Fine granular application-specific complex filters in remote analytical application integration

1. A method for data analytics in a first data center using transactional data of a second data center, the method being executed by one or more processors and comprising:

receiving, by a query manager service (QMS) executed within the first data center, a query definition provided from a browser of an analytics platform executed within the second data center, the query definition being associated with a user having cell-based permissions, row-based permissions, and field-based permissions assigned thereto for accessing at least a portion of transactional data stored within the first data center;

providing, by the QMS, a raw calculation scenario as an object model based on the query definition and one or more filters;

processing, by the QMS, the raw calculation scenario to provide an enhanced calculation scenario, the enhanced calculation scenario incorporating one or more relationships based on at least one of the one or more filters;

executing, by a calculation engine within the first data center, the enhanced calculation scenario to provide an analytical artifact comprising a query-level calculation view on transactional data stored in the first data center, executing comprising using one or more of a row permission base join, a cell permission base join, and a permission compound join to provide a root compound projection to determine the transactional data that the user is allowed to access based on the field-based permissions; and

transmitting, by the first data center, the analytical artifact to the second data center to perform analytics on at least a portion of the transactional data stored in the first data center.

2. The method of claim 1 , wherein the raw calculation scenario is an analytical calculation scenario represented by a directed acyclic graph, in which one or more base calculation views from the first data center are connected using join relationships.

3. The method of claim 1 , wherein the one or more filters are provided based on user-specific permission metadata that is retrieved from an application executing within the first data center.

4. The method of claim 1 , wherein the enhanced calculation scenario is transferred into an analytical representation that is passed to the calculation engine for execution to provide the analytical artifact