FORM 2
THE PATENTS ACT, 1970
(39 OF 1970)
&
THE PATENT RULES, 2003
COMPLETE SPECIFICATION
(See section 10 and rule 13)
“METHOD AND SYSTEM FOR BULK DATA INTEGRATION
THROUGH MULTI-FORMAT FILE PARSING”
We, Jio Platforms Limited, an Indian National, of Office - 101, Saffron, Nr. Centre Point,
Panchwati 5 Rasta, Ambawadi, Ahmedabad - 380006, Gujarat, India.
The following specification particularly describes the invention and the manner in which it is
to be performed.
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METHOD AND SYSTEM FOR BULK DATA INTEGRATION THROUGH MULTI-FORMAT FILE PARSING
FIELD OF INVENTION
[0001] Embodiments of the present disclosure generally relate to data integration in database systems. In particular, the present disclosure relates to bulk synchronization. More particularly, embodiments of the present disclosure relate to method and system for bulk data integration through multi-format file parsing.
BACKGROUND

[0002] The following description of related art is intended to provide background information
pertaining to the field of the disclosure. This section may include certain aspects of the art that
15 may be related to various features of the present disclosure. However, it should be appreciated
that this section be used only to enhance the understanding of the reader with respect to the
present disclosure, and not as admissions of prior art.
[0003] In the field of data management and database integration, the increasing volume of data 20 managed by businesses highlights the significance of efficient methods to input and synchronize large datasets into databases. Manual data entry, which is the conventional approach, proves to be time-consuming and susceptible to errors. Therefore, there is a need for a solution that allows users to import data in bulk, offering the advantages of time savings and ensuring a high level of accuracy. By facilitating bulk data importation, this solution addresses 25 the urgent requirement for streamlined processes, reduces manual effort, and minimizes the potential for errors when dealing with substantial amounts of data in database systems.
[0004] Prior solutions often lack flexibility, typically being designed to manage one specific data format. This limitation forces users to convert their data into the accepted format before 30 they can upload it, creating extra steps and potential points of error. Traditional methods often manage data on a case-by-case basis, requiring individual input for each data set. This approach is not only time-consuming but also prone to human error, particularly when dealing with large volumes of data. In the event of a mistake in the uploaded data, previous systems either rejected the entire upload or accepted it with errors, without providing specific error details. This
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absence of detailed error logs complicates troubleshooting and rectification of the issues. Further, prior solutions tend to depend heavily on the client device for data processing, which can be a strain on the client device's resources and also limit the scalability of the solution. Previous systems were not designed to efficiently manage bulk data operations across multiple 5 tables simultaneously. This limitation restricts their utility for large-scale data integration tasks. Many older systems are not adept at updating existing entries in the database. In the absence of an effective mechanism to identify and update existing entries, data redundancy can become a significant issue.
10 [0005] These problems and limitations in the prior art necessitate the development of a method and system for efficient bulk data integration through multi-format file parsing. The present invention enhances data integration by providing significant advancements over prior solutions.
15 SUMMARY
[0006] This section is provided to introduce certain aspects of the present disclosure in a simplified form that are further described below in the detailed description. This summary is not intended to identify the key features or the scope of the claimed subject matter.
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[0007] An aspect of the present disclosure is related to a method for bulk data integration through multi-format file parsing. The method includes receiving, by a display unit via a user interface (UI) unit, a request comprising a file associated with one or more tables. The method further includes storing, by a storing unit, the received file on a server. The method further
25 includes assigning, by a processing unit, a unique identifier to the stored file, the unique identifier is generated based on an order identifier (ID). The method further includes parsing, by an Enterprise Product Catalogue (EPC) parser, the stored file to identify one or more table names from sheet name or node name. The method further includes validating, by the processing unit, data associated with each of the one or more identified tables. Finally, the
30 method includes updating, by the processing unit, the validated data in a database.
[0008] In an aspect of the present disclosure, the method comprises generating, by the processing unit, an alert based on an error encountered during at least one of parsing, validation, and data insertion.
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[0009] In an aspect of the present disclosure, the request corresponds to the file in any of eXtensible Markup Language (XML) format, and Excel format.
5 [0010] In an aspect of the present disclosure, an error file is generated based on the generated alert, wherein the generated error file comprises at least details of the error that occurred during at least one of parsing, validation, and data insertion, where the details of the error comprise at least one of location of the error, and a description of the error.
10 [0011] In an aspect of the present disclosure, the generated error file is in at least one of Excel format or XML format.
[0012] In an aspect of the present disclosure, the validation of the data comprises checking for at least one of a data type consistency, presence of required fields, and value constraints.
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[0013] In an aspect of the present disclosure, the method further comprises syncing the file in one of a parallel execution mode, sequential execution mode, and scheduler-assisted sequential execution mode.
20 [0014] In an aspect of the present disclosure, the parallel execution mode corresponds to creating a plurality of requests and updating the plurality of requests simultaneously.
[0015] In an aspect of the present disclosure, the sequential execution mode corresponds to creating and updating the request after a previous request is created and updated.
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[0016] In an aspect of the present disclosure, the scheduler-assisted sequential execution mode corresponds to creating a subsequent request after a predefined time period of creating the request; and waiting for the predefined time period after updating the request before updating the subsequent request.
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[0017] Another aspect of the present disclosure relates to a system for bulk data integration through multi-format file parsing. The system comprises a display unit configured to receive, via a user interface (UI) unit, a request comprising a file associated with one or more tables. Furthermore, the system comprises a storing unit that is configured to store the received file on
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a server. Furthermore, the system comprises a processing unit that is configured to assign a unique identifier to the stored file, the unique identifier is generated based on an order identifier (ID). Furthermore, the system comprises an Enterprise Product Catalogue (EPC) parser configured to parse the stored file to identify one or more table names from sheet name or node 5 name. Thereafter the processing unit is configured to validate data associated with each of the one or more identified tables and update the validated data in a database.
[0018] Yet another aspect of the present disclosure relates to a user equipment (UE) for bulk data integration through multi-format file parsing, comprises a processor configured to,
10 receive, via a user interface (UI) unit, a request comprising a file associated with one or more tables; store the received file on a server; assign a unique identifier to the stored file, the unique identifier is generated based on an order identifier (ID); parse, via an Enterprise Product Catalogue (EPC) parser, the stored file to identify one or more table names from sheet name or node name; validate data associated with each of the one or more identified tables; and update
15 the validated data in a database.
[0019] Further, another aspect of the present disclosure relates to a non-transitory computer-readable storage medium storing instructions for bulk data integration through multi-format file parsing, the instructions include executable code which, when executed by one or more
20 units of a system, causes a display unit to receive, via a user interface (UI) unit, a request comprising a file associated with one or more tables. Further, the instructions include executable code which, when executed causes a storing unit to store the received file on a server. Further, the instructions include executable code which, when executed causes a processing unit to assign a unique identifier to the stored file, the unique identifier is generated
25 based on an order identifier (ID). Further, the instructions include executable code which, when executed causes an Enterprise Product Catalogue (EPC) parser to parse the stored file to identify one or more table names from sheet name or node name. Further, the instructions include executable code which, when executed causes the processing unit to: validate data associated with each of the one or more identified tables; and update the validated data in a
30 database.
OBJECTS OF THE INVENTION
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[0020] Some of the objects of the present disclosure, which at least one embodiment disclosed herein satisfies are listed herein below.
[0021] It is an object of the present disclosure to provide a system and method for bulk data 5 integration through multi-format file parsing.
[0022] It is another object of the present disclosure to provide a system and method for bulk data integration through multi-format file parsing that provides a versatile data integration system capable of handling multiple formats, specifically XML and Excel files. This level of 10 flexibility accommodates a wide variety of data sources, eliminating the need for users to convert their data into a specific format before uploading.
[0023] It is yet another object of the present disclosure to provide a system and method for bulk data integration through multi-format file parsing that streamlines data input processes. 15 By supporting bulk data uploads, users can input large amounts of data simultaneously rather than adding each entry individually, thus reducing the time and effort required for data integration.
[0024] It is yet another object of the present disclosure to provide a system and method for 20 bulk data integration through multi-format file parsing that improves troubleshooting processes by providing detailed error logs immediately upon encountering data parsing or validation issues. This real-time feedback allows users to quickly identify, understand, and rectify any issues, leading to more efficient data handling and higher data quality.
25 [0025] It is yet another object of the present disclosure to provide a system and method for bulk data integration through multi-format file parsing that makes the data integration process more scalable by performing all operations on the server-side. This server-side processing approach allows the system to handle larger datasets without being constrained by the processing power or memory of the client device.
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[0026] It is yet another object of the present disclosure to provide a system and method for bulk data integration through multi-format file parsing that aims to manage large-scale data integration tasks effectively. By supporting simultaneous bulk data operations across multiple tables, the system can efficiently handle extensive data inputs in a single operation.
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[0027] It is yet another object of the present disclosure to provide a system and method for bulk data integration through multi-format file parsing that ensures high data integrity by automatically identifying and updating existing entries in the database. This feature effectively 5 prevents data redundancy and ensures the database remains accurate and up to date, thereby improving overall data management.
DESCRIPTION OF THE DRAWINGS
10 [0028] The accompanying drawings, which are incorporated herein, and constitute a part of this disclosure, illustrate exemplary embodiments of the disclosed methods and systems in which like reference numerals refer to the same parts throughout the different drawings. Components in the drawings are not necessarily to scale, emphasis instead being placed upon clearly illustrating the principles of the present disclosure. Also, the embodiments shown in the
15 figures are not to be construed as limiting the disclosure, but the possible variants of the method and system according to the disclosure are illustrated herein to highlight the advantages of the disclosure. It will be appreciated by those skilled in the art that disclosure of such drawings includes disclosure of electrical components or circuitry commonly used to implement such components.
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[0029] FIG. 1 illustrates an exemplary block diagram of a computing device upon which the features of the present disclosure may be implemented in accordance with exemplary implementation of the present disclosure.
25 [0030] FIG. 2 illustrates an exemplary block diagram of a system for bulk data integration through multi-format file parsing in accordance with exemplary implementations of the present disclosure.
[0031] FIG. 3 illustrates a method flow diagram for bulk data integration through multi-format 30 file parsing in accordance with exemplary implementations of the present disclosure.
[0032] FIG. 4 illustrates an exemplary block diagram of a system architecture for efficient bulk data integration through multi-format file parsing, in accordance with exemplary implementations of the present disclosure.
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[0033] FIG. 5 illustrates, an exemplary process flow diagram for bulk data integration through multi-format file parsing, in accordance with exemplary implementations of the present disclosure is shown.
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[0034] The foregoing shall be more apparent from the following more detailed description of the disclosure.
10 DETAILED DESCRIPTION
[0035] In the following description, for the purposes of explanation, various specific details are set forth in order to provide a thorough understanding of embodiments of the present disclosure. It will be apparent, however, that embodiments of the present disclosure may be 15 practiced without these specific details. Several features described hereafter may each be used independently of one another or with any combination of other features. An individual feature may not address any of the problems discussed above or might address only some of the problems discussed above.
