Active Data Table — Activating a request transfers the data from the inbound table to the active data table. From this point of view, the active data table behaves like an E fact table of a classic InfoCube. Validity Table — The validity table stores the time interval s for which non-cumulative values have been loaded into the InfoProvider. Reference Point Table — The reference point table contains reference points for non-cumulative key figures.
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Select Currencies and choose a transfer mode. No data is updated. The new entries are updated on the database. The tables are rebuilt, old data is deleted. Then Execute. Transfer exchange rates. Maintain Exchange rates and the transfer mode.
Check the read mode for queries. For a query, the OLAP processor can read the data from the fact table in one of three ways: Reading all of the data When executing the query in the Business Explorer all of the fact table data that is needed for all possible navigational steps in the query, is read in the main memory area of the OLAP processor.
Therefore, all new navigational states are aggregated and calculated from the data of the main memory. Reading the data on demand The OLAP processor only requests the corresponding fact table data that is needed for each navigational state of the query in the Business Explorer.
Therefore, new data is read for each navigational step. The most suitable aggregate table is used and, if possible, already aggregated on the database. The data for identical navigational states are buffered in the OLAP processor. Reading on demand when expanding the hierarchy When reading data on demand 2 , the data for the entire - meaning completely expanded - hierarchy is requested for a hierarchy drilldown.
For the read on demand when expanding the hierarchy 3 , the data is aggregated by the database along the hierarchy and is sent to the start level of the hierarchy highest node in the OLAP processor. When expanding a hierarchy node, the children of the node are then respectively read on demand. In general, the reading of data on demand 2 provides much better performance than reading all the data 1. This read mode should especially be considered for queries with many, free characteristics.
A query that contains two or more free characteristics from different dimensions e. For large hierarchies, aggregates should be created on the middle level of the hierarchy and the start level of the query should be smaller or the same as this aggregate level. For queries about such large hierarchies, the read on demand when expanding the hierarchy method 3 should be set. After choosing Return, the read mode of your queries is the read mode recommended by SAP.
Switch off all system traces. Execute transaction ST Check trace tool. Verify there are no users activated for logging. Source System Enter the logical system of your source client and assign the control parameters you selected to it. You can find further information on the source client in the source system by choosing the transaction SCC4.
Maximum Size of the Data Packet When you transfer data into BW, the individual data records are sent in packets of variable size. You can use these parameters to control how large a typical data packet like this is. If no entry was maintained then the data is transferred with a default setting of 10, kBytes per data packet. The memory requirement not only depends on the settings of the data packet, but also on the size of the transfer structure and the memory requirement of the relevant extractor.
Maximum Number of Lines in a Data Packet. Upper-limit for the number of records per data packet. Frequency 1 is set by default. This means that an Info Idoc follows every data Idoc. In general, you should select a frequency between 5 and 10 but no higher than The bigger the data IDoc packet, the lower the frequency setting should be.
In this way, when you upload you can obtain information on the respective data loading in relatively short spaces of time. With the help of every Info IDoc, you can check the BW monitor to see if there are any errors in the loading process.
If there are none, then the traffic light in the monitor will be green. The Info IDocs contain information such as whether the respective data IDocs were uploaded correctly. So many more settings we need to do..
How to Handle Inventory Management Scenarios in BW (NW2004) BW7
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GRIFFIN PODSTAWY ZARZADZANIA PDF
This function is used to make changes to non-cumulative that have yet to be initialized visible at a later point in time. When loading and compressing historical transaction data records, note the following: Before compression, InfoCubes into which historical transaction data records were loaded, show potentially incorrect results. These inconsistencies are resolved during the compression process. After historical transaction data records are loaded into an InfoCube, the corresponding aggregates contain incorrect data. All incorrect aggregates are therefore deactivated and rebuilt during a compression run. For performance reasons, we recommend deactivating aggregates before a compression run with historical data, and rebuilding them after the compression run.
Procedures for implementing a snapshot scenario with custom DataSources
In case you have in addition to 0calday e. If non-cumulative key figures are aggregated across several validity characteristics it may be necessary to determine non-cumulative values outside the corresponding validity periods. For this the system determines a kind of superset of all involved validity periods, please see note for more details to this. In case the validity object is drilled down, the system highlights the values which are outside the validity by setting of square brackets. Lets discuss this again with the help of our example.
SAP First Guidance Collection for SAP BW powered by SAP HANA – Application Specific
Kigagis Please help me to explain. Browse the Latest Snapshot. Using Literal Filename and Path. Inventory data sources and janagement data flow is standard one. Please tell me are the start and end periods are coming as transaction values i. Hav a nice Time Technology Overview and Introduction. Hi Monica, I am also working on these extractors.
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