Data upload with Platform Manager

PlatformManager Data Upload-Customers

In this lab narrative, we will use the Data Upload option within the Platform Manager tool to load the Customer Master table. The use of PM Data Upload templates provides a quick and easy method for loading all types of master data including pricing tables, data sources, and extensions.

Prerequisites

In order to be able to complete this laboratory exercise, please complete the prerequisite lab(s) before proceeding.

• Platform Manager Login/Setup

• Extract of Customer master data in CSV format

Define Master Data Metadata

Prior to uploading an data using PlatformManager, we must create the metadata associated with the master data entity (Product, Customer, etc). Once the metadata has been defined, then we will be able to reference the attributes for the data mapping phase of the data upload.

Download external Customer data

1. Download and examine the Customer CSV data file

   1. Which columns exist in the file?

      

   2. What is the content of each column? Which data type does each column support (text, number, date)?

Configure the Customer Master Table

Our goal is to use PlatformManager to upload our CSV data into the Customer Master Table. First, you’ll need to configure the columns in the Master Table to match column in the Customert Master CSV file.

1. Click on Master Data | Customer (open the screenshot for a better view)

1. The Customer master table exists out of the box, but the column names are not matching the names in the CustomerMaster CSV file. When you hover over the column label, a tooltip will display the name of the column in the back-end database.

   

2. From this table layout we can see that we have a standard set of defined columns; isParent?, Customer ID, Customer Name, and Last Update These do not need to be renamed.

3. Additionally, we have some customizable columns that are labeled as Attribute1, Attribute2, etc. These are the user defined columns and we will rename them to match the incoming columns on our CSV file.

4. Rename the column Attribute1 to CustomerGroup

   1. Right-click on the label for the Attribute1 column, from the list select Rename and Customize Columns option:

      

   2. Rename it to “CustomerGroup”.

   3. Set the label to “Customer Group”.

   4. Set the type to “String”.

1. Click on Confirm Changes

2. Repeat the steps above for all the other columns in the CSV file using the following assignments:

   1. Attribute 2 = Customer Type

   2. Attribute 3 = Customer Class

   3. Attribute 4 = Region

   4. Attribute 5 = Country

3. At this point we will have exhausted all of the viewable custom columns in our table. In order to make more columns visible, click on the drop-down menu of any column and choose Select Fields to Display option.

   

   From the following click on checkbox for Attributes #6 -12

   Note: Aside from the prebuilt columns, there’s a maximum of 30 columns that can be added to the Customer master table (attribute1 to attribute30)

4. Now we can complete the definition of our remaining columns so the Customer master closely matches the columns in the CSV file. Thus, create the following attributes and associate them with our Attributes:

   1. Attribute6 = Segmentation

   2. Attribute7 = Service

   3. Attribute8 = Customer Currency

   4. Attribute9 = Industry

   5. Attribute10 = Global Customer

   6. Attribute11 = Location

   7. Attribute12 = SubRegion

5. Now ,we will need to save the preference settings for our Customer Master table.

   1. Click on Preferences Manager icon (bottom, right) to create a preference. This will save the layout changes you made to the Customer view (column position, etc).

      

   2. From the Preferences dialog box, click on the Save as New Preference option.

      

   3. Type the Preference name of Customer_default and check option of Set as default preference for me

      

   4. Click Apply button.

Upload Data using PlatformManager

Now that our Customer master table has been defined, we are ready to upload the data in our CSV file into our Customer master.

Login to Platform Manager

1. In browser, go to URL: https://platform.pricefx.com/

   

2. If you are a Pricefx employee, click on Login with O365.

Access Target Partition

1. Navigate to Partitions option

   

2. Then, input (or select) your target partition:

   

3. Click on Data Upload option. Then click on the Add button:

   

4. The Data Upload dialog will now begin:

   

5. First, we must provide a meaningful name for our Data Upload, enter “CustomerMasterLoad” as the name.

6. Next, we need to select the Pricefx entity that we will be loading, click inside the box and the list of possible entities will appear:

   

7. Select the Customer entity. Click Continue button.

8. Next, the Data Upload will need the CSV file that we will be uploading:

   

9. Drag and Drop our CustomerMaster.csv file onto the page.

10. PlatformManager will then parse the CSV file and using default parsing options it will show you a sample layout of the file:

    

    NOTE: Verify that the layout shown here will map to the CSV file uploaded. This view within PlatformManager will be used to map these columns to our Customer master table.

11. Click Continue button.

Data Mapping

Our next phase is the mapping of the columns in the CSV file to the attributes defined in our Customer master table in our partition.

