…,” in the context of these claims encompass the user manually process a request, query database, identify one or more tables, organize specified data. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim only recites additional elements – retrieve…, store…, create…. The “retrieve”, “store”, and “create” limitations are insignificant extra-solution activity (mere data gathering and outputting, please see MPEP 2106.05g). Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The additional elements “retrieve”, “store”, and “create” is a well-understood, routine, and conventional activity (data gathering and outputting, see MPEP 2106.05d). The additional elements, individually and in combination, also do not amount to significantly more than the abstract idea.
The claim 18 recite wherein the database is a source database or a target database; wherein the source database is the database from which data has been migrated, and the target database is the database to which data has been migrated; and wherein a portion of the data migrated from the source database to the target database is tokenized such that the portion of the data in the target database that should correspond to a second portion of data in the source database has been masked with a tokenized version of the second portion of data from the source database. The limitations only recite additional elements at a high level of generality. The limitations only recite additional elements recited at a high level of generality. Accordingly, this additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea. The additional elements, individually and in combination, also do not amount to significantly more than the abstract idea.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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 of this title, 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 1-3, 5, 6, 8-10, 12, 13, 15-17, 19, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Bhide et al. (U.S. PGPub 2015/0134699; hereinafter “Bhide”) in view of Mundlapundi et al. (U.S. PGPub 2014/0358845; hereinafter “Mundlapundi”).
As per claim 1, Bhide discloses a method comprising: receiving, by an extract, transform, and load engine, a request from a user account for specified data from a predetermined table of a database, the request including the table; (See paras. 17, 23, wherein request to server, processing request are disclosed, also See para. 48, wherein Extract, Transform, and Load (ETL) tools are disclosed; as taught by Bhide.)
accessing the database and navigating to the table of the database; (See Fig. 2, paras. 17, 20-23, wherein providing data access are disclosed; as taught by Bhide.)
However, Bhide fails to disclose extracting the specified data from the predetermined table of the database and storing the specified data in temporary memory of a computing device executing the extract, transform, and load engine; organizing the specified data in the temporary memory according to the output file format to create an output file containing the specified data as organized; and storing the output file in a data storgge other than the temporary memory, the data storage being accessible by a second computing device associated with the user account.
On the other hand, Mundlapudi teaches extracting the specified data from the predetermined table of the database and storing the specified data in temporary memory of a computing device executing the extract, transform, and load engine; (See paras. 38, 41, wherein data warehouse and process of extracting a part of data stream (analogous to specific data) in which “one or more extract processes select a part of data stream 202 to be considered. This part of data stream 202 may subsequently be transformed, by executing one or more processes to manipulate the extracted data” [0038] and “specialized analytical tools 210 are configured to extract data from a data warehouse. Advantageously, compatibility processing module 206 facilitates the use of specialized analytical tools 210 configured for use with proprietary data warehouse 208 and on open-source data warehouse” [0041] are disclosed, also See paras. 44-47, wherein ETL processes and storing data stream in volatile memory (i.e. RAM) in which “DFS 306 stores part, or all, of data stream 202 in volatile memory, such as random access memory (RAM), that is cleared by a power cycle or other reboot operation” [0044] and “Open-source distribution processing module 304 may have a parallel processing module 310, configured to execute one or more map and reduce processes on data stored in distributed file system” [0046] are disclosed; as taught by Mundlapudi.)
organizing the specified data in the temporary memory according to the output file format to create an output file containing the specified data as organized; (See Fig. 7, paras. 38, 41, wherein data warehouse and process of extracting a part of data stream (analogous to specific data) in which “one or more extract processes select a part of data stream 202 to be considered. This part of data stream 202 may subsequently be transformed, by executing one or more processes to manipulate the extracted data” [0038] and “specialized analytical tools 210 are configured to extract data from a data warehouse. Advantageously, compatibility processing module 206 facilitates (analogous to organizing) the use of specialized analytical tools 210 configured for use with proprietary data warehouse 208 and on open-source data warehouse” [0041] are disclosed also See paras. 35, 67, wherein formatting of data, compatibility processing module functions in which “formatting processes executed on a table of data points representative of a dataset, wherein the one or more formatting processes rank the rows of the table according to a single value (metric) associated with each row. Compatibility processing module 206 may iterate through the rows of a received dataset…compatibility processing module 206 may assign a rank value to the row. In one example implementation, a single-metric rank process 600 may output a ranked dataset table such as dataset table” [0067], as taught by Mundlapudi.)
