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Part 1 covers technical steps for attribute view creation & Little introduction to COPA & Attribute View.

Controlling & Profitability Analysis in SAP HANA


Profitability Analysis (CO-PA) enables you to evaluate market segments, which can be classified according to products, customers, orders or any combination of these, or strategic business units, such as sales organizations or business areas, with respect to your company’s profit or contribution margin.

The aim of the system is to provide your sales, marketing, product management and corporate planning departments with information to support internal accounting and decision-making.


Two forms of Profitability Analysis are supported: costing-based and account-based.


  • Costing-based Profitability Analysis is the form of profitability analysis that groups costs and revenues according to value fields and costing-based valuation approaches, both of which you can define yourself. It guarantees you access at all times to a complete, short-term profitability report.


  • Account-based Profitability Analysis is a form of profitability analysis organized in accounts and using an account-based valuation approach. The distinguishing characteristic of this form is its use of cost and revenue elements. It provides you with a profitability report that is permanently reconciled with financial accounting.

You can also use both of these types of CO-PA simultaneously.


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COPA Model in SAP HANA

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Before creating information models you need to provision the source data to SAP HANA.

Customer attribute view is created based on KNA1, T005U & T005T tables.

Product attribute is created based on MARA & MAKT tables.


Actual Analytic view is based on CE1IDEA & Customer & Product Attribute Views.

Plan Analytic view is based on CE2IDEA & Customer & Product Attribute Views

Attribute View introduction

Attribute Views are used to model an entity based on the relationships between attribute data contained in multiple source tables.

You can model the columns & calculated elements within an attribute view.

Simple attributes are individual non-measurable analytic elements that are derived from the data foundation.

For example, PRODUCT_ID and PRODUCT_NAME are attributes of a PRODUCT subject area.

Calculated attributes are derived from one or more existing attributes or constants.

For example, deriving the full name of a customer (first and last name), assigning a constant value to an attribute that can be used for arithmetic calculations.

Defines joins between tables and selects a subset (or all) of their columns. The rows selected can also be restricted by filters. An additional application of attribute a view is as dimensions in the star schema defined by an analytic view. In this use

case, the attribute view adds more columns and also hierarchies as further analysis

Criteria to the analytic view. In the star schema of the analytic view the attribute view is shown as a single dimension table (although it might join multiple tables), that can be joined to a fact table.

  SAP HANA modeler is a graphical data modeling tool which allows you to design analytical models and later analytical privileges, that governs the access to those models.

1.Create a new package. Select the Content folder > Right Click > New Package.

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2.Select your package, Give the name details.

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3.As a result you should see following screen.

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4.Drag & drop MARA & MAKT tables in to Data Foundation.

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5.In the details screen, select MATNR & Right Click > Add to Output.

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6.In the properties screen, select Key Attribute change it to True to enable as Key.

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7. Connect MATNR(MARA) to MATNR (MAKT), In the properties select join type as Text Join , Language column as SPARS &          Cardinality as 1:1.

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8. Select MTART, MBRSH, MATKL fields as Add to Output.

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9. As a result you should see all columns in the output frame & Click Validate.

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10. Activate the attribute view.

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11.Click Data Preview to see the output of the view.

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12.Click Raw Data to see the output of the view in the column format.

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13.Click Analysis to see the output of the view in the graphical representation.

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14.Click Distinct Values to see the distinct values.

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Attribute View for Customer

1. Select package – Click New & select attribute view

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2. Specify the technical name.

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3.Drag & drop KNA1,T005T & T005U table in to Data Foundation , In the details screen , select KUNNR & Right Click > Add to Output.

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4.Connect LAND1(KNA1) to LAND1 (T005U), In the properties select join type as Text Join , Language column as SPARS & Cardinality as 1:1.

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5.Connect REGIO(KNA1) to BLAND (T005U), In the properties select join type as Text Join , Language column as SPARS & Cardinality as 1:1.

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6.Connect LAND1(KNA1) to LAND1 (T005T), In the properties select join type as Text Join , Language column as SPARS & Cardinality as 1:1.

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7. Select LAND1,ORT01,REGIO,LANDX & BEZEI fields as Add to Output.

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8.As a result you should see all columns in the output frame.

   Validate & Activate View

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9.Click Data Preview to see the output of the view

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10.Click Data Preview to see the output of the view.

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Navigate to the Catalog.  Select the folder _SYS_BIC, expand Column Views and locate your Attribute Views.

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2. COPA E2E Modelling Scenario in SAP HANA 1.0 Part_2

3.  COPA E2E Modelling Scenario in SAP HANA Part_3

4. Script Based Calculation View in COPA Scenario_Part 4


Thanks for reading.

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9 Comments

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  1. Sreeverdhan Potavathri

    CO-PA Scenario was already covered in the training material for both SP4 and SP5 in 300 series. It was great to put in pictorial format. The above example looks to be based on Cost based with Contribution Margins example.

    thanks the blog and nice explanation.

    It would be great if you can add Account based and I was looking for some scenarios for a General Ledger based reporting in SAP HANA and landed in your blog.

    Good luck with your part 2 and 3.

    (0) 
    1. Mahesh Kumar CV Post author

      I agree with you , This is genral platform to share knowledge , This will be helpful for those who are not taken training from SAP.

      Shortly you can expect some blogs on GL.

      (0) 
  2. Aby Jacob

    Dear Mahesh,

    Thanks for all the info/pictures, This is valuable for many Customers.

    Looking forward to more such inputs … 🙂

    (0) 

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