R365 Intelligence: Adding Data by Dataset

03 Jul 2024
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R365 Intelligence: Adding Data by Dataset

Updated on 03 Jul 2024
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This article is part of R365 intelligence and covers adding data by dataset.

Users can elect to add data to dashboard environments by dataset. Datasets are groups of selected attributes and metrics that can be used together to build visualizations. When data is added by datasets, the group of related attributes and metrics will automatically be added to the datasets panel.

Users can choose from the following preset datasets:

Financial Dataset
Intraday Dataset
Labor Dataset
PMIX Dataset
Purchase and Receiving Dataset
Sales Dataset

Users can also add data to their dashboard environment by manually selecting individual attributes and metrics. To read about adding data using existing data objects, click here.

Adding data by dataset is a feature that is currently in beta. For more information, please reach out to your CSM!

Adding Data by Dataset

To add data by dataset, open a dashboard, then follow these steps:

	From the datasets panel, under 'Add Data,' click Existing Dataset.
	Users will be prompted with the Select Existing Dataset dialog box. Click the datasets folder to open the list of datasets.
	Select the desired dataset from the list.
	After making a selection, click Select.
	Users will be prompted to set parameters for the dataset. This prompt may vary depending on the dataset selected. Set the parameters as needed.	Click the images to enlarge. The following require a start and end date: Financial Dataset Labor Dataset Purchasing & Receiving Dataset Sales Dataset The Intraday Dataset requires an end date for a 15 day range. The PMIX Dataset requires an end date for a 7 day range.
	Once the parameters are set, click Run.
	Once loaded, all the attributes and metrics in the dataset will appear in the datasets panel.

Available Datasets

Each dataset has a preset selection of attributes and metrics. View the collection of data in each dataset below.

Financial Dataset

Attributes		Metrics
Approved vs Unapproved		Credit
Comment		Debit
Date		Net Change
Day of Week		Unapproved
Financial Account Type
Financial Report
Fiscal Period
Fiscal Quarter
Fiscal Week
Fiscal Year
GL Account
GL Account Number
GL Type Name
Legal Entity
Location
Location Categories
Operational Period
Operational Quarter
Operational
Operational Reporting Category
Operational Week
Operational Year
Transaction Number
Transaction Type

Intraday Dataset

Attributes		Metrics
15 Minute Interval		Actual Shift Count
30 Minute Interval		Actual Shift Count PW (Prior Week)
Date		Actual Shift Count PY (Prior Year)
Day of Week		Check Count
Daypart		Check Count PW
Employee Name		Check Count PY
Hour Interval		DT Actual Hours
Location		DT Actual Wages
Location #		DT Scheduled Hours
Location Categories		DT Scheduled Wages
Operational Period		OT Actual Hours
Operational Quarter		OT Actual Wages
Operational Week		OT Scheduled Hours
Operational Year		OT Scheduled Wages
Regular Actual Hours
Regular Actual Wages
Regular Scheduled Hours
Regular Scheduled Wages
Scheduled Shift Count
Total Actual Hours
Total Actual Hours PW
Total Actual Hours PY
Total Actual Wages
Total Actual Wages PW
Total Actual Wages PY
Total Scheduled Hours
Total Scheduled Wages
Void Amount
Void Amount PW
Void Amount PY
Void QTY
Void QTY PW
Void QTY PY

Labor Dataset

Attributes		Metrics
Date		Actual Shift Count
Day of Week		Cash Tips
Daypart		CC Tips
Employee Name		DT Actual Hours
Fiscal Period		DT Actual Wages
Fiscal Quarter		DT Scheduled Hours
Fiscal Week		DT Scheduled Wages
Fiscal Year		OT Actual Hours
Job Department		OT Actual Wages
Job Title		Regular Actual Hours
Legal Entity		Regular Actual Wages
Location		Regular Scheduled Hours
Location #		Regular Scheduled Wages
Location Categories		Scheduled Shift Count
Operational Period		Total Actual Hours
Operational Quarter		Total Actual Wages
Operational Week		Total Scheduled Hours
Operational Year		Total Scheduled Wages
Total Tips

PMIX Dataset

Attributes		Metrics
Date		Check Count By Menu Item
Day of Week		Check Count By Menu Item PW
Daypart		Check Count By Menu Item PY
Delivery Service		Entree Count
Is Entree		Menu Item's Recipe Cost
Legal Entity		QTY Sold
Location		QTY Sold PW
Location Categories		QTY Sold PY
Menu Item		Sales Amount
Menu Item Category 1, 2, 3		Sales Amount PW
Operational Period		Sales Amount PY
Operational Quarter
Operational Week
Operational Year
Order Mode
Service Type

Purchasing and Receiving Dataset

Attributes		Metrics
Date		Ordered Amount
Day of Week		Ordered QTY
Fiscal Period		Received Amount
Fiscal Week		Received QTY
Fiscal Year
Inventory U of M
Item Category 1, 2, 3
Item Name
Item Type
Legal Entity
Location
Location #
Location Categories
Operational Period
Operational Quarter
Operational Week
Operational Year
Reporting U of M
Vendor Item
Vendor Item #
Vendor Name

Sales Dataset

Attributes		Metrics
Date		Check Count
Day of Week		Check Count PW
Daypart		Check Count PY
Delivery Service		Comp Amount
Employee Name		Comp QTY
Fiscal Period		Gross Sales
Fiscal Quarter		Gross Sales PW
Fiscal Week		Gross Sales PY
Fiscal Year		Guest Count
Legal Entity		Guest Count PW
Location		Guest Count PY
Location Categories		Housed Account Amount
Operational Period		House Account QTY
Operational Quarter		Net Sales
Operational Week		Net Sales PW
Operational Year		Net Sales PY
Order Mode		Promo Amount
Service Type		Promo QTY
Tax Amount
Tax Amount PW
Tax Amount PY
Void Amount
Void Amount PW
Void Amount PY
Void QTY
Void QTY PW
Void QTY PY

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What's Next

R365 Intelligence: Adding Data by Existing Objects

Table of contents

Adding Data by Dataset
Available Datasets