Step-by-Step Guide: How to Pull A Report in Walmart Scintilla
Discover how Walmart Scintilla enhances supplier analytics, replacing DSS for better insights into sales, inventory, and supply chain performance.
Who is this for?
Walmart suppliers who want to understand:
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What Scintilla is and how it replaced DSS in Retail Link
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How to navigate the Report Builder and pull your first report
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Which datasets matter most for tracking deduction and supply chain performance
What Is Walmart Scintilla?
Walmart Scintilla is the analytics and reporting platform that replaced the Decision Support System (DSS) inside Retail Link. It is Walmart's current reporting environment for US suppliers, giving you access to sales data both in-store and online pickup/delivery. It also provides customer shopping insights and supply chain metrics that become useful for businesses.
This wasn’t just a cosmetic upgrade. Here's the deal:
DSS was built for a purely brick-and-mortar retail model. As Walmart's business evolved to include online pickup and delivery (OPD) and marketplace, DSS just couldn't keep up with omnichannel tracking. With that, Scintilla was born - the need for better tracking.
There are two versions of this platform: Basic and Charter.
How Do You Log Into Scintilla And Pull A Report?
Log in to Walmart Scintilla with your existing Retail Link credentials and MFA process. There are no separate login credentials for this platform. Once inside, the Report Builder is the primary workspace for Basic users.
The process follows a consistent four-step flow regardless of which dataset you're pulling from.
Step 1: Select your dataset
Navigate to the Datasets tab inside Report Builder. Search for the dataset that you need. Once you click on a dataset name, a Data Preview will appear in the right navigation bar.
Step 2: Choose your columns
Columns can be searched using either Scintilla or old DSS business element names. This is helpful if your team is not familiar with DSS terminology and hasn't fully mapped the new naming conventions yet. Hover over any column name to see its full definition if need arises. For reference, for the Store Sales & Inventory dataset As an example, for the Store Sales & Inventory dataset, the categorisation of the columns is as follows:
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Time Period
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DC Alignment
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Item Info and Hierarchy
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Item Velocity
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Store Inventory
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Store Sales
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Store Fulfillment (OPD)
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Vendor Information
Step 3: Apply filters
Before you create a report, you must select a Walmart time frame. This could be by date, week, month or year. Additional filters can be applied optionally. Common optional filters include item number, DC number, or store number, depending on the level of detail required for the report.
Step 4: Name, Create, and Wait
Name your report before submitting. Use a naming convention that includes the columns and filters selected, so that it makes identification easier. Once the report is submitted, it will take approximately 20–70 minutes to finish. Processing time usually varies by dataset size and query complexity. Do not resubmit if the report hasn’t appeared yet; check the report queue for the status first.
Tip: If you plan to run the same report regularly, save your column selection and filter settings as a template. This avoids rebuilding the same configuration from scratch every time.
Which Reports Matter Most for Suppliers?
Not all datasets are equally useful depending on your role. Here's a quick reference guide to which reports are most relevant for common supplier workflows:
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Use Case |
Dataset to Pull |
Key Columns |
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Shortage claim investigation |
Store Sales & Inventory |
Receipt quantities, Store Inventory, |
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OTIF and delivery tracking |
DC Metrics |
In stock %, Receipt quantities by DC |
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Forecasting and replenishment |
Store Demand Forecast / Order Forecast |
Item Velocity, Time Period |
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Markdown and pricing review |
Store Markup and Markdowns |
Net Initial Margin, Home Office Markdown Amount |
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eCommerce performance |
eComm Sales/ Inventory |
POS quantity, inventory levels by channel |
Dealing with Walmart deductions tied to what you're seeing in Scintilla?
Scintilla gives you data, but that alone isn’t enough. The real challenge is converting that insight into recovered revenue, especially when the process is highly manual and filing windows are tight. iNymbus automates the end-to-end dispute process for Walmart chargebacks, helping suppliers turn those data signals into recovered revenue faster and with less manual work. Schedule a demo with the iNymbus team to see how it works for your Walmart account.