20 [0036] The ensuing description provides exemplary embodiments only, and is not intended to limit the scope, applicability, or configuration of the disclosure. Rather, the ensuing description of the exemplary embodiments will provide those skilled in the art with an enabling description for implementing an exemplary embodiment. It should be understood that various changes may be made in the function and arrangement of elements without departing from the spirit and
25 scope of the disclosure as set forth.
[0037] Specific details are given in the following description to provide a thorough understanding of the embodiments. However, it will be understood by one of ordinary skill in the art that the embodiments may be practiced without these specific details. For example, 30 circuits, systems, processes, and other components may be shown as components in block diagram form in order not to obscure the embodiments in unnecessary detail.
[0038] Also, it is noted that individual embodiments may be described as a process which is depicted as a flowchart, a flow diagram, a data flow diagram, a structure diagram, or a block
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diagram. Although a flowchart may describe the operations as a sequential process, many of the operations may be performed in parallel or concurrently. In addition, the order of the operations may be re-arranged. A process is terminated when its operations are completed but could have additional steps not included in a figure.
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[0039] The word “exemplary” and/or “demonstrative” is used herein to mean serving as an example, instance, or illustration. For the avoidance of doubt, the subject matter disclosed herein is not limited by such examples. In addition, any aspect or design described herein as “exemplary” and/or “demonstrative” is not necessarily to be construed as preferred or
10 advantageous over other aspects or designs, nor is it meant to preclude equivalent exemplary structures and techniques known to those of ordinary skill in the art. Furthermore, to the extent that the terms “includes,” “has,” “contains,” and other similar words are used in either the detailed description or the claims, such terms are intended to be inclusive—in a manner similar to the term “comprising” as an open transition word—without precluding any additional or
15 other elements.
[0040] As used herein, a “processing unit” or “processor” or “operating processor” includes one or more processors, wherein processor refers to any logic circuitry for processing instructions. A processor may be a general-purpose processor, a special purpose processor, a
20 conventional processor, a digital signal processor, a plurality of microprocessors, one or more microprocessors in association with a (Digital Signal Processing) DSP core, a controller, a microcontroller, Application Specific Integrated Circuits, Field Programmable Gate Array circuits, any other type of integrated circuits, etc. The processor may perform signal coding data processing, input/output processing, and/or any other functionality that enables the
25 working of the system according to the present disclosure. More specifically, the processor or processing unit is a hardware processor.
[0041] As used herein, “a user equipment”, “a user device”, “a smart-user-device”, “a smart-device”, “an electronic device”, “a mobile device”, “a handheld device”, “a wireless 30 communication device”, “a mobile communication device”, “a communication device” may be any electrical, electronic and/or computing device or equipment, capable of implementing the features of the present disclosure. The user equipment/device may include, but is not limited to, a mobile phone, smart phone, laptop, a general-purpose computer, desktop, personal digital assistant, tablet computer, wearable device or any other computing device which is capable of
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implementing the features of the present disclosure. Also, the user device may contain at least one input means configured to receive an input from at least one of a transceiver unit, a processing unit, a storage unit, a detection unit and any other such unit(s) which are required to implement the features of the present disclosure.
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[0042] As used herein, “storage unit” or “memory unit” refers to a machine or computer-readable medium including any mechanism for storing information in a form readable by a computer or similar machine. For example, a computer-readable medium includes read-only memory (“ROM”), random access memory (“RAM”), magnetic disk storage media, optical 10 storage media, flash memory devices or other types of machine-accessible storage media. The storage unit stores at least the data that may be required by one or more units of the system to perform their respective functions.
[0043] As used herein “interface” or “user interface refers to a shared boundary across which 15 two or more separate components of a system exchange information or data. The interface may also be referred to a set of rules or protocols that define communication or interaction of one or more modules or one or more units with each other, which also includes the methods, functions, or procedures that may be called.
20 [0044] All modules, units, components used herein, unless explicitly excluded herein, may be software modules or hardware processors, the processors being a general-purpose processor, a special purpose processor, a conventional processor, a digital signal processor (DSP), a plurality of microprocessors, one or more microprocessors in association with a DSP core, a controller, a microcontroller, Application Specific Integrated Circuits (ASIC), Field
25 Programmable Gate Array circuits (FPGA), any other type of integrated circuits, etc.
[0045] As used herein the transceiver unit include at least one receiver and at least one transmitter configured respectively for receiving and transmitting data, signals, information or a combination thereof between units/components within the system and/or connected with the 30 system.
[0046] As used herein, the “Enterprise Product Catalogue (EPC)” provides the core components necessary to centralize, configure, integrate, and maintain the product and service portfolio across the enterprise. EPC, a centralized catalogue, contains all of the commercial
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and technical elements you use to define usable product and service building blocks and resulting offers.
[0047] As discussed in the background section, the current known solutions have several 5 shortcomings. The present disclosure aims to overcome the above-mentioned and other existing problems in this field of technology by providing method and system for bulk data integration through multi-format file parsing. Further, the bulk data integration solution of the present disclosure offers increased flexibility and efficiency by supporting bulk uploads in XML and Excel formats. Instant error logs streamline troubleshooting, while server-side 10 operations improve scalability. The bulk data integration solution comprises an ability to handle simultaneous multi-table operations and update existing entries ensures optimal data handling and integrity.
[0048] FIG. 1 illustrates an exemplary block diagram of a computing device [100] (also 15 referred to herein as computer system [100]) upon which the features of the present disclosure
may be implemented in accordance with exemplary implementation of the present disclosure.
In an implementation, the computing device [100] may also implement a method for bulk data
integration through multi-format file parsing utilising the system. In another implementation,
the computing device [100] itself implements the method for bulk data integration through 20 multi-format file parsing using one or more units configured within the computing device
[100], wherein said one or more units are capable of implementing the features as disclosed in
the present disclosure.
[0049] The computing device [100] may include a bus [102] or other communication 25 mechanism for communicating information, and a processor [104] coupled with the bus [102] for processing information. The processor [104] may be, for example, a general-purpose microprocessor. The computing device [100] may also include a main memory [106], such as a random-access memory (RAM), or other dynamic storage device, coupled to the bus [102] for storing information and instructions to be executed by the processor [104]. The main 30 memory [106] also may be used for storing temporary variables or other intermediate information during execution of the instructions to be executed by the processor [104]. Such instructions, when stored in non-transitory storage media accessible to the processor [104], render the computing device [100] into a special-purpose machine that is customized to perform the operations specified in the instructions. The computing device [100] further
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includes a read only memory (ROM) [108] or other static storage device coupled to the bus [102] for storing static information and instructions for the processor [104].
[0050] A storage device [110], such as a magnetic disk, optical disk, or solid-state drive is 5 provided and coupled to the bus [102] for storing information and instructions. The computing device [100] may be coupled via the bus [102] to a display [112], such as a cathode ray tube (CRT), Liquid crystal Display (LCD), Light Emitting Diode (LED) display, Organic LED (OLED) display, etc. for displaying information to a computer user. An input device [114], including alphanumeric and other keys, touch screen input means, etc. may be coupled to the
10 bus [102] for communicating information and command selections to the processor [104]. Another type of user input device may be a cursor controller [116], such as a mouse, a trackball, or cursor direction keys, for communicating direction information and command selections to the processor [104], and for controlling cursor movement on the display [112]. This input device typically has two degrees of freedom in two axes, a first axis (e.g., x) and a second axis
15 (e.g., y), that allow the device to specify positions in a plane.
[0051] The computing device [100] may implement the techniques described herein using customized hard-wired logic, one or more ASICs or FPGAs, firmware and/or program logic which in combination with the computing device [100] causes or programs the computing
20 device [100] to be a special-purpose machine. According to one implementation, the techniques herein are performed by the computing device [100] in response to the processor [104] executing one or more sequences of one or more instructions contained in the main memory [106]. Such instructions may be read into the main memory [106] from another storage medium, such as the storage device [110]. Execution of the sequences of instructions contained
25 in the main memory [106] causes the processor [104] to perform the process steps described herein. In alternative implementations of the present disclosure, hard-wired circuitry may be used in place of or in combination with software instructions.
[0052] The computing device [100] also may include a communication interface [118] coupled 30 to the bus [102]. The communication interface [218] provides a two-way data communication coupling to a network link [120] that is connected to a local network [122]. For example, the communication interface [118] may be an integrated services digital network (ISDN) card, cable modem, satellite modem, or a modem to provide a data communication connection to a corresponding type of telephone line. As another example, the communication interface [118]
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may be a local area network (LAN) card to provide a data communication connection to a compatible LAN. Wireless links may also be implemented. In any such implementation, the communication interface [118] sends and receives electrical, electromagnetic or optical signals that carry digital data streams representing various types of information.
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[0053] The computing device [100] can send messages and receive data, including program code, through the network(s), the network link [120] and the communication interface [118]. In the Internet example, a server [130] might transmit a requested code for an application program through the Internet [128], the ISP [126], the local network [122], host [124] and the 10 communication interface [118]. The received code may be executed by the processor [104] as it is received, and/or stored in the storage device [110], or other non-volatile storage for later execution.
[0054] The computing device [100] encompasses a wide range of electronic devices capable 15 of processing data and performing computations. Examples of computing device [100] include, but are not limited only to, personal computers, laptops, tablets, smartphones, servers, and embedded systems. The devices may operate independently or as part of a network and can perform a variety of tasks such as data storage, retrieval, and analysis. Additionally, computing device [100] may include peripheral devices, such as monitors, keyboards, and printers, as well 20 as integrated components within larger electronic systems, showcasing their versatility in various technological applications.
[0055] Referring to FIG. 2, an exemplary block diagram of a system [200] for bulk data integration through multi-format file parsing is shown, in accordance with the exemplary
25 implementations of the present disclosure. The system [200] comprises at least display unit [202], at least one user interface (UI) unit [204], at least one storing unit [206], at least one processing unit [208], at least one Enterprise Product Catalogue (EPC) parser [210]. Also, all of the components/ units of the system [200] are assumed to be connected to each other unless otherwise indicated below. As shown in the figures all units shown within the system should
30 also be assumed to be connected to each other. Also, in FIG. 2 only a few units are shown, however, the system [200] may comprise multiple such units or the system [200] may comprise any such numbers of said units, as required to implement the features of the present disclosure. Further, in an implementation, the system [200] may be present in a user device to implement the features of the present disclosure. The system [200] may be a part of the user device / or
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may be independent of but in communication with the user device (may also referred herein as a UE). In another implementation, the system [200] may reside in a server or a network entity. In yet another implementation, the system [200] may reside partly in the server/ network entity and partly in the user device.
[0056] The system [200] is configured for bulk data integration through multi-format file parsing, with the help of the interconnection between the components/units of the system [200].