and storing the output file in a data storage other than the temporary memory, the data storage being accessible by a second computing device associated with the user account. (See Fig. 9, paras. 48, 68, 75-76, wherein storing data process in which “Open-source data warehouse 204 includes storage 324, for storing the refined, or parsed data from the ETL processing module 322, wherein storage 324 may be one or more storage devices consolidated in a single server rack, or distributed across a LAN, WAN, the Internet, or any other communication network. The storage devices may be nonvolatile storage devices, such as HDDs, SSDs, optical disks, storage tapes, ROM and the like” [0048] are disclosed, also See paras. 40, 83, wherein organizing different media into hybrid storage system process and compatibility processing module functions on allowing user, implementing open-source solutions while coordinating data using proprietary data warehouse are disclosed; as taught by Mundlapudi.)
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the Mundlapundi teachings in the Bhide system. Skilled artisan would have been motivated to incorporate data warehouse compatibility taught by Mundlapudi in the Bhide system for efficient data movement from a database to a distributed file system. In addition, both of the references (Bhide and Mundlapudi) teach features that are directed to analogous art and they are directed to the same field of endeavor, such as, data consistency. This close relation between both of the references highly suggests an expectation of success.
As per claims 2, 9 and 17, Bhide discloses wherein the specified data includes one or more columns of data from the table of the database. (See paras. 24, 58, 63, wherein columns of table are disclosed; as taught by Bhide.)
However, Bhide fails to disclose predetermined of data from the predetermined table of the database.
On the other hand, Mundlapudi teaches predetermined of data from the predetermined table of the database. (See paras. 47, wherein predetermined patter, structure are disclosed; as taught by Mundlapudi.)
See claims 1, 8, and 16 for motivation.
As per claims 3 and 10, the combination of Bhide and Mundlapudi discloses wherein the database is a source database or a target database, wherein the source database is the database from which data has been migrated, and the target database is the database to which data has been migrated. (See Fig. 2, paras. 18, 21-22, wherein target tables migration of data in tables are disclosed; as taught by Bhide.)
As per claim 5, Bhide fails to disclose wherein the source database is a first type of database and the destination database is a second type of database different from the first type of database.
On the other hand, Mundlapudi teaches wherein the source database is a first type of database and the destination database is a second type of database different from the first type of database. (See paras. 50, 60, wherein process of changing data type of data value (analogous to different database types) are disclosed; as taught by Mundlapudi.)
See claim 1 for motivation.
As per claims 6, 13 and 20, the combination of Bhide and Mundlapudi discloses wherein the output file format for the specified data is selected from one of comma separated value (CSV), Java script object notation (JSON), and Parquet file formats. (See paras. 23-24, wherein CSV file are disclosed; as taught by Bhide.)
As per claims 8 and 16, Bhide discloses a processing circuit; (See Fig. 3, paras. 7, 96, wherein processing unit are disclosed; as taught by Bhide.)
a memory having executable instructions stored thereon, which when executed by the processing circuit, cause the processing circuit to: (See Fig. 3, paras. 7, 96, wherein system memory are disclosed; as taught by Bhide.)
process a request from a user device for specified data from one or more tables of a source database or a target database, the request including identifiers of the one or more tables; (See paras. 17, 23, wherein request to server, processing request are disclosed, also See paras. 48, 89, 121, wherein Extract, Transform, and Load (ETL) tools, security requirements are disclosed; as taught by Bhide.)
query the source database or the target database and identify one of the one or more tables within the source database or the target database; (See paras. 18, 23, wherein querying and managing data in files are disclosed; as taught by Bhide.)
However, Bhide fails to disclose retrieve the specified data from the one table of the source database or the target database and store the specified data in temporary memory of the apparatus; organize the specified data in the temporary memory according to the output file format to create an output file that contains the specified data according to the file requirements; and store the output file in a data storage other than the temporary memory, the data storage being accessible by the user device.
