Loading Master Data Attributes using Flat File

Loading Master Data using Flat file

1. Create info object for ZTES_MATL with Type Char and length 18.

2. Add attributes like 0MAT_TYPE, 0GROSS_WT ETC based on your file structure.

3. Insert your newly created object as info provider under your Info Area.

 

 

4. Now choose Data Sources option from left side and   Create the data source structure by entering the info object in the sequence of your file for PC_FILE.
 For this choose  option under Modeling of AWB-Data sources- Flat file-File as source

 

 

  Insert info objects Attributes  from your newly created Info object  under Template column so that you get     all  technical details are copied . First row should be your newly created Info object.

5.  Save your EXCEL File as .CSV( Comma Delimited ). Make sure all your data is in CAPTITOL unless otherwise required, then change your Info Object to accept the SMALL letters.

6.. Give this file Path under Extraction Tab and change the entries for DATA SEPARATOR TO ' ,'.  and enter the no of rows to be excluded like Headers etc.

7  .Activate the data Source.  
8.You can see the preview of your data by choosing PREVIEW Tab.
9 If everything is fine then you will see the entries like as below.  

 

10. Choose Create Transformation from Context Menu of Test Material Attributes

 

    
11.Choose FLAT File as source and Master Data attributes from respective selections , and select your Data Source created above.

 

12.Complete the mapping by creating link between left and right structures.
Since Both source and Target are same , you don't need to anything as system proposes mapping unless if you want to change.

13.If you need to change the rule instead of direct assignment , then choose the appropriate function from RULE
14. Create info package from Context menu of Data Source and execute the same choosing Schedule Tab.  See the Progress by choosing Monitor from the Toll bar. Once you see the Success light then your extraction is completed.

 

15. Create DTP and  execute the same. Once  you get POPUP , choose YES to see the progress.
      Here also you will GREEN LIGHT  FOR  success.

16. Finally the data can be viewed by choosing the option Display Data from Context menu of your Info Object. Also choose the objects you need to display by choosing option Field selection for output. choose the column names , click F8  and again F8.

Change Log

Selective Deletion of Change log from DSO


1. Choose Manage from Context Menu of the DSO

2. Select Delete Change Log Option from Main Menu under Environment

3. Choose appropriate button from the screen either Older than or Before a date

4. Click on Start button and that will delete the log

Process Chain

Including the deletion of requests from the PSA in the process chain

If you want to automate the deletion of requests from the PSA, you can include an appropriate process variant in a process chain.

1. In the maintenance of process variants, you specify the DataSource for which the requests need to be deleted by using the implicit selection of a PSA table or an InfoPackage.

2. Specify the requests that need to be deleted by determining the days or dates. You also have the option to specify whether you only want to delete successfully updated requests, and/or only incorrect requests, that are no longer updated in a data target (this is only valid for transaction data).

3. Save your entries and go back.

4. In the following screen, confirm the addition of the process variants in the process chain.

Data Initizlization in ECC

Steps for Initializing source Data in ECC
1. Activate DataSource

2. Maintain Extract Structure

(you cannot create new Extract Structures!)

3. Generate DataSource / Repl. DataSource

4. Activate Extract Structure

5. Delete Setup tables using LBWG.

6. Check Extractor Update (optional)

7. Perform Extractor Setup

8. Define periodic V3 update jobs

9. Create InfoPackage in BW for initialization

10. Create InfoPackage in BW for periodic Delta

11. Delete Initialization Table ‘LBWG’

KPI Definitions

Dimensions :


 Perfect Order

 Complete Order

 Order Line Fill

Definitions

 % Complete: % of number of orders fully dispatched at first dispatch

 % Perfect Orders: % of orders on time and in full

 % Value Fill: % of value/quantity dispatched at first dispatch

 % On Time: % of orders dispatched on or before the requested delivery date

 % Line Fill: % of number of lines fully dispatched at first dispatch

Possible solution

 Build a new DSO to for the Metrics based on DSO of Orders,Sales Order Schedule Line . Deliveries using Shipment Info and Status with count as Key figure for each dimension.

 Built an Cube over this DSO and built Query over this.

FOX Formula for Planning

Definition:

Formulas define how transaction data is to be processed in order to generate plan data. Formula functions enable you to use extended mathematical functions to calculate plan data. In addition to different calculation functions, which you can use for value assignment in formulas, there is also the possibility to model complex flow structures with the formula language FOX  (FOrmula eXtensions).

