How to format supplier inventory data file to match the database
Working with supplier files is a common process for many businesses, and despite its relative complexity and significant time investment, in many cases, it is still poorly automated or even done manually.
Typically, working with supplier files (such as product prices or available inventory items) involves more or less typical steps:
- Obtaining information
- Transformation
- Passing it for further processing or importing into various systems
By performing these steps sequentially, it's possible to fully automate the process of working with supplier files.
Let's consider the steps in more detail.
Obtaining information
Usually, supplier files are simple Excel documents but with fairly complex structures and several different tables. Despite this, it can always be uploaded to Mipler and represented as a table for further work.
In some cases, supplier data (or other necessary information for processing) can be obtained using built-in integrations, such as with Shopify or Magento, through direct API queries, or from a database.
Data Transformation
Making any changes to the data tables is considered transformation stages. Sequential transformations allow deriving derivative data in a new format from the input data.
Mipler Data Workflow is essentially Excel or Google Sheet with visual, step-by-step data manipulation programming. Mipler is ideal for manipulating datasets that are quite difficult to work with using event-driven automation systems (Zapier, Make).
In the case of supplier files, automation typically includes such steps:
- Data filtering - i.e., removing irrelevant data
- Changing names, order, deleting columns
- Adding new columns with custom calculations
- Merging data from other sources (e.g., assigning your own SKU to a product by comparing products by name or supplier id)
It should be noted that the list of possible table transformations includes many more options and covers most of the existing tasks.
Processing prepared data
After completing the necessary transformations, the data can be used directly in the Mipler data workflow or saved to an external storage and used in other systems.
For example:
- Data can be uploaded to Google Sheets
- Transferred to external systems using API requests (Inventory data can be directly uploaded to Shopify or Magento)
- Uploaded to your ERP system
- Send an email with the prepared document
- Convert to HTML and then to PDF documents
- And hundreds of other possibilities
At this stage, it's also possible to directly input data into the database or extract a prepared file and perform updates in the database using other solutions.
How to format supplier inventory data file to match the database
Working with supplier files is a common process for many businesses, and despite its relative complexity and significant time investment, in many cases, it is still poorly automated or even done manually.
Typically, working with supplier files (such as product prices or available inventory items) involves more or less typical steps:
- Obtaining information
- Transformation
- Passing it for further processing or importing into various systems
By performing these steps sequentially, it's possible to fully automate the process of working with supplier files.
Let's consider the steps in more detail.
Obtaining information
Usually, supplier files are simple Excel documents but with fairly complex structures and several different tables. Despite this, it can always be uploaded to Mipler and represented as a table for further work.
In some cases, supplier data (or other necessary information for processing) can be obtained using built-in integrations, such as with Shopify or Magento, through direct API queries, or from a database.
Data Transformation
Making any changes to the data tables is considered transformation stages. Sequential transformations allow deriving derivative data in a new format from the input data.
Mipler Data Workflow is essentially Excel or Google Sheet with visual, step-by-step data manipulation programming. Mipler is ideal for manipulating datasets that are quite difficult to work with using event-driven automation systems (Zapier, Make).
In the case of supplier files, automation typically includes such steps:
- Data filtering - i.e., removing irrelevant data
- Changing names, order, deleting columns
- Adding new columns with custom calculations
- Merging data from other sources (e.g., assigning your own SKU to a product by comparing products by name or supplier id)
It should be noted that the list of possible table transformations includes many more options and covers most of the existing tasks.
Processing prepared data
After completing the necessary transformations, the data can be used directly in the Mipler data workflow or saved to an external storage and used in other systems.
For example:
- Data can be uploaded to Google Sheets
- Transferred to external systems using API requests (Inventory data can be directly uploaded to Shopify or Magento)
- Uploaded to your ERP system
- Send an email with the prepared document
- Convert to HTML and then to PDF documents
- And hundreds of other possibilities
At this stage, it's also possible to directly input data into the database or extract a prepared file and perform updates in the database using other solutions.