[0057] The system [200] comprises a display unit [202] which is configured to receive, via a
10 user interface (UI) unit [204], a request comprising a file associated with one or more tables. The request corresponds to the file in any of eXtensible Markup Language (XML) format XML, and Excel format. The request may be associated with the data integration. The display unit [202] via the user interface (UI) unit [204] provides point of interaction between the user and the digital service, in this case, the data integration system. This could be a webpage, a
15 desktop application, or even a command-line interface. In this context, the user uses this interface to provide the system [200] with an input file. The input file can be in XML (eXtensible Markup Language) or Excel format. Both XML and Excel (.xlsx) are standard data interchange formats widely used for data storage and transmission. Excel files are spreadsheet files that can contain multiple sheets, each representing a table of data. XML files, on the other
20 hand, are plain text files that use tags to define elements and contain structured data (such as node). The file that includes multiple tables of data, this means the file contains various sets of structured data. In an Excel file, each sheet could be seen as a table, with rows representing records and columns representing fields. If the file is an XML file, each node could represent a separate table, with the node name representing the table name. For XML, each node could
25 represent a table, with child nodes representing records and attributes representing fields. The file is transmitted from the user's local device to the system [200], often via a network connection. In an implementation, by supporting both formats (XML or Excel format), the display unit [202] of the system [200] offers flexibility to users, in how the users wish to upload their data.
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[0058] The system [200] comprises a storing unit [206] which is configured to store the received file on a server. In an exemplary aspect, the display unit [202] of the system [200] receives the file (e.g., XML, Excel file) from the user interface unit [204]. The received file may be stored in the storing unit [206] for further processing. The received file may be stored
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on a server, which could be either locally hosted or cloud based. The file is stored may be in a specific directory on the server where the system [200] can access it. Depending on the system design and data privacy requirements, the file may be encrypted before being stored.
5 [0059] The system [200] comprises a processing unit [208], which is configured to assign a unique identifier to the stored file, the unique identifier is generated based on an order identifier (ID). The processing unit [208] is communicatively coupled with the storing unit [206]. In order to efficiently manage and track the file during and after processing, the processing unit [208] of the system [200] assigns a unique identifier to the stored file. The identifier is a string 10 of characters that is not currently associated with any other file in the system. The generation of the unique identifier can be based on various factors such as timestamp of upload, user ID, a sequential number, or even a random string, as long as uniqueness is maintained. For example, a file uploaded by User123 at a specific time could be named "User123_20231234567.xlsx", reflecting the user ID, date and time of upload.
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[0060] The system [200] comprises an Enterprise Product Catalogue (EPC) parser [210], which is configured to parse the stored file to identify one or more table names from sheet name or node name. Parsing is the process of interpreting the file data into a format that the system can understand and work with. The system [200] reads the file stored on the server and
20 interprets the content based on its structure and format. For example, for XML files, the EPC parser [210] parser will read and interpret the tags and content, whereas for Excel files, the parser will interpret the rows, columns, and their contents. The EPC parser [210] utilizes application (such as Apache workbooks) for Excel files and translates XML nodes into JSON format for XML files. Parsing involves identifying table names based on sheet names (for Excel
25 file) or node names (for XML file), validating the data in each identified one or more table names, and either storing new data or updating existing data in the database.
[0061] In an exemplary aspect, the EPC parser [210] then identifies the one or more table names for the data. If the file is an Excel file, each sheet is considered to represent a separate 30 table, and the name of the sheet is interpreted as the name of the table. If the file is an XML file, each node could represent a separate table, with the node name representing the table name. The system [200] would be designed to interpret these based on predefined rules or formats. Once the one or more table names have been identified and the data has been parsed, each record (or row of data) is validated.
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[0062] The processing unit [208] is further configured to validate data associated with each of the one or more identified tables and update the validated data in a database. The processing unit [208] is communicatively attach with the EPC parser [210]. Once the one or more table 5 names have been identified and the data has been parsed, each record (or row of data) is validated. The processing unit [208] validates data associated with each of the one or more identified tables. The validation of the data comprises checking for at least one of a data type consistency, presence of required fields, and value constraints.
10 [0063] The validation could involve checks such as data type validation, checking if required fields are present, checking if the values are within expected ranges or formats or pred-defined constraints or limits, etc. The validation rules will depend on the specific requirements of each table. The processing unit [208] may check data type format consistency in pre-defined order and format. After validation, the data is ready to be stored in the database. If the data is new, it
15 gets inserted as new records in the corresponding tables. If the data already exists (identified by a unique key such as an ID), it gets updated.
[0064] The processing unit [208] is further configured to generate an alert based on an error encountered during at least one of parsing, validation, and data insertion. The processing unit 20 [208] generates an alert during at least one parsing, validation and data insertion if it encounters any error. In an exemplary aspect, an error file is generated based on the generated alert, wherein the generated error file comprises at least details of the error that occurred during at least one of parsing, validation, and data insertion, where the details of the error comprise at least one of location of the error, and a description of the error.
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[0065] If any errors occur during the parsing, validation, or data insertion process, an error file is created. This file details the specific errors that occurred, providing valuable feedback for users and facilitating efficient troubleshooting. For example, the generated error file is in one of Excel format or XML format.
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[0066] As the system [200] via the EPC parser [210] parses the received file (e.g., XML, Excel), it keeps track of any issues or anomalies that occur. These could be related to the format of the file, the structure of the data, or the data content itself. These issues could arise during the parsing of the file, the validation of the data, or during the data insertion process into the
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database. If an error is encountered at any stage, the system [200] generates a file that details these errors. This is the 'error file'. The generation of the error file happens in real-time as the system parses and processes the input file, so it's ready as soon as the processing finishes.
5 [0067] The error file includes details of the specific errors that occurred. This could include the type of error, where it occurred, what data it related to, and other details that could help in understanding and resolving the error. For instance, if a certain cell in an Excel file contains data that doesn't meet the validation rules, the error file might note the sheet name, row number, column name, and a description of the error, such as "Invalid data type in cell B5 of sheet 10 'UserSubscriptions' - expected number but received text." This error file facilitates in improving data quality and efficiency. It enables users to quickly identify and understand any issues with their data, make necessary corrections, and re-upload the data. It also allows system administrators to monitor and troubleshoot any recurring or system-level issues.
15 [0068] The system [200] further comprises syncing the file in one of a parallel execution mode, sequential execution mode, and scheduler-assisted sequential execution mode. As used herein, the parallel execution mode corresponds to creating a plurality of requests and updating the plurality of requests simultaneously. For example, parallel execution mode shall create and hit multiple requests simultaneously in each of their threads, for multiple requests to be created 20 and updated. Further used herein, the sequence is an ordered list of something. Sequential execution mode means that each command in a program script executes in the order in which it is listed in the program. The first command in the sequence executes first and when it is complete, the second command executes, and so on. In an exemplary aspect, sequential execution mode creates and hit the requests one after the other. Also used herein, scheduler-25 assisted sequential execution mode is a scheduler or controller assists in managing the sequential execution of various tasks or queries. In an exemplary, aspect, scheduler-assisted sequential mode executes, creates and updates the request after a previous request is created and updated.
30 [0069] In an exemplary aspect, the sequential execution mode corresponds to creating and updating the request after a previous request is created and updated.
17

