Data upload

Zilliant Gen AI Pricing Analytics requires properly-formatted transactional data to produce analytics. You must upload data to File Upload in CSV format, where the system validates your files for common errors and accepts or rejects the files. Analytics sends you an email notification if it rejects a file and provides a summary of why.

Before you continue
Analytics validates files only for common file errors such as incorrect line endings. For Analytics to generate meaningful pricing analytics, your files must contain relevant column headers and fields before you upload them to Zilliant.
Your files must meet Zilliant’s data input specifications. For more, read Data model.

For best data formatting practices, read Best practices. If you experience issues managing uploaded data, contact your Zilliant representative.

Upload data

Select File Upload.
Select a storage bucket.
If you want to create a folder, select Options, then Create folder. Enter a folder name, then select Create folder.
Select Options, then select Upload > Add files.
Select a CSV file to upload, then select Start.
Tip
Depending on the files you choose to upload, upload in the following order one at a time:
1. account.csv
2. product_category.csv
3. supplier_sku_lookup.csv
4. product.csv
5. transaction.csv
6. transaction_line_item.csv
Track your files’ status and upload progress under the Status and Progress columns. To view your uploaded files, select Back.

View uploaded data

To view the latest version of your storage bucket, select Refresh.

Tip
After validation, a file may take 1–2 minutes to appear in your storage bucket.

To search for an uploaded file:

Select File Upload.
Select a storage bucket. If you want to search for an uploaded file in a folder, select the folder.
Go to the Search current folder search bar and enter a file name. Select the Include subfolders checkbox to extend your search to files in child folders.

Best practices

The system validates files for common file errors. To ensure a valid data upload, check your files against the following best formatting practices.

There can also be many causes of duplicative or near-duplicative data, including combining data from multiple sources. To avoid this, make sure to implement data quality processes, such as standardizing data collection and entry procedures.

Files

Your files:

Should	Should not
Tie out corresponding data sets with other files	Contain duplicate data
Comply with RFC 4180 Tip: Read more about RFC 4180 .
Use only lowercase letters, numbers, underscores, and the CSV file extension for the file name Tip: For consistent file names, we suggest using a `<data_model_name>.csv` file naming convention where <data_model_name> is the file’s data model. For example, `customers.csv`.

Should

Should not

Tie out corresponding data sets with other files

Contain duplicate data

Comply with RFC 4180

Tip: Read more about RFC 4180 External link indicator .

Use only lowercase letters, numbers, underscores, and the CSV file extension for the file name

Tip: For consistent file names, we suggest using a <data_model_name>.csv file naming convention where <data_model_name> is the file’s data model. For example, customers.csv.

Columns

Each of your files should have a column header row. A file’s column headers:

Should	Should not
Meet data specification requirements as specified in the Zilliant data model
Use only lowercase letters, numbers, and underscores Tip: If a file’s column headers include `AccountId`, `AccountNAME`, and `Customer_Id`, then revise the file’s column headers to all use lowercase letters and underscores, like `account_id`, `account_name`, and `customer_id`.

Should

Should not

Meet data specification requirements as specified in the Zilliant data model

Use only lowercase letters, numbers, and underscores

Tip: If a file’s column headers include AccountId, AccountNAME, and Customer_Id, then revise the file’s column headers to all use lowercase letters and underscores, like account_id, account_name, and customer_id.

Data rows

Your files’ data types must meet data specification requirements as specified in the Zilliant data model. Data rows should list data in the same order as their file’s column headers.

For example
If a file’s column header row is transaction_id, account_id, total, order_datetime, then its data rows should list data in the same order.

Additionally, each of your files:

Should	Should not
Have at least one data row	Use ASCII characters in numerical data
Use commas to separate fields
End lines with CRLF
Use the ISO 8601 date format for dates
Enclose a field that has special characters with quotation marks Tip: If a file isn’t encoded with UTF-8, consider using byte order marks in the file to signal the endianness of the file’s encoding. For more details about UTF-8, read HTML Unicode (UTF-8) Reference. For more details about byte order marks, read Using Byte Order Marks (BOMs).