Faced with the need to convert multiple xlsx tables into JSON files, manually processing them one by one is not only inefficient but may also cause omissions and naming confusion. This article focuses on the Excel-to-JSON functionality of HeSoft Doc Batch Tool , introducing applicable scenarios, the effects before and after conversion, and the complete steps from accessing the Excel tool, importing files, confirming the list, setting the save location, to starting the process. It is suitable for reference in scenarios such as office data organization, system import, and development delivery.
Many office data were initially managed using Excel because tables are intuitive, easy to edit, and convenient for cross-departmental collaboration. However, in scenarios like system development, data interfaces, website configuration, batch importing, and automated script processing, the JSON format is often more commonly used. The problem is, in practice, it's rare to convert just one table; more often, a folder contains multiple xlsx files: customer feedback forms, employee records, financial reports, inventory lists, product catalogs, sales data, etc., all need to be uniformly converted to json. If you continue to process them manually at this point, each file needs to be opened, converted, saved, and checked—a repetitive and error-prone process.
This article introduces a method more suitable for office scenarios: using HeSoft Doc Batch Tool to batch convert Excel files to Json format. It is a batch processing software designed for documents and office files, with its core value being the centralization of repetitive file operation workflows, helping users reduce manual clicking and repetitive labor. Below, with screenshots, we will explain the applicable scenarios for batch converting xlsx tables to json files, the effects before and after processing, and the specific operation steps.
Applicable Scenarios: From Excel Data Organizing to JSON Delivery
Batch converting xlsx to json is common in several types of work processes. The first is data delivery; for example, after operations staff organize Excel tables, they need to hand them over to R&D colleagues for importing into a database or interface testing environment. The second is system migration; for instance, data exported from an old system is in Excel, but the new system's import template requires JSON. The third is automated processing; for example, scripts or toolchains need to read structured data, and JSON is easier for programs to parse. The fourth is data archiving; for example, multiple tables generated within a project cycle need to be uniformly converted into a more machine-readable format for preservation.
The pain point in these scenarios is not just "not knowing how to convert," but rather "having too many files and not wanting to convert them repeatedly." As the number of files increases, manual operation encounters several problems: it's easy to miss a file; the converted file names might not be consistent; source files and result files are mixed together and hard to manage; and the same steps must be repeated for each process. The role of a batch conversion tool is to merge these repetitive actions into a single task, allowing the user to focus only on file selection, save location, and result verification.
Before Processing: Multiple xlsx Files Awaiting Unified Conversion
The screenshot before processing shows a typical office folder containing multiple Excel table files, all with the .xlsx extension. The files include customer_feedback.xlsx, employee_records.xlsx, financial_report.xlsx, inventory_list.xlsx, marketing_analysis.xlsx, product_catalog.xlsx, project_timeline.xlsx, and sales_data.xlsx. These file names correspond to different business data, making them perfectly suited for a unified batch conversion.
If processed one by one traditionally, these 8 files would mean at least 8 repetitive operations. A more realistic scenario is that users also need to confirm whether each file was processed successfully, whether the output file name is correct, and whether the save directory is consistent. For a one-off temporary task, manual operation might be manageable; but for people who frequently process Excel data, this method consumes a significant amount of time. Using HeSoft Doc Batch Tool , you can process these xlsx files as a unified task list.
After Processing: Excel Files Generate Corresponding JSON Files
In the screenshot after processing, the original xlsx files have been converted to json files, with the main file names kept consistent, only the extension changed to .json. For example, customer_feedback.xlsx corresponds to customer_feedback.json after conversion, employee_records.xlsx corresponds to employee_records.json, and sales_data.xlsx corresponds to sales_data.json. This result is very easy to verify and also convenient for subsequent delivery to systems, scripts, or developers.
From an office efficiency perspective, the most important benefits of batch conversion are stability and traceability. Users do not need to rename each file after conversion or manually establish a correspondence between Excel and JSON. As long as the source files are clearly named, the output json files will naturally inherit this naming structure. This is particularly helpful for batch generation of json files and batch organizing of data files.
Operation Steps: How to Batch Convert Excel Tables to Json Format
Step 1: Open the Software and Enter Excel Tools
After launching HeSoft Doc Batch Tool , first look at the tool categories on the left. The screenshot on the left includes entries such as Home, Task Flow, All Tools, File Name, Folder Name, File Organizing, Word Tools, Excel Tools, PowerPoint Tools, PDF Tools, Text Tools, Image Tools, More Tools, etc. Since this task handles Excel tables, you need to click on Excel Tools.
After entering Excel Tools, a set of conversion functions related to Excel files will appear on the right. The screenshot shows various format conversion options, such as Excel to JPG image, Excel to PDF, Excel to Csv, Excel to Xls, Excel to Xlsx, Excel to Txt, Excel to HTML webpage, Excel to Numbers table, Excel to XML, etc. To batch convert Excel to JSON, you need to select "19. Excel to Json" from the list.
The expected result of this step is to enter the dedicated "Excel to Json" page. Choosing the correct function is very important, as the same software might contain multiple Excel format conversion capabilities. Only by entering the Json conversion function will the subsequent task execute according to the Excel-to-JSON target.