1. When performing the data mapping we should be aware that certain Customer master table columns are mandatory (in most cases this is just the primary key column). The mapping page should now appear:

   

2. The very first column in our mapping will be IsParent?, we don’t need this column to be mapped. So, click on the trashcan icon to delete

   

3. Now, we will begin the mapping process and our first mapping will be for Customer Id (in CSV) to primary key in Customer master (which is Customer Id column). Click in the Choose field drop down:

   

4. Scroll down in the list and locate the customerid column and select it.

5. Next, we will continue to map to the pre-built “out-of-the-box” columns in Customer Master. Map Customer Name to name in Customer Master:

   

6. We don’t need the mapping of the Last Update date for our purposes. So, we can delete this mapping using the trashcan icon:

   

7. Next, perform the following mapping assignments:

   1. Customer Group to attribute1(“CustomerGroup”)

   2. Customer Type to attribute2(“CustomerType”)

   3. Customer Class to attribute3(“CustomerClass”)

8. Then, we have a series of mappings where the input and output columns have already been defined. This is due to the matching column name:

   

9. Next, we need to map the input field of Customer Currency to attribute8(“CustomerCurrency”):

   

10. There should only be 2 unmapped input fields left and here is the mapping for them:

    1. Global Customer to attribute10(“GlobalCustomer”)

    2. Sub-Region to attribute12(“SubRegion”)

       

11. Finally, we don’t need to map the remaining columns of User Group (Edit) and User Group (View). So, simply click on the trashcan icon to delete both of these mappings.

    Thus, the final data mapping should appear as:

    

12. Click Continue button. This will submit the data upload for processing:

    

13. Click on our CustomerMasterLoad upload process and select Show history from the menu options:

    

    The history of the upload will appear as:

    

    NOTE: Review the number of records processed and the number that failed. This upload shows that all records were processed successfully with 0 failures.

14. Additionally, if there were any record failures, then we can review the log records. The upload log records can be found via Data Upload Logs link:

    

15. Finally, to verify it was successful we need to view the Customer Master in our partition. Click on Master Data | Customer:

    

16. When we return to the Customer Master (without the refresh) it will appear as:

    

17. Click on the Refresh option:

    

    NOTE: After the refresh, then the full complement of data should now be available.

PlatformManager Data Upload-Products

In this narrative, we will use the Data Upload option within the Platform Manager tool to load the Product Master table. The use of PM Data Upload templates provides a quick and easy method for loading all types of master data including pricing tables, data sources, and extensions.

Additional templates provide the ability to load a variety of Accelerator packages (data and corresponding logic or data visualizations) directly into our partition.

Figure 1: Use of Platform Manager for data uploads

Prerequisites

In order to be able to complete this laboratory exercise, please complete the prerequisite lab(s) before proceeding.

• Platform Manager Login/Setu

• Extracted Product master data in CSV format

Define Master Data Metadata

Prior to uploading an data using PlatformManager, we must create the metadata associated with the master data entity (Product, Customer, etc). Once the metadata has been defined, then we will be able to reference the attributes for the data mapping phase of the data upload.

Download external Product data

1. Review the Product master CSV data file

   1. Which columns exist in the file?

   2. What is the content of each column? Which data type does each column support (text, number, date)?

      

Configure the Products Master Table

Our goal is to use PlatformManager to upload our CSV data into the Products Master Table. First, you’ll need to configure the columns in the Master Table to match column in the ProductMaster CSV file.

1. Click on Master Data | Products from the menu:

   

2. The Products master table exists out of the box, but the column names do not match the names in the extracted Product master CSV file. When you hover over the column label, a tooltip will display the name of the column in the back-end database.

   

3. From this table layout we can see that we have a standard set of defined columns; Product ID, Label, Product Unit, Currency, Last Update and Pricing Logic. These do not need to be renamed.

4. Additionally, we have some customizable columns that are labeled as Attribute1, Attribute2, etc. These are the user defined columns and we will rename them to match the incoming columns on our CSV file.

5. Rename the column Attribute1 to ProductFamily

   1. Right-click on the label for the Attribute1 column, or click on the dropdown menu Click [Rename and Customize Columns]

   2. Rename it to “ProductFamily”.

   3. Set the label to “Product Family”.

   4. Set the type to “String”.

      

      Click on Confirm Changes

1. Repeat the steps above for all the other columns in the CSV file using the following assignments:

   1. Attribute2 = Business Unit

   2. Attribute3 = Product Category

   3. Attribute 4 = Product Group

   4. Attribute 5 = Product Type

1. At this point we will have exhausted all of the viewable custom columns in our table. In order to make more columns visible, click on the drop-down menu of any column and choose Select Fields to Display option.