[0070] In an exemplary aspect, the scheduler-assisted sequential execution mode corresponds to creating a subsequent request after a predefined time period of creating the request; and waiting for the predefined time period after updating the request before updating the subsequent request.
5
[0071] Referring to FIG. 3, an exemplary method flow diagram [300] for bulk data integration through multi-format file parsing, in accordance with exemplary implementations of the present disclosure is shown. In an implementation the method [300] is performed by the system [200]. Further, in an implementation, the system [200] may be present in a server device to 10 implement the features of the present disclosure. Also, as shown in FIG. 3, the method [300] starts at step [302].
[0072] At step [304], the method [300] comprises receiving, by a display unit [202] via a user interface (UI) unit [204], a request comprising a file associated with one or more tables. The
15 request corresponds to the file in any of eXtensible Markup Language (XML) format, and Excel format. The request may be associated with the data integration. The display unit [202] via the user interface (UI) unit [204] provides point of interaction between the user and the digital service, in this case, the data integration system. This could be a webpage, a desktop application, or even a command-line interface. In this context, the user uses this interface to
20 provide the system [200] with an input file. The input file can be in XML (eXtensible Markup Language) or Excel format. Both XML and Excel (.xlsx) are standard data interchange formats widely used for data storage and transmission. Excel files are spreadsheet files that can contain multiple sheets, each representing a table of data. XML files, on the other hand, are plain text files that use tags to define elements and contain structured data (such as node). The file that
25 includes multiple tables of data, this means the file contains various sets of structured data. In an Excel file, each sheet could be seen as a table, with rows representing records and columns representing fields. If the file is an XML file, each node could represent a separate table, with the node name representing the table name. For XML, each node could represent a table, with child nodes representing records and attributes representing fields. The file is transmitted from
30 the user's local device to the system [200], often via a network connection. In an implementation, by supporting both formats (XML or Excel format), the display unit [202] of the system [200] offers flexibility to users, in how the users wish to upload their data.
18

