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 .
Claim Objections
Claim(s) 1, 7-8, 10-13, 15-16 and 20 is/are objected to because of the following informalities:
Claim 1: “…for real time changes” should read “…for real time data changes”
Claim 1: ”…across the data mesh…within the data mesh” should read”…across the real time data mesh…within the real time data mesh”
Claim 1: “…into the data layer…” should read “…into a data layer…”
Claim 8: “…for real time changes, the computerized systems, the one or more computers comprising” should read “…for real time data changes, the one or more computers comprising”
Claim 7/15/20: “…the change data capture process…” should read “…the change data capture mechanisms”
Claim 8: ”…within the data mesh” should read “…within the real time data mesh”.
Claim 10: “…the components” should read “…components”
Claim 11: “…wherein the System of Records” should read “wherein System of Records”
Claim 12:” the system of claim 8, wherein the Data Governance Module…” should read “the system of claim 9, wherein the Data Governance Module…”
Claim 13: “wherein the data layer comprises the Purposive Datastores (PDSes) optimized for efficient retrieval and storage of specific types of data relevant to the supply chain domain” should read “wherein the data layer comprises the one or more Purposive Datastores (PDSes) optimized for efficient retrieval and storage of specific types of data relevant to a supply chain domain”.
Claim 16: “monitoring transactional systems, including ERPs, for real time changes” should read “monitoring transactional systems, including ERPs, for real time data changes”
Claim 1 and 16 implement periods at the end of claim sentence other than the last sentence. These periods should be replaced by either “comma” or a “semi-colon”.
Appropriate correction is required.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 03/06/2026 were considered by the examiner.
Double Patenting
Claims 1-20 of this application is patentably indistinct from claim 1-20 of Application No. 18/349,836. Pursuant to 37 CFR 1.78(f), when two or more applications filed by the same applicant or assignee contain patentably indistinct claims, elimination of such claims from all but one application may be required in the absence of good and sufficient reason for their retention during pendency in more than one application. Applicant is required to either cancel the patentably indistinct claims from all but one application or maintain a clear line of demarcation between the applications. See MPEP § 822.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: “Data Governance Module” in claim 9.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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 a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Claim(s) 1/8/16 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Claim(s) 1/8/16 is/are directed towards a method (i.e. a process), a computer system (i.e. machine), and computer readable medium (i.e. a manufacture), respectively. Thus, each of the claims fall within one of the four statutory categories. Nevertheless, the claims fall within the judicial exception of an abstract idea.
Claim 1 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites “monitoring transactional systems for real-time changes; capturing and processing the changed data using change data capture mechanisms; transforming and harmonizing the captured data into a standardized format that is compatible with analysis and integration processes, ensuring data consistency and compatibility; integrating the transformed and harmonized data, to enable real-time analysis and decision-making based on up-to-date data”.
The limitations above, as drafted, is a process that, under its broadest reasonable interpretation, covers a method of monitoring data changes and analyzing said data which is a method that falls under mental processes and certain methods of organizing human activity. That is, the method allows for concepts that are performed in the human mind (with the help of pen and paper) and commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations).
This judicial exception is not integrated into a practical application. In particular, the claim only recites ERPs, data capture mechanisms, data mesh, Global Data Lake, data layer and purposive datastores. Each of the additional limitations is recited at a high level of generality and amounts to no more than mere instructions to apply the exception using a generic computer component. Accordingly, these additional elements, alone or in combination, 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, alone or in combination, that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements are nothing more than mere instructions to apply the exception on a general computer.
Dependent claim 2 is also directed to an abstract idea without significantly more because it further narrows the abstract idea described in relation to claim 1 without successfully integrating the exception into a practical application or providing significantly more limitation.
Dependent claim 3 is also directed to an abstract idea without significantly more because it further narrows the abstract idea described in relation to claim 1 without successfully integrating the exception into a practical application (the additional elements of data layer, Global Data Lake and data mesh as recited in claim 1 are still recited at a high level of generality) or providing significantly more limitation.
Dependent claim 4 is also directed to an abstract idea without significantly more because it further narrows the abstract idea described in relation to claim 1 without successfully integrating the exception into a practical application (the additional elements of machine learning and/or polling based CDC algorithms are recited at a high level of generality and amounts to instructions of applying the abstract idea on a generic computer) or providing significantly more limitation.
