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Semantic Layers in SAP Hana

 1. Consumption of HANA views /Tables/NUDT to Prepare BO Semantic buyer;-

UDT is a (universe designer tool) to prepare structure based on report requirement by using Table structure in HANA DB.

 

NOTE:-

House we can bring only table structure from database instead of disturbing data in DB

  • We can design structure joining tables band business, so we need to concentrate on cardinality (1-1, many to 1, 1 to many, many to many)
  • While property structure will get some complex scenario like loop & traps
  • Loops it brings less amnt of data rather then actual data in attributes So, we can solve the loops by shortcut, alias, context
  • Traps bring more data them actual date so, we can slowed this problem by using context and we can add features like hierarchies, disturb values, cascading disturb values, cascaded objects based on requirements.

Procedure to create semantic layer (UDT)

Create ODBC connection

  1. Go to start   Untitled   settings  Untitled   content panel    Untitled     administrator tools    Untitled   Data source (ODBC)
  2. Select system ADM (tab)  Untitled   click on sys adm (tab)   Untitled  click on add   Untitled  select HDBODBC32 connection
  3. Provide ODBC connection name: __________

Port NO   :___________

Click on connect   Untitled   provide usr name : _________

& Password:_________
and       OK

  1. Log on to universe design tool create universe click on new connection select connection type is secured   Untitled    provide connection name (universe connection Untitled  Select ODBL connection type (SAP  Untitled  SAP – In __ memory)  Untitled  ODBC  provide universe parameters and   OK
  • Insert required table & view and prepare the structure and follow above mention methodologies create classes & objects
  • Cheek the integrity
  • Save and export to the system repository
  • We can create web1, crystal, explore and dashboard

 

2)   Consumption of HANA views | Tables in IDT To prepare BO semantic layer

 

It is a semantic layer which contains business layer to provide data to the reports

Prouder:-

Log on IDT

  • Create new project
  • Create new connection

 

 

NOTE: Connection should be secured & rolap type

  • Select our HANA ODBC connection
  • So will get connection in the form of .CNS
  • After we need to export connection into system repository
  • Create Data foundation by selecting our shared connection
  • Select required tables and views and prepare the structure
  • We need to join the tables and views with the coordinates based on business report requirement
  • We need to follow rules to designs the structure
  • Create business layer
  • Select our data foundation, save, & export into the system repository
  • After exporting our business layer we can create reports like web 1, explorer, crystal reports

 

NOTE:- For both UDT & IDT we can create views from ‘ – sys – bic’ for catalog only

For tables we can bring form any catalogs

 

Reports:-

  1. webi reports:- It is a web paged report which provides refreshed values
  • We can create web-I reports from UDT & IDT
  • We can create web-I reports in launch – pad 

 

Procedure:-

  1. 1. Create ODBC connection
  2. create universe from UDT

Or                                           Export into system Repository

Business layer from IDT

  1. Log on to launch pad
  2. create query from universe select our universe
  3. Design Query
  4. Based on report requirement, we can use measures, attributes, hierarchies, files, based on report requirement
  5. execute query will get report
  6. so, based on requirement we can add features like alerts, ranking, variables, filters, build up drill down, chaas, tables & relative positions ………………. Etc
  7. Save reports & publish into public folders
  8. We con use webi reports for xceleries & live office

 

Dash boards:-

It is which contains tables, charts, & other components

Procedure:-

  1. create ODBC connection
  2. create IDT
  3. use OLAP connections (BICS)
  4. Create SAP dashboard
  5. Select BW connection   Untitled   we can take connection from BICS & cube & views (calculated & analytic)
  6. Select component to model data
  7. prepared dashboards by using alerts like extra ranking.

 

 

 

3)Crystal reports:

  • It mainly depends on xcel, they are mainly cal based report
  • We can create crystal reports from views & tables by using HODBC & TDBC connections directly
  • Here no, need to create JDBC & ODBC

Procedure:

  1. Create ODBC connection for SAP HANA
  2. Create crystal reports Untitledselect HANA ODBL connection as a source
  3. Select tables & prepare schema
  4. In a field explorer  select required column from the table
  5. Apply the cosmetics prompts, alerts, calculated columns, variables, filters, links …… etc
  6. Based on Requirements we need to creates sub – queries | reports
  7. Save export into the B.O Enterprise

 

 

4) EXPLORER:_

It is a web – based dashboard

Procedure:-

  1. Create ODBC connection
  2. log on to IDT
  3. create project
  4. Create relational connection (secured) (.CNS)
  5. Export into system repository will get in the form of CNX
  6. Create data foundation by selecting connection
    Insert required tables & views and the prepare the structure based on the reles
  7. create business layer
  8. select our data foundation, & save our Business layer and export into system repository
  9. so, will get in the form of UNX
  10. Log on to the explorer by providing URL
    http://sysname:8080/explorer
  11. log on & click on manage spaces
  12. click on new query
  13. select out business layer
  14. prepare query
  15. and save it
    1. NOTE:-The query must have at least one attribute measure
  16. create index for our query
  17. we can drill on the report
  18. based upon the repot requirement we can apply cosmetics like scenery order, charts, alerts tables and publish into the public folders.

 

Appendix procedure;-

Procedure:-

To maintain consistency with SQL standard, functions will be called procedures

The following example shows procedure implemented is SQL script based on the new syntax.  To better illustrate the high – level concept, we omitted details.

CREATE PROCEDURE get out put (in out integer, in currency varchar (3),

Out out put – pubs tt – publishers,

Out out put – year tt – years,

LANGUAGE SQL SCRIPT READS SQL DATA as BEGIN

Big – pub – ids = SELECT publisher FROM (query1) books

Group by publisher HAVING COUNT (isbrr) .: cnt:

Big – pub – books = SELECT title, price —- Query 2

FROM : big – pub –Ids, publishers, books

HERE pub – ID = fid and pub = id = publisher

AND crcy = currency;

Out put – puts = SELECT SUM (Query 3)(price)

FROM : big – pub – books GROUP by publisher:

Out put – year + SELECT SUM (price)

FROM :  big – put – books GROUP by year;

END;

The SQL script above defines read –only procedure which have 2 scalar input parameters and 2 output parameters or type table.  As different languages are supported in the body of the procedure, the Implementation language are supported in the body of the procedure, the Implementation language is defined to be SQL script. More over, the procedure is a read – only procedure. Here it is free of side effects and can be called by other read – only procedures.

The first line contains a SQL query Q1 which identifies big published  (using the input parameter cnt). After wards, detailed information about these publishers along with their corresponding books is determined in Query Q2. Finally. This information is aggregated in two different way queries W3 (aggregated per publisher ) and Q4 (aggregated per year) respectively. The resulting tables constitute the output of the functions.

 

Screenshot_1

 

Aprocedure is SQL script that only uses declarative constructs can be completely translated into an acyclic data flous graph where each node represents a data trans formation. The example above could be represented as a data flous graph In the picture similar to SQL queries the graph is analyzed and optimized before execution

For optimization the sub graph of the called functions is merged with the graph of calling function and the resulting graph is the optimized

The optimization applies security rules as SQL optimizer use’s for its logical optimization then the plan is translated into a  physical plan which consists of physical data base operations

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