[0073] At step [306], the method [300] comprises storing, by a storing unit [206], the received file on a server. In an exemplary aspect, the display unit [202] of the system [200] receives the file (e.g., XML, Excel file) from the user interface unit [204]. The received file may be stored in the storing unit [206] for further processing. The received file may be stored on a server, 5 which could be either locally hosted or cloud based. The file is stored may be in a specific directory on the server where the system [200] can access it. Depending on the system design and data privacy requirements, the file may be encrypted before being stored.
[0074] At step [308], the method [300] comprises assigning, by a processing unit [208], a 10 unique identifier to the stored file, the unique identifier is generated based on an order identifier (ID).
[0075] The processing unit [208] is communicatively coupled with the storing unit [206]. In order to efficiently manage and track the file during and after processing, the processing unit
15 [208] of the system [200] assigns a unique identifier to the stored file. The identifier is a string of characters that is not currently associated with any other file in the system. The generation of the unique identifier can be based on various factors such as timestamp of upload, user ID, a sequential number, or even a random string, as long as uniqueness is maintained. For example, a file uploaded by User123 at a specific time could be named
20 "User12320231234567.xlsx", reflecting the user ID, date and time of upload.
[0076] At step [310], the method [300] comprises parsing, by an Enterprise Product Catalogue (EPC) parser [210], the stored file to identify one or more table names from sheet name or node name. Parsing is the process of interpreting the file data into a format that the system can
25 understand and work with. The system [200] reads the file stored on the server and interprets the content based on its structure and format. For example, for XML files, the EPC parser [210] parser will read and interpret the tags and content, whereas for Excel files, the parser will interpret the rows, columns, and their contents. The EPC parser [210] utilizes application (such as Apache workbooks) for Excel files and translates XML nodes into JSON format for XML
30 files. Parsing involves identifying table names based on sheet names (for Excel file) or node names (for XML file), validating the data in each identified one or more table names, and either storing new data or updating existing data in the database.
19