Dependent claim 5 is also directed to an abstract idea without significantly more because it further narrows the abstract idea described in relation to claim 1 without successfully integrating the exception into a practical application (the additional elements of Purposive Datastores as recited in claim 1 are still recited at a high level of generality) or providing significantly more limitation.
Dependent claim 6 is also directed to an abstract idea without significantly more because it further narrows the abstract idea described in relation to claim 1 without successfully integrating the exception into a practical application (the additional elements of cloud-based storage infrastructure are recited at a high level of generality and amounts to instructions of applying the abstract idea on a generic computer) or providing significantly more limitation.
Dependent claim 7 is also directed to an abstract idea without significantly more because it further narrows the abstract idea described in relation to claim 1 without successfully integrating the exception into a practical application (artificial intelligence and/or machine learning models are recited at a high level of generality and amounts to instructions of applying the abstract idea on a generic computer) or providing significantly more limitation.
Claim 8 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites “monitor transactional systems for real-time changes; capture and process the changed data using change data capture mechanisms; transform and harmonize the captured data into a standardized format that is compatible with analysis and integration processes, ensuring data consistency and compatibility”.
The limitations above, as drafted, is a process that, under its broadest reasonable interpretation, covers a method of monitoring data changes and analyzing said data which is a method that falls under mental processes and certain methods of organizing human activity. That is, the method allows for concepts that are performed in the human mind (with the help of pen and paper) and commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations).
This judicial exception is not integrated into a practical application. In particular, the claim only recites ERPs, one or more headless engines; data capture mechanisms, data mesh, Global Data Lake, data layer and purposive datastores. Each of the additional limitations is recited at a high level of generality and amounts to no more than mere instructions to apply the exception using a generic computer component. Accordingly, these additional elements, alone or in combination, 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, alone or in combination, that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements are nothing more than mere instructions to apply the exception on a general computer.
Dependent claim 9 is also directed to an abstract idea without significantly more because it further narrows the abstract idea described in relation to claim 8 without successfully integrating the exception into a practical application (the data governance module is recited at a high level of generality and amounts to simple instructions of applying the abstract idea on a computer) or providing significantly more limitation.
Dependent claim 10 is also directed to an abstract idea without significantly more because it further narrows the abstract idea described in relation to claim 8 without successfully integrating the exception into a practical application (API connectivity is recited at a high level of generality) or providing significantly more limitation.
Dependent claim 11 is also directed to an abstract idea without significantly more because it further narrows the abstract idea described in relation to claim 1 without successfully integrating the exception into a practical application (System of records and ERPs are recited at a high level of generality and amounts to instructions of applying the abstract idea on a generic computer) or providing significantly more limitation.
Dependent claim 12 is also directed to an abstract idea without significantly more because it further narrows the abstract idea described in relation to claim 8 without successfully integrating the exception into a practical application (the data governance module is recited at a high level of generality and amounts to simple instructions of applying the abstract idea on a computer) or providing significantly more limitation.
Dependent claim 13 is also directed to an abstract idea without significantly more because it further narrows the abstract idea described in relation to claim 8 without successfully integrating the exception into a practical application (data layer and Purposive Datastores are still recited at a high level of generality and amounts to instructions of applying the abstract idea on a generic computer) or providing significantly more limitation.
Dependent claim 14 is also directed to an abstract idea without significantly more because it further narrows the abstract idea described in relation to claim 8 without successfully integrating the exception into a practical application (cloud based storage infrastructure recited at a high level of generality and amounts to instructions of applying the abstract idea on a generic computer) or providing significantly more limitation.
Dependent claim 15 is also directed to an abstract idea without significantly more because it further narrows the abstract idea described in relation to claim 8 without successfully integrating the exception into a practical application (artificial intelligence and/or machine learning models and data mesh are recited at a high level of generality and amounts to instructions of applying the abstract idea on a generic computer) or providing significantly more limitation.
Claim 16 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites “monitor transactional systems for real-time changes; capture and process the changed data using change data capture mechanisms; transform and harmonize the captured data into a standardized format that is compatible with analysis and integration processes, ensuring data consistency and compatibility; integrating the transformed and harmonized data, to enable real-time analysis and decision-making”.
