DSO: Data is stored in 2-dimensional format like a regular table.
Cube data is stored as star schea(multi dimensional data)
Cube is used mainly used for aalytical reports. DSO is used for operational reports.
DSO has the overwrite capability.
Infocube data will get appended.
DSO gives detailed data, Infocube gives aggregated information
DSO can be used as a datastage and fo data cnsolidation
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DataStore object serves as a storage location for consolidated and cleansed transaction data or master data on a document (atomic) level.
This data can be evaluated using a BEx query.
A DataStore object contains key fields (for example, document number/item) and data fields that can also contain character fields (for example, order status, customer) as key figures. The data from a DataStore object can be updated with a delta update into InfoCubes and/or other DataStore objects or master data tables (attributes or texts) in the same system or across different systems.
Unlike multidimensional data storage using InfoCubes, the data in DataStore objects is stored in transparent, flat database tables. The system does not create fact tables or dimension tables.
The cumulative update of key figures is supported for DataStore objects, just as it is with InfoCubes, but with DataStore objects it is also possible to overwrite data fields. This is particularly important with document-related structures. If documents are changed in the source system, these changes include both numeric fields, such as the order quantity, and non-numeric fields, such as the ship-to party, status and delivery date. To reproduce these changes in the DataStore objects in the BI system, you have to overwrite the relevant fields in the DataStore objects and set them to the current value. Furthermore, you can use an overwrite and the existing change log to render a source delta enabled. This means that the delta that is further updated to the InfoCubes, for example, is calculated from two successive after-images.
An InfoCube describes (from an analysis point of view) a self-contained dataset, for example, for a business-orientated area. You analyze this dataset in a BEx query.
An InfoCube is a set of relational tables arranged according to the star schema: A large fact table in the middle surrounded by several dimension tables.
InfoCubes are filled with data from one or more InfoSources or other InfoProviders. They are available as InfoProviders for analysis and reporting purposes.
The data is stored physically in an InfoCube. It consists of a number of InfoObjects that are filled with data from staging. It has the structure of a star schema.
The real-time characteristic can be assigned to an InfoCube. Real-time InfoCubes are used differently to standard InfoCubes.
Hope this helps,
as above mentioned , DSO is 2 dimensional table which can store a detailed level of data ie line item lvel.
DSO have overwrite,additionand noupdate to the fields option.
DSO is mostly used for staging the data from source system and rarely used for report as reports from dso have low perfromance.
Cube is a multidimensional model which have addition and noupdate option for the key figures.
cubes will have summarized data and is more efficient for reporting.
cube is bukilt in the extended star schema concept which faciltate the sharing of master data.
various performance tuning can be done on cube to improve loading and reporting perfromace.
1. Multidimentional - 16 dimention
2. Has additive functionality
3. Performance is better as compared to ods
4. Summerised form of data
5. Has 3 dso
6. Star schema stracture
1. Two dimentional
2. Has overwrite functionality
3. Performance is less as compared to infocube
4. Detailed form of data
5. Has 2 DSO
6. Flat file formate structure.
hope it is helpful
Thanks & Regards