[0077] In an exemplary aspect, the EPC parser [210] then identifies the one or more table names for the data. If the file is an Excel file, each sheet is considered to represent a separate table, and the name of the sheet is interpreted as the name of the table. If the file is an XML file, each node could represent a separate table, with the node name representing the table 5 name. The system [200] would be designed to interpret these based on predefined rules or formats. Once the one or more table names have been identified and the data has been parsed, each record (or row of data) is validated.
[0078] At step [312], the method [300] comprises validating, by the processing unit [208], data 10 associated with each of the one or more identified tables. The validation of the data comprises checking for at least one of a data type consistency, presence of required fields, and value constraints. The processing unit [208] is communicatively attach with the EPC parser [210]. The processing unit [208] validates data associated with each of the one or more identified tables. This validation could involve checks such as data type validation, checking if required 15 fields are present, checking if the values are within expected ranges or formats, etc. The validation rules will depend on the specific requirements of each table.
[0079] At step [314], the method [300] comprises updating, by the processing unit [208], the validated data in a database. After validation, the data is ready to be stored in the system's 20 database. If the data is new, it gets inserted as new records in the corresponding tables. If the data already exists (identified by a unique key such as an ID), it gets updated.
[0080] The method further comprises, generating, by the processing unit [208], an alert based on an error encountered during at least one of parsing, validation, and data insertion. The
25 processing unit [208] generates the alert during at least one parsing, validation and data insertion if it encounters any error. In an exemplary aspect, an error file is generated based on the generated alert, wherein the generated error file comprises at least details of the error that occurred during at least one of parsing, validation, and data insertion, where the details of the error comprise at least one of location of the error, and a description of the error. The generated
30 error file is in one of Excel format or XML format.
[0081] If any errors occur during the parsing, validation, or data insertion process, an error file is created. This file details the specific errors that occurred, providing valuable feedback for
20