The limitations above, as drafted, is a process that, under its broadest reasonable interpretation, covers a method of monitoring data changes and analyzing said data which is a method that falls under mental processes and certain methods of organizing human activity. That is, the method allows for concepts that are performed in the human mind (with the help of pen and paper) and commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations).
This judicial exception is not integrated into a practical application. In particular, the claim only recites ERPs, capture mechanisms and a data layer of a real time data mesh. Each of the additional limitations is recited at a high level of generality and amounts to no more than mere instructions to apply the exception using a generic computer component. Accordingly, these additional elements, alone or in combination, 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, alone or in combination, that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements are nothing more than mere instructions to apply the exception on a general computer.
Dependent claim 17 is also directed to an abstract idea without significantly more because it further narrows the abstract idea described in relation to claim 16 without successfully integrating the exception into a practical application (machine learning and/or polling based CDC algorithms are recited at a high level of generality and amounts to simple instructions of applying the abstract idea on a computer) or providing significantly more limitation.
Dependent claim 18 is also directed to an abstract idea without significantly more because it further narrows the abstract idea described in relation to claim 16 without successfully integrating the exception into a practical application (data layer comprises purposive Datastores is recited at a high level of generality and amounts to simple instructions of applying the abstract idea on a generic computer) or providing significantly more limitation.
Dependent claim 19 is also directed to an abstract idea without significantly more because it further narrows the abstract idea described in relation to claim 16 without successfully integrating the exception into a practical application (cloud-based storage infrastructure recited at a high level of generality and amounts to instructions of applying the abstract idea on a generic computer) or providing significantly more limitation.
Dependent claim 20 is also directed to an abstract idea without significantly more because it further narrows the abstract idea described in relation to claim 16 without successfully integrating the exception into a practical application (artificial intelligence and/or machine learning models is recited at a high level of generality and amounts to simple instructions of applying the abstract idea on a computer) or providing significantly more limitation.
As to claim 16, the claim is directed towards a computer readable medium. Under the broadest reasonable interpretation, the term includes carrier waves and signals which are non-statutory forms of patentable subject matter and the specification does not limit the definition to exclude carrier waves and signals. In order to overcome this rejection, the Office recommends amending the claims so that they recite only non-transitory media (see USPTO Notice 1351 OG 212).
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 1-7 and 16-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Makhija (US 2020/0279200) in view of Hadar (US 2023/0067777).
As per claim 1/16, Makhija discloses a computerized method for change data capture in an ERP agnostic real-time storage architecture and a computer readable medium, comprising:
monitoring transactional systems, including ERPs, for real-time changes (paragraph 9 and 42, “a control tower configured for controlling a plurality of functions associated with the one or more applications wherein the control tower determines characteristic of at least one attribute of one or more of the plurality of received data wherein characteristic includes change in the at least one attribute or determination of the attribute as a new attribute,”);
capturing and processing the changed data using change data capture mechanisms (paragraphs 47, 53, 63-64, “The controller 113 selects an Artificial Intelligence based dynamic processing logic using the bot to reduce the processing time for performing multiple functions of the ERP or SCM applications. The processing logic for each function of an application is different. The controller 113 is configured to determine and generate a processing logic for each function in real-time depending on the received data and processing cycle of that received data in the one or more application “…“creation of a plurality of data models for execution of tasks in one or more applications including ERP and SCM, a plurality of registers 125 for temporarily storing data from various sources for determination of characteristic of the data like change in attribute of received data or receipt of a new attribute data itself. The received data may be image data, voice data or text data where the image and voice data can be converted to text data for analysis”);
transforming and harmonizing the captured data into a standardized format that is compatible with analysis and integration processes, ensuring data consistency and compatibility across the data lake (paragraph 46, 54, 61, “the data cleansing and normalization engine 116 is configured to clean data received at the data lake in real time using natural language processing and machine learning algorithms for enhanced accuracy. Since, the data will be received from multiple disconnected sources, the engine 116 has an ability to remove duplicates, standardize and group the data”…);
integrating the transformed and harmonized data into the data layer of the real-time storage architecture, which includes a Global Data Lake comprising one or more Purposive Datastores (PDSes), to enable real-time analysis and decision-making based on up-to-date data within the data lake (paragraph 47, 61, 65, 79, “The data lake 108 includes a relational database 122a for storing related data sets received from distinct sources, a non-relational database 122b for storing non-related raw data sets, a functional database 124 for storing a library of functions enabling creation of a plurality of data models for execution of tasks in one or more applications including ERP and SCM, a plurality of registers 125 for temporarily storing data from various sources for determination of characteristic of the data like change in attribute of received data or receipt of a new attribute data itself.”)