On the other hand, Mundlapudi teaches retrieve the specified data from the one table of the source database or the target database and store the specified data in temporary memory of the apparatus; (See paras. 38, 41, wherein data warehouse and process of extracting a part of data stream (analogous to specific data) in which “one or more extract processes select a part of data stream 202 to be considered. This part of data stream 202 may subsequently be transformed, by executing one or more processes to manipulate the extracted data” [0038] and “specialized analytical tools 210 are configured to extract data from a data warehouse. Advantageously, compatibility processing module 206 facilitates the use of specialized analytical tools 210 configured for use with proprietary data warehouse 208 and on open-source data warehouse” [0041] are disclosed, also See paras. 44-47, wherein ETL processes and storing data stream in volatile memory (i.e. RAM) in which “DFS 306 stores part, or all, of data stream 202 in volatile memory, such as random access memory (RAM), that is cleared by a power cycle or other reboot operation” [0044] and “Open-source distribution processing module 304 may have a parallel processing module 310, configured to execute one or more map and reduce processes on data stored in distributed file system” [0046] are disclosed; as taught by Mundlapudi.)
organize the specified data in the temporary memory according to the output file format to create an output file that contains the specified data according to the file requirements; (See Fig. 7, paras. 38, 41, wherein data warehouse and process of extracting a part of data stream (analogous to specific data) in which “one or more extract processes select a part of data stream 202 to be considered. This part of data stream 202 may subsequently be transformed, by executing one or more processes to manipulate the extracted data” [0038] and “specialized analytical tools 210 are configured to extract data from a data warehouse. Advantageously, compatibility processing module 206 facilitates (analogous to organizing) the use of specialized analytical tools 210 configured for use with proprietary data warehouse 208 and on open-source data warehouse” [0041] are disclosed also See paras. 35, 67, wherein formatting of data, compatibility processing module functions in which “formatting processes executed on a table of data points representative of a dataset, wherein the one or more formatting processes rank the rows of the table according to a single value (metric) associated with each row. Compatibility processing module 206 may iterate through the rows of a received dataset…compatibility processing module 206 may assign a rank value to the row. In one example implementation, a single-metric rank process 600 may output a ranked dataset table such as dataset table” [0067], as taught by Mundlapudi.)
and store the output file in a data storage other than the temporary memory, the data storage being accessible by the user device. (See Fig. 9, paras. 48, 68, 75-76, wherein storing data process in which “Open-source data warehouse 204 includes storage 324, for storing the refined, or parsed data from the ETL processing module 322, wherein storage 324 may be one or more storage devices consolidated in a single server rack, or distributed across a LAN, WAN, the Internet, or any other communication network. The storage devices may be nonvolatile storage devices, such as HDDs, SSDs, optical disks, storage tapes, ROM and the like” [0048] are disclosed, also See para. 83, wherein organizing different media into hybrid storage system process are disclosed; as taught by Mundlapudi.)
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the Mundlapundi teachings in the Bhide system. Skilled artisan would have been motivated to incorporate data warehouse compatibility taught by Mundlapudi in the Bhide system for efficient data movement from a database to a distributed file system. In addition, both of the references (Bhide and Mundlapudi) teach features that are directed to analogous art and they are directed to the same field of endeavor, such as, data consistency. This close relation between both of the references highly suggests an expectation of success.
As per claims 12 and 19, Bhide fails to disclose wherein the source database is a first type of database and the destination database is a second type of database different from the first type of database.
On the other hand, Mundlapudi teaches wherein the source database is a first type of database and the destination database is a second type of database different from the first type of database. (See paras. 50, 60, wherein process of changing data type of data value (analogous to different database types) are disclosed; as taught by Mundlapudi.)
See claims 8 and 16 for motivation.
As per claim 15, the combination of Bhide and Mundlapudi discloses wherein the output file is stored in a cloud server. (See Fig. 3, paras. 75-78, 82, wherein cloud computing environment are disclosed; as taught by Bhide.)
Claims 4, 7, 11, 14, and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Bhide et al. (U.S. PGPub 2015/0134699; hereinafter “Bhide”) in view of Mundlapundi et al. (U.S. PGPub 2014/0358845; hereinafter “Mundlapundi”). and further in view of Parthasarathy (U.S. PGPub 2020/0311304).