How to specify a record in a formula:
- You use { }-operands to access transaction data. Syntax:

{field to be changed 1, field to be changed 2, …, field t.b.c. n}

- If "key figure name" is a field to be changed, then each key figure in

a record can be addressed individually.

- If "key figure name" is not in the fields to be changed, then all key

figures of the data record will be changed according to the formula.

- Use F4-help for entering { }-operands.

How to read and write data:

 - To read data, put the { }-operand on the right hand side of equations.

- To write data, put the { }-operand on the left hand side of equations.

Do not forget the "." at the end of each statement.

Example 1:

Calculate sales amount from sales quantity and a fixed price

- Field(s) to be changed: Key figure name

- Formula: {0AMOUNT} = {0QUANTITY} * 100.

- Note: If key figure is the only field to be changed, you do not need

the { } brackets: 0AMOUNT = 0QUANTITY * 100.



Example 2:

For each product copy data from the current year (2005) to the

next year (2006)

- Field(s) to be changed: Fiscal Year

- Formula: {2006} = {2005}.

- Note: You do not have to care about the product because of the

subsets ("automatic FOREACH")!



FOX Formulas – Foreach Statement

You have to define a local variable:

DATA year TYPE 0fiscyear.

Use this variable in the Foreach Statement:

FOREACH year.

{year} = {2004} * 1.05.

ENDFOR.

The values for YEAR are taken from the records in the selection of

the planning package.

Assume we have data records for year 2005 and 2006.

First loop: YEAR is replaced with 2005, system calculates

{2005} = {2004} * 1.05.

Second loop: YEAR is replaced with 2006, system calculates

{2006} = {2004} * 1.05.



Variables

Example of formula using one planning area variable and three local

variables:

DATA ZCURPER TYPE 0FISCPER.

DATA ZFCPER TYPE 0FISCPER.

DATA COUNTER TYPE I.

* Copy current period to the next 5 forecast periods

ZCURPER = VARV('PERCUR').

DO.

COUNTER = COUNTER + 1.

ZFCPER = TMVL(ZCURPER,COUNTER).

{0COPASLQTY,ZFCPER,RFC} = {0COPASLQTY,ZCURPER,ACT}.

IF COUNTER = 5.

EXIT.

ENDIF.

ENDDO.



Standard Fox Statements

Using Time Characteristics TMLV( Characteristic, Offset )

- offset: to add for example one year you would select 1 as offset

IF … ELSEIF … ENDIF.

- ELSEIF if you want to integrate several alternatives

IF … ELSE … ENDIF.

- ELSE if no condition mentioned before works

Loop Constructs

DO … ENDDO.

- Needs explicit EXIT Condition

FOREACH … ENDFOR.

- Ending, if last selected characteristic value or key figure is reached

Master Data Classification

Master Data assigned to Multiple Characteristics for Classification
The standard Classification Functionality for Extracting the Master Data for Material/ Customer etc is not helpful when there are multiple characteristic values assigned to Master Data Object for example Check Boxes. The Standard Solution will extract only the first available Characteristic Values only. To get all the assigned Values for any given


Characteristic required Custom built extractor. Let us see that are the steps to be followed. This example guides you to bring in Customer Data for Ship To, where each Ship To Customer is assigned to different Groups for Reporting Purpose. The solution holds well for any Master Data Object, you can achieve this by restricting Class Type.


1. Create a class for Customer Class Type 011 using T. Code CL01 and

Create the Characteristics.

The Group Detail look like this

The associated values are stored in tables CAWN and CABN

2. Assign the above created groups to Ship using T.Code XD02 .

3. These Values are stored in table AUSP. This table stores all the classification data related to any Master Data objects by Class Type.

4. Create the Data source based on this table for BW Extraction

5. Test the Extractor using RSA3.

6. Create Info object to hold Classification Assignments as Master Data. Since a customer can be assigned more than one Group 0SHIP-TO is compounded with Group. Group and its assigned Values, Ship To are added as attributes. Ship to be added two times here as we plan to create an Infoset as compounded object does not allow for Join with other object from any source. Need to create a new Ship-To with reference to 0SHIP_TO.

7 Create Transformation and DTP for the same.

8. Create Infoset between the Master data object, Billing Cubes by linking Ship To. Choose only required Objects for reporting.

9. Built a Query on the Info Set and here is the sample result.

SAP

SAP WiKi