However, Makhija does not disclose but Hadar discloses a data storage architecture as a data mesh comprising a data lake (paragraph 37).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of the invention to include the limitations above as taught by Hadar in the teaching of Makhija, in order enable a divide-and-conquer approach for consuming and providing data, while enforcing a common data format for the interoperability between the data sources and a data orchestration process (please see Hadar, paragraph 9).
As per claim 2, Makhija discloses wherein the transformation and harmonization of the captured data involve data cleansing, normalization, and enrichment techniques to ensure data quality and consistency (paragraph 38, 42, 46 and 101).
As per claim 3, Makhija discloses wherein the data layer includes the Global Data Lake configured as a scalable and fault tolerant storage infrastructure, providing a central repository for the captured and transformed data within the real time data lake (paragraph 9-10, 35, 46-48, the data lake comprises a plurality of relational and non-relational databases which Examiner interprets as scalable and fault tolerant.). However, Makhija does not disclose but Hadar discloses a data mesh includes a data lake (paragraph 37)(please see claim 1 rejection for combination rationale).
As per claim 4/17, Makhija discloses implementing change data capture using one or more trigger based, machine learning and/or polling based CDC algorithms (paragraph 12, 53 and 76).
As per claim 5/18, Makhija discloses wherein the data layer comprises the Purposive Datastores (PDSes) optimized for efficient retrieval and storage of specific types of data (paragraph 10 and 47).
As per claim 6/19, Makhija discloses storing the transformed and harmonized data in a cloud-based storage infrastructure (paragraph 77).
As per claim 7/20, Makhija discloses applying artificial intelligence and/or machine learning models to enhance the change data capture process, facilitating automated analysis, and decision making the real time data lake (paragraph 9, 47, 60, 78 and 93). However, Makhija does not disclose but Hadar discloses that a data mesh includes a data lake (paragraph 37)(please see claim 1 rejection for combination rationale).
Claim(s) 8-10 and 13-15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Makhija (US 2020/0279200) in view of Hadar (US 2023/0067777) and Grunenberger (US 2015/0189014).
As per claim 8, Makhija discloses a system for change data capture in an ERP agnostic real time data storage architecture, comprising:
One or more computers to monitor transactional systems, including ERPs, for real time changes, the computerized systems, the one or more computers comprising: (paragraph 9 and 42, “a control tower configured for controlling a plurality of functions associated with the one or more applications wherein the control tower determines characteristic of at least one attribute of one or more of the plurality of received data wherein characteristic includes change in the at least one attribute or determination of the attribute as a new attribute,”);
a data layer of a real-time data storage architecture operably connected to the one or more engines, the data layer comprising a Global Data Lake comprising one or more Purposive Datastores (PDSes), to enable real-time analysis based on real time data within the data mesh, wherein the one or more computers are configured to capture and process the changed data using change data capture mechanisms, and wherein the Global Data Lake is configured to transform and harmonize the captured data into a standardized format that is compatible with analysis and integration processes, ensuring data consistency and compatibility across the data lake (paragraph 42, 46-47, 54, 61, 65 and 79).
However, Makhija does not disclose but Hadar discloses a data storage architecture as a data mesh comprising a data lake (paragraph 37).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of the invention to include the limitations above as taught by Hadar in the teaching of Makhija, in order enable a divide-and-conquer approach for consuming and providing data, while enforcing a common data format for the interoperability between the data sources and a data orchestration process (please see Hadar, paragraph 9).
However, Makhija does not disclose but Grunenberger discloses one or more headless engines and a data layer connected to the one or more headless engines (paragraph 31 and 38, “Said cloud processing engine may be a headless engine”).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of the invention to include the limitations above as taught by Grunenberger in the teaching of Makhija, since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
As per claim 9, Makhija discloses a Data Governance Module for ensuring data integrity, security, and compliance within the real-time data lake (paragraph 42, 46, 54, 64, 67) However, Makhija does not disclose but Hadar discloses that a data mesh includes a data lake (paragraph 37)(please see claim 8 rejection for combination rationale).