As per claims 4 and 11, the combination of Bhide and Mundlapundi fails to disclose wherein a portion of the data migrated from the source database to the target database is tokenized such that the portion of the data in the target database that should correspond to a second portion of data in the source database has been masked with a tokenized version of the second portion of data from the source database.
On the other hand, Parthasarathy teaches wherein a portion of the data migrated from the source database to the target database is tokenized such that the portion of the data in the target database that should correspond to a second portion of data in the source database has been masked with a tokenized version of the second portion of data from the source database. (See Fig. 1, para. 66, wherein integrated platform implemented as on-premise software is disclosed, also See paras. 70, 121, wherein on-premise, cloud computing systems, databases and excluding features are disclosed, also See paras. 98, 111 and 114, wherein the integrated platform providing data security to cloud data sources is disclosed, also See paras. 23, 86 and 89, wherein data tokenization, data anonymization engine and data masking module functions are disclosed; as taught by Parthasarathy.)
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the Parthasarathy teachings in the combination of Bhide and Mundlapundi system. Skilled artisan would have been motivated to incorporate a method of integrating for sensitive data taught by Parthasarathy in the combination of Bhide and Mundlapundi system for efficient data movement from a database to a distributed file system. In addition, both of the references (Bhide, Mundlapundi and Parthasarathy) teach features that are directed to analogous art and they are directed to the same field of endeavor, such as, data consistency. This close relation between both of the references highly suggests an expectation of success.
As per claims 7 and 14, the combination of Bhide and Mundlapundi fails to disclose wherein the portion of the data that is tokenized in the target database includes confidential data that is untokenized in the second portion of the data in the source database; and wherein the request is a request for the confidential data from the source database.
On the other hand, Parthasarathy teaches wherein the portion of the data that is tokenized in the target database includes confidential data that is untokenized in the second portion of the data in the source database; (See paras. 97, 113, 146, wherein organization of data are disclosed, also See paras. 23, 86 and 89, wherein data tokenization, data anonymization engine and data masking module functions are disclosed; as taught by Parthasarathy.)
and wherein the request is a request for the confidential data from the source database. (See paras. 87, 142, wherein output data are disclosed, also See Fig. 11A, paras. 114-115, 134, wherein generating data, results are disclosed, also See paras. 23, 86 and 89, wherein data tokenization, data anonymization engine and data masking module functions are disclosed; as taught by Parthasarathy.)
See claim 4 for motivation.
As per claim 18, the combination of Bhide and Mundlapundi discloses wherein the database is a source database or a target database; (See Fig. 2, paras. 18, 21-22, wherein target tables migration of data in tables are disclosed; as taught by Bhide.)
wherein the source database is the database from which data has been migrated, and the target database is the database to which data has been migrated. (See Fig. 2, paras. 18, 21-22, wherein target tables migration of data in tables are disclosed; as taught by Bhide.)
However, the combination of Bhide and Mundlapundi discloses fails to disclose wherein a portion of the data migrated from the source database to the target database is tokenized such that the portion of the data in the target database that should correspond to a second portion of data in the source database has been masked with a tokenized version of the second portion of data from the source database.
On the other hand, Parthasarathy teaches wherein a portion of the data migrated from the source database to the target database is tokenized such that the portion of the data in the target database that should correspond to a second portion of data in the source database has been masked with a tokenized version of the second portion of data from the source database. (See para. 35, wherein method of replacing sensitive data with tokens is disclosed, also See para. 63, wherein tokenizing data are disclosed, also See paras. 23, 86 and 89, wherein data tokenization, data anonymization engine and data masking module functions are disclosed; as taught by Parthasarathy.)
See claim 4 for motivation.
Conclusion
1. The examiner requests, in response to this Office action, support be shown for language added to any original claims on amendment and any new claims. That is, indicate support for newly added claim language by specifically pointing to page(s) and line no(s) in the specification and/or drawing figure(s). This will assist the examiner in prosecuting the application.
2. When responding to this office action, Applicant is advised to clearly point out the patentable novelty which he or she thinks the claims present, in view of the state of the art disclosed by the references cited or the objections made. He or she must also show how the amendments avoid such references or objections See 37 CFR 1.111(c).
POINT OF CONTACT
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/L. L. H./
Examiner, Art Unit 2153
/KAVITA STANLEY/ Supervisory Patent Examiner, Art Unit 2153