users and facilitating efficient troubleshooting. For example, the generated error file is in one of Excel format or XML format.
[0082] As the method [300] implemented by the EPC parser [210] of the system [200] parses 5 the received file, it keeps track of any issues or anomalies that occur. These could be related to the format of the file, the structure of the data, or the data content itself. These issues could arise during the parsing of the file, the validation of the data, or during the data insertion process into the database. If an error is encountered at any stage, the system [200] generates a file that details these errors. This is the 'error file'. The generation of the error file happens in real-time 10 as the system parses and processes the input file, so it's ready as soon as the processing finishes.
[0083] The error file includes details of the specific errors that occurred. This could include the type of error, where it occurred, what data it related to, and other details that could help in understanding and resolving the error. For instance, if a certain cell in an Excel file contains
15 data that doesn't meet the validation rules, the error file might note the sheet name, row number, column name, and a description of the error, such as "Invalid data type in cell B5 of sheet 'UserSubscriptions' - expected number but received text." This error file facilitates in improving data quality and efficiency. It enables users to quickly identify and understand any issues with their data, make necessary corrections, and re-upload the data. It also allows system
20 administrators to monitor and troubleshoot any recurring or system-level issues.
[0084] The method further comprises, syncing the file in one of a parallel execution mode, sequential execution mode, and scheduler-assisted sequential execution mode.
25 [0085] In an exemplary aspect, the parallel execution mode corresponds to creating a plurality of requests and updating the plurality of requests simultaneously. The sequential execution mode corresponds to creating and updating the request after a previous request is created and updated.
30 [0086] The scheduler-assisted sequential execution mode corresponds to creating a subsequent request after a predefined time period of creating the request; and waiting for the predefined time period after updating the request before updating the subsequent request.
[0087] Thereafter, the method [300] terminates at step [316].
21

[0088] The present disclosure further discloses a user equipment (UE) for bulk data integration through multi-format file parsing. The UE comprises a processor configured to: receive, via a user interface (UI) unit [204], a request comprising a file associated with one or more tables; 5 store the received file on a server; assign a unique identifier to the stored file, the unique identifier is generated based on an order identifier (ID); parse, via an Enterprise Product Catalogue (EPC) parser [210], the stored file to identify one or more table names from sheet name or node name; validate data associated with each of the one or more identified tables; and update the validated data in a database.
10
[0089] The present disclosure further discloses a non-transitory computer readable storage medium storing instructions for bulk data integration through multi-format file parsing, the instructions include executable code which, when executed by one or more units of a system, causes a display unit [202] to receive, via a user interface (UI) unit [204], a request comprising
15 a file associated with one or more tables. Further, the instructions include executable code which, when executed causes a storing unit [206] to store the received file on a server. Further, the instructions include executable code which, when executed causes a processing unit [208] to assign a unique identifier to the stored file, the unique identifier is generated based on an order identifier (ID). Further, the instructions include executable code which, when executed
20 causes an Enterprise Product Catalogue (EPC) parser [210] to parse the stored file to identify one or more table names from sheet name or node name. Further, the instructions include executable code which, when executed causes the processing unit [208] to: validate data associated with each of the one or more identified tables; and update the validated data in a database.
25
[0090] Referring to FIG. 4, an exemplary block diagram of a system architecture [400] for efficient bulk data integration through multi-format file parsing, in accordance with exemplary embodiments of the present disclosure. The system architecture [400] comprises one or more channels [402], Enterprise Product Catalogue (EPC) user interface (UI) [402a], other channels 30 [402b], firewall [404], load balancer [406], Enterprise Product catalogue (EPC) [408], Enterprise product catalogue [EPC] instance [410], operations, administration and management (OAM) instance [412], identity access management (IAM) instance [414], Elastic search cluster (ES cluster) [416], fulfilment management system (FMS) [418], SE [420],
22

Customer Relationship Management (CRM) [422], and a Data Information Framework (DIF) [424].
[0091] One or more Channels [402b] are different EPC user interface [402a] like web 5 application, external system from where rest API request comes to EPC [408]. This request is authenticated and authorized by IAM (Identity Access Management) instance [414]. Once the request is validated by IAM [414], Load balancer [406] sends the request to backend EPC [408] application instance. An API request is handled and processed by EPC [408] instance. OAM instance [412] is the broadcaster which manages the micro services registry, dependencies, etc. 10 information required to other microservices to communicate with each other. FMS [418] is the middleware used to integrate the API services with other system nodes. ES cluster [416] is the database used to store data.
[0092] Referring to FIG. 5, an exemplary process flow diagram [500] for bulk data integration 15 through multi-format file parsing, in accordance with exemplary implementations of the present disclosure is shown. Also, shown in FIG. 5, the process starts as follows:
[0093] At step S1, the user creates Excel/XML file and uploads it on UI unit [204].
20 [0094] At step S2, type-3 implementation identifies the file type, and parses table by table.
[0095] At step S3, the system [200] checks if there is any incorrect table name present.
[0096] At step S4, if there is any incorrect table name present, the system [200] creates an 25 error.
[0097] At step S5, the system [200] checks if there is any error validation incorrect field type or name present.
30 [0098] At step S6, if there is an error validation incorrect field type or name present, the system [200] creates an error.

[0099]

At step S7, the system [200] parses the data and save into the data base.

23

[0100] At step S8, the system [200] creates an error excel sheet/XML file containing all errors for each table.
[0101] At Step S9, the system [200] sends the error file to UI unit [204] along with parsed data 5 and details of the order. In an exemplary aspect, Enterprise Product Catalogue (EPC) parser [210] executes the process in an asynchronous mode, and may not immediately send details of the order, the details along with error file, and parsed data to user interface (UI) unit [204]. Further, in an implementation of the present disclosure, the data is sent to UI unit [204] when the data requested from UI unit [204] and/or upon complete execution.
10
[0102] As is evident from the above, the present disclosure provides a technically advanced solution for bulk data integration through multi-format file parsing. The present solution provides a versatile data integration system capable of handling multiple formats, specifically XML and Excel files. This level of flexibility accommodates a wide variety of data sources,
15 eliminating the need for users to convert their data into a specific format before uploading. The present disclosure further provides a system and method for bulk data integration through multi-format file parsing that streamlines data input processes. By supporting bulk data uploads, users can input large amounts of data simultaneously rather than adding each entry individually, thus reducing the time and effort required for data integration. The present
20 disclosure further provides a system and method for efficient bulk data integration through multi-format file parsing that improves troubleshooting processes by providing detailed error logs immediately upon encountering data parsing or validation issues. This real-time feedback allows users to quickly identify, understand, and rectify any issues, leading to more efficient data handling and higher data quality. The present disclosure further provides a system and
25 method for efficient bulk data integration through multi-format file parsing that makes the data integration process more scalable by performing all operations on the server-side. This server-side processing approach allows the system to handle larger datasets without being constrained by the processing power or memory of the client device. The present disclosure further provides a system and method for efficient bulk data integration through multi-format file parsing that
30 aims to manage large-scale data integration tasks effectively. By supporting simultaneous bulk data operations across multiple tables, the system can efficiently handle extensive data inputs in a single operation. The present disclosure further provides a system and for efficient bulk data integration through multi-format file parsing that ensures high data integrity by automatically identifying and updating existing entries in the database.
24