   

   From the following click on checkbox for Attributes #6 -11:

   

   Note: Aside from the prebuilt columns, there’s a maximum of 30 columns that can be added to the Products master table (attribute1 to attribute30)

2. Some of the columns in our CSV file can be aligned with some of the pre-built columns that are provided in our Product master “out-of-the-box. Make note of the following attribute assignments that we will NOT need to define:

   1. Product Currency will be assigned to Currency in Product master

   2. Last Update will be assigned to Last Update in Product master

   3. Pricing Logic will be assigned to Pricing Logic in Product master

1. Now we can complete the definition of our remaining columns so the Product master closely matches the columns in the CSV file. Thus, create the following attributes and associate them with our Attributes:

   1. Attribute6 = Product Class

   2. Attribute7 = Discount

   3. Attribute8 = UOM

   4. Attribute9 = Industry

   5. Attribute10 = Product Group Id

2. Save the preferences

   1. Click on Preferences Manager icon (bottom, right) to create a preference. This will save the layout changes you made to the Products view (column position, etc).

      

   2. From the Preferences dialog box, click on the Save as New Preference option.

      

   3. Type the Preference name of Product_default and check option of Set as default preference for me.

1. Click Apply button.

Upload Data using PlatformManager

Now that our Product master table has been defined, we are ready to upload the data in our CSV file into our Product master.

Login to Platform Manager

1. In browser, go to URL: https://platform.pricefx.com/

   

2. If you are a Pricefx employee, click on Login with O365.

Access Target Partition

1. Navigate to Partitions option

   

2. Then, input (or select) your target partition:

   

3. Click on Data Upload option. Then click on the Add button:

   

4. The Data Upload dialog will now begin:

   

5. First, we must provide a meaningful name for our Data Upload, enter “ProductMasterLoad” as the name.

6. Next, we need to select the Pricefx entity that we will be loading, click inside the box and the list of possible entities will appear:

   

7. Select the Product entity. Click Continue button.

8. Next, the Data Upload will need the CSV file that we will be uploading:

   

9. Drag and Drop our ProductMaster.csv file onto the page.

10. PlatformManager will then parse the CSV file and using default parsing options it will show you a sample layout of the file:

    

    NOTE: Verify that the layout shown here will map to the CSV file uploaded. This view within PlatformManager will be used to map these columns to our Product master table.

11. Click Continue button.

Data Mapping

Our next phase is the mapping of the columns in the CSV file to the attributes defined in our Product master table in our partition.

1. When performing the data mapping we should be aware that certain Product master table columns are mandatory (in most cases this is just the primary key column). The mapping page should now appear:

   

2. Now, we will begin the mapping process and our first mapping will be for Product Id (in CSV) to primary key in Product master (which is sku column). Click in the Choose field drop down:

   

3. Scroll down in the list and locate the sku column and select it.

4. Next, we will continue to map to the pre-built “out-of-the-box” columns in Product Master. Map Product Name to label in Product Master:

   

5. Next, perform the following mapping assignments:

   1. Product Family to attribute1(“ProductFamily”)

   2. Business Unit to attribute2(“BusinessUnit”)

   3. Product Category to attribute3(“ProductCategory”)

   4. Product Group to attribute4(“ProductGroup”)

   5. Product Type to attribute5(“ProductType”)

   6. Product Currency to currency

      

6. That brings us to the Last Update column in our CSV file and we will use it to illustrate that NOT ALL data has to be mapped. If it is not mapped, then it will NOT be uploaded. So, click on the trash can for Last Update column mapping:

   

7. Next, we map Pricing Logic to the prebuilt Product Master column of formulaName:

   

8. Next, we to map the following columns:

   1. Product Class to Attribute6(“ProductClass”)

   2. Discount Family to Attribute7(“Discount”)

9. Notice that the next two columns (UOM and Industry) are mapped automatically because the names were a direct match between source and target.

10. Next, we must map Product Goup Id to Attribute10(“ProductGroupId”).

    

11. Finally, we don’t need to map the remaining columns of User Group (Edit) and User Group (View). So, simply click on the trashcan icon to delete both of these mappings.

    Thus, the final data mapping should appear as:

    

12. Click Continue button. This will submit the data upload for processing:

    

13. Click on our ProductMasterLoad upload process and select Show history from the menu options:

    

    The history of the upload will appear as:

    

    NOTE: Review the number of records processed and the number that failed. This upload shows that all records were processed successfully with 0 failures.

14. Additionally, if there were any record failures, then we can review the log records. The upload log records can be found via Data Upload Logs link:

    

15. Finally, to verify it was successful we need to view the Product Master in our partition. Click on Master Data | Products:

1. When we return to the Product Master (without the refresh) it will appear as:

   

2. Click on the Refresh option:

   

   NOTE: After the refresh, then the full complement of data should now be available.