As per claim 10, Makhija discloses wherein the cloud engines are connected to the data layer through API Connectivity, enabling integration and communication between the components (paragraph 52, 54, 64, 90). However, Makhija does not disclose but Grunenberger discloses that the engines are headless engines (paragraph 31 and 38)(please see claim 8 rejection for combination rationale).
As per claim 13, Makhija discloses wherein the data layer comprises the Purposive Datastores (PDSes) optimized for efficient retrieval and storage of specific types of data relevant to the supply chain domain (paragraph 10, 47 and 93).
As per claim 14, Makhija discloses a cloud-based storage infrastructure for storing the transformed and harmonized data (paragraph 77).
As per claim 15, Makhija discloses artificial intelligence and/or machine learning models used to enhance the change data capture process, enabling automated analysis and decision-making within the real-time data mesh (paragraph 9, 47, 60, 78 and 93).
Claim(s) 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Makhija (US 2020/0279200) in view of Hadar (US 2023/0067777) and Grunenberger (US 2015/0189014), as disclosed in the rejection of claim 8, in further view of Gangadarappa (US 2021/0350429), hereinafter “Gang”.
As per claim 11, Makhija does not disclose but Gang discloses wherein the System of Records integrates with external enterprise systems, including ERPs, for data exchange and synchronization (paragraph 37).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of the invention to include the limitations above as taught by Gang in the teaching of Makhija, in order to obtain additional information and/or instructions (please see Gang, paragraph 37).
Claim(s) 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Makhija (US 2020/0279200) in view of Hadar (US 2023/0067777) and Grunenberger (US 2015/0189014), as disclosed in the rejection of claim 8, in further view of Ballaro (US 2023/0419387) and Hastman (US 2014/0279254)
As per claim 12, Makhija discloses a data governance module (paragraph 54). However, Makhija does not disclose but Ballaro discloses wherein the Data Governance Module includes functionalities for catalog management, order status and tracking (OST) management, special pricing management, and quote management (158-159, 160, 170, 694 and 781).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of the invention to include the limitation above as taught by Ballaro in the teaching of Makhija, in order to provide an efficient and simple procurement process that is easily customizable for multiple organizations and multiple vendors with simple and complex business terms, and can also provide a single point-of-access for both businesses and consumers to interface, interact, and implement and execute transactions, in accordance with existing or newly defined relationships, using a custom and configurable methodology for realizing their requirements (please see Ballaro paragraph 16).
However, Makhija in view of Ballaro does not disclose but Hastman discloses Pimcore-based product data management (paragraph 18).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of the invention to include the limitation above as taught by Hastman in the teaching of Makhija in view of Ballaro, in order to automatically enables communications service providers to define and configure products and/or services and subsequently offer such products and/or services to customers in near real-time (please see Hastman abstract).
Relevant art
Pinheiro (US 2022/0114509). Pinheiro is directed towards a decentralized domain-oriented data architecture. It discloses disseminating reports via API, saving data in a data lake that is part of a data mesh and capturing data changes in a data mesh via a change data capture mechanism.
Vasudevan (US 2019/0102418). It is directed towards capturing change data from distributed data sources for use with heterogenous targets. It discloses the log-based change tracking process and a polling-based retrieval mechanism.
Crockett (US 2024/0062099). It is directed towards vectorized fuzzy string-matching process. It discloses an enterprise resource planning system being part of a data mesh.
Dickey (US 2015/0295766). It is directed towards transformation of network data at a remote capture agent. It discloses a trigger-based event detection system that intercepts data modifications.
Andreakis (US 11,334,554). It is directed towards watermark-based techniques for change data capture. It discloses allocating data resources within a distributed storage framework and a federated data processing layer which allows for parallel query execution.
Nanda (US 2019/0243836). It discloses wherein data is allocated to data stores based on data classification.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to OMAR ZEROUAL whose telephone number is (571)272-7255. The examiner can normally be reached Flex schedule.
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OMAR . ZEROUAL
Examiner
Art Unit 3628
/OMAR ZEROUAL/Primary Examiner, Art Unit 3628
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