How to Create Custom Datasets in Scintilla

By Bekah Tatem, Content Writer

Last Updated January 7, 2025

6 min read

In this article, learn about:

Pre-built vs. Custom Datasets in Luminate/Scintilla

How to create and save a Custom Dataset

Editing and managing your saved Custom Datasets

Example Custom Dataset for data segmentation analysis

When Walmart transitioned from DSS to Lumiante/Scintilla, suppliers had to quickly adapt to a new way of pulling their reports. Although Walmart has provided template datasets to pull reports, finding one-to-one report equivalents has been challenging for suppliers.

In addition, with Walmart offering two levels of service, Basic (free) and Charter (paid), suppliers on the free service do not have access to the same level of data.

To help suppliers have more flexibility in the reports they create, Luminate/Scintilla Basic now has a feature called Custom Datasets. In this article, we’ll dive into how to use this feature and create tailored reports that meet your unique business needs.

What are Custom Datasets?

Within Luminate/Scintilla, Walmart provides pre-built datasets covering various areas, such as Store Sales and inventory, Order Corecast, and eComm Sales.

While these datasets are helpful, suppliers may have reporting needs that fall outside the confines of these reports; that’s where Custom Datasets come in. Custom Datasets allow suppliers to:

Combine tables from multiple datasets for a more holistic view.

Apply filters to refine data for unique use cases.

Save Custom Datasets for quick use in the future.

How to Create Custom Datasets

Login to Luminate > click New Report > select Custom Dataset beneath My datasets.

Select the data tables you want to include in your report:

You can search for specific tables or field names using the search function.

To see the data attributes included in each table, click on the three dots next to the table name and select Table Details. This allows you to search for an attribute by name or by its DSS alias.

Make sure to select Save dataset at the bottom left-hand corner of the pop-up if you want to save this dataset for continued use.

Click Okay once you’ve finished making your selections.

If you choose to save the dataset, you’ll now have the chance to name it.

Now your dataset is saved, it’s time to create your report.

Here are a few things to keep in mind while creating your report:

To create any report, you need at least one dimension, one metric, and a time period filter.

In Custom Datasets, there is no function to compare multiple time periods. If you need to do this, we recommend pulling multiple reports and combining them in excel.

You can toggle between Columns and Filters options in the top left corner of your screen.

If you’re struggling to find dimensions/metrics you’re used to in DSS, hover your mouse over the name to reveal more details and the DSS alias.

Related Reading: DSS Aliases in Luminate

How to Edit or Delete Your Custom Datasets

Once you’ve saved a Custom Dataset, you can return to the New Report screen to see your saved datasets.

By clicking the three dots in the top right corner of the tile, you can edit, rename or delete the dataset.

Custom Dataset Example: Data Segmentation

Now that we understand the basics of building a Custom Dataset, let’s look at a real-time example. Let’s say a supplier wants to do a data segmentation analysis on an item with low instock levels but high weeks of supply.

The goal of this analysis is to divide store data into distinct groups or segments to identify microtrends much more quickly than drilling down to individual store-level.

To pull the data needed for this analysis, we need a custom report that combines tables from multiple datasets to extract all the attributes needed for the report.

Here’s the information we need:

Attribute Needed for Report	DSS Alias	Walmart Dataset the Attribute Lives In
Prime Item Number	Prime Item Nbr	Item Info and Item Hierarchy
All Links Item Description	Prime Item Desc	Item Info and Item Hierarchy
Store Number	Store Nbr	Store Info
City Name	City	Store Info
State or Province Name	State	Store Info
POS Quantity-This Year	POS Qty	Store Sales
Store On Hand Quantity-This Year	Curr On Hand Qty	Store Inventory

Here are the steps to pulling that information from Luminate/Scintilla using a Custom Dataset:

Login to Luminate > click New Report > select Custom Dataset beneath My datasets.

Select desired tables:

Item Info and Item Hierarchy

Store Info

Store Sales

Store Inventory

Save the Custom Dataset.

Configure the columns with the needed dimensions:

Prime Item Number

All Links Item Description

Store Number

City Name

State or Province Name

POS Quantity-This Year

Store On Hand Quantity-This Year

Set filters.

Click Create Report.

Fill out the required fields and create the report.

Once the report has been created, it can take 30 minutes to an hour for the report to be ready to download. After the report is ready, you can use the segmented data to identify trends, such as which geographic areas are experiencing stock imbalances or sales anomalies. These insights allow for targeted interventions to optimize inventory and improve supply chain efficiency.

This is just one example of how Custom Datasets in Luminate/Scintilla can be used to meet specific business and reporting needs.

If you’ve not yet explored Custom Datasets, we highly recommend trying them. They’re a powerful tool for unlocking deeper insights into your Walmart business and rebuilding reports you used to access in DSS.

Related Reading: What is Segmentation Analysis in Retail?

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