Step 2: Import the xlsx Tables to be Converted
After entering the function page, the page title displays "Excel to Json". Above the interface, there are two buttons: Add Files and Import Files from Folder. They correspond to two common import methods: if files are located in different places, you can use "Add Files" to select them one by one; if the files are already collected in one folder, you can use "Import Files from Folder" to import them all at once.
In batch office processing, it is recommended to first organize the xlsx files to be converted into the same folder, and then import them via the folder method. This has two benefits: first, it reduces the time spent repeatedly selecting files; second, it lowers the probability of missing selections. In the screenshot, the imported task list already shows 8 records, indicating that these Excel files have been added to the pending queue.
The list displays the sequence number, name, path, extension, creation time, modification time, and action. Through these fields, users can confirm the source and type of each file. For example, the path shows the files are located in a test folder on the desktop, and the extension shows xlsx. The summary at the bottom shows the record count is 8, which helps users quickly determine if the imported quantity meets expectations.
Step 3: Verify the File List Before Starting Conversion
The biggest fear in batch processing is an inaccurate source file list, so it is recommended to complete a verification before clicking the next step. First, check the name column to confirm that all files needing conversion are present, such as customer_feedback.xlsx, financial_report.xlsx, product_catalog.xlsx, etc. Second, check the path column to confirm the files come from the correct directory, avoiding mistakenly adding old versions or unrelated files to the task. Third, check the extension column to confirm the imported files are Excel files.
If you find files that do not need processing, you can use the delete button on the right side of each row to remove them; if the entire list is incorrect, you can use the Clear button at the top right of the page to start the import again. After completing the verification, click the Next Step button at the bottom to proceed to the subsequent settings.
Step 4: Set the Save Location for Result Files
From the page flow, you can see that after selecting the records to be processed, the next stage is Setting the Save Location. This step determines where the converted json files will be output. For a task involving the batch generation of json files, it is not advisable to choose a save location casually; it is best to plan a clear output directory in advance.
For example, you can create a new folder named "json results," "Excel to Json Output," or a project-named folder, specifically for saving the result files. This prevents the output files from mixing with the original xlsx files and facilitates subsequent compression, uploading, delivery, or archiving. If processing multiple batches of data, you can create different folders by date or batch number to improve traceability.
Step 5: Start Processing and View Conversion Results
After setting the save location, the flow enters the Start Processing stage. After the user initiates the process, the software will execute the conversion one by one according to the records in the task list and output the json files. Once processing is complete, you need to go to the save directory to check the conversion results. The most basic checks include: whether the number of output files matches the number of source files; whether the file extension is .json; whether the file names correspond one-to-one with the source Excel files.
As seen in the post-processing screenshot, all 8 Excel files have generated corresponding json files with a clear naming structure. For important business data, it is recommended to spot-check a few json files to confirm that the content can be read normally by subsequent systems or scripts. This allows you to promptly identify issues with the source data or format before formal delivery.
Common Questions and Notes
1. Do I need to organize the table content before converting xlsx to json?
It is recommended. Batch conversion tools handle the format conversion, but whether the data in the source table is standardized will still affect the subsequent user experience. Before conversion, you can check if the headers are clear, if the data rows are complete, and if there are any obviously empty tables or erroneous files. Especially when handing over to a system for import, the standardization of the source data is very important.
2. Is it more appropriate to use Add Files or Import Files from Folder?
If you are only converting a few files, using "Add Files" is more direct; if you need to process an entire folder of Excel files, "Import Files from Folder" is more efficient. The example in the screenshot involves adding multiple xlsx files to a list, a type of task more suitable for folder import, which can reduce repetitive selection.
3. Why should file names be kept consistent after conversion?
After batch conversion, consistent file names aid verification and delivery. For instance, when sales_data.xlsx is converted to sales_data.json, the user can immediately see their correspondence. If the source file naming is chaotic, the converted json files will inherit this chaos. Therefore, it is recommended to standardize the Excel file names before conversion.
4. Can a large number of Excel files be processed at once?
Judging from the software interface and function description, "Excel to Json" is positioned for batch converting multiple Excel files to Json format, suitable for multi-file tasks. In practice, it's recommended to organize files by project or batch, conduct a small-scale test first, and after confirming the results meet requirements, proceed with a larger number of files. This is more prudent and facilitates troubleshooting.
5. How to deliver json results after conversion?
It's recommended to first confirm the quantity, names, and save directory, then deliver based on the usage scenario. If handing over to development or data personnel, you can compress the entire output directory; if using for system import, upload the corresponding json files according to the system requirements. Regardless of the method, it is advisable to keep the original Excel files for future tracing and re-conversion.
Summary: Using Office Batch Processing Tools to Improve Excel-to-JSON Efficiency
Batch converting multiple xlsx tables to json files is a common requirement in many office data workflows. Although manual processing seems simple, it creates a lot of repetitive work as the number of files increases and raises risks like missed conversions, incorrect selections, and naming chaos. The "Excel to Json" function provided by HeSoft Doc Batch Tool can add multiple Excel files to the same task list, and by setting the save location and starting the process, batch generate the corresponding JSON files.
If your work frequently involves requirements like Excel files to JSON, batch xlsx to json, or batch generation of json files, it is recommended to adopt this batch processing method: first organize the source folder, then import into the software, verify the list, set the output directory, and finally process all at once. This ensures a clear workflow and significantly reduces repetitive operations, leaving more time for data checking, business analysis, and subsequent delivery.