[0103] This feature effectively prevents data redundancy and ensures the database remains accurate and up to date, thereby improving overall data management.
[0104] Further, in accordance with the present disclosure, it is to be acknowledged that the functionality described for the various the components/units can be implemented interchangeably. While specific embodiments may disclose a particular functionality of these units for clarity, it is recognized that various configurations and combinations thereof are within the scope of the disclosure. The functionality of specific units as disclosed in the disclosure should not be construed as limiting the scope of the present disclosure. Consequently, alternative arrangements and substitutions of units, provided they achieve the intended functionality described herein, are considered to be encompassed within the scope of the present disclosure.
[0105] While considerable emphasis has been placed herein on the disclosed implementations, it will be appreciated that many implementations can be made and that many changes can be made to the implementations without departing from the principles of the present disclosure. These and other changes in the implementations of the present disclosure will be apparent to those skilled in the art, whereby it is to be understood that the foregoing descriptive matter to be implemented is illustrative and non-limiting.
25

We Claim:
1. A method for bulk data integration through multi-format file parsing, comprising:
receiving, by a display unit [202] via a user interface (UI) unit [204], a request comprising a file associated with one or more tables;
storing, by a storing unit [206], the received file on a server;
assigning, by a processing unit [208], a unique identifier to the stored file, the unique identifier is generated based on an order identifier (ID);
parsing, by an Enterprise Product Catalogue (EPC) parser [210], the stored file to identify one or more table names from sheet name or node name;
validating, by the processing unit [208], data associated with each of the one or more identified tables; and
updating, by the processing unit [208], the validated data in a database.
2. The method as claimed in claim 1, wherein the method comprises generating, by the processing unit [208], an alert based on an error encountered during at least one of parsing, validation, and data insertion.
3. The method as claimed in claim 2, wherein an error file is generated based on the generated alert, wherein the generated error file comprises at least details of the error that occurred during at least one of parsing, validation, and data insertion, where the details of the error comprise at least one of location of the error, and a description of the error.
4. The method as claimed in claim 1, wherein the validation of the data comprises checking for at least one of a data type consistency, presence of required fields, and value constraints.
5. The method as claimed in claim 1, wherein the method comprises syncing the file in one of a parallel execution mode, sequential execution mode, and scheduler-assisted sequential execution mode.
6. The method as claimed in claim 5, wherein the parallel execution mode corresponds to creating a plurality of requests and updating the plurality of requests simultaneously.

7. The method, as claimed in claim 5, wherein the sequential execution mode corresponds to creating and updating the request after a previous request is created and updated.
8. The method as claimed in claim 5, wherein the scheduler-assisted sequential execution mode corresponds to creating a subsequent request after a predefined time period of creating the request; and waiting for the predefined time period after updating the request before updating the subsequent request.
9. A system for bulk data integration through multi-format file parsing, the system comprises:
a display unit [202] configured to receive, via a user interface (UI) unit [204], a request comprising a file associated with one or more tables;
a storing unit [206] configured to store the received file on a server;
a processing unit [208] configured to assign a unique identifier to the stored file, the unique identifier is generated based on an order identifier (ID);
an Enterprise Product Catalogue (EPC) parser [210] configured to parse the stored file to identify one or more table names from sheet name or node name;
the processing unit [208] configured to:
validate data associated with each of the one or more identified tables; and update the validated data in a database.
10. The system as claimed in claim 9, wherein the processing unit [208] is further configured to generate an alert based on an error encountered during at least one of parsing, validation, and data insertion.
11. The system as claimed in claim 10, wherein an error file is generated based on the generated alert, wherein the generated error file comprises at least details of the error that occurred during at least one of parsing, validation, and data insertion, where the details of the error comprise at least one of location of the error, and a description of the error.
12. The system as claimed in claim 9, wherein the validation of the data comprises checking for at least one of a data type consistency, presence of required fields, and value constraints.

13. The system as claimed in claim 9, wherein the system [200] comprises syncing the file in one of a parallel execution mode, sequential execution mode, and scheduler-assisted sequential execution mode.
14. The system as claimed in claim 13, wherein the parallel execution mode corresponds to creating a plurality of requests and updating the plurality of requests simultaneously.
15. The system, as claimed in claim 13, wherein the sequential execution mode corresponds to creating and updating the request after a previous request is created and updated.
16. The system as claimed in claim 13, wherein the scheduler-assisted sequential execution mode corresponds to creating a subsequent request after a predefined time period of creating the request; and waiting for the predefined time period after updating the request before updating the subsequent request.
17. A user equipment (UE) for bulk data integration through multi-format file parsing, comprising:
a processor configured to:
receive, via a user interface (UI) unit [204], a request comprising a file associated with one or more tables;
store the received file on a server;
assign a unique identifier to the stored file, the unique identifier is generated based on an order identifier (ID);
parse, via an Enterprise Product Catalogue (EPC) parser [210], the stored file to identify one or more table names from sheet name or node name;
validate data associated with each of the one or more identified tables; and
update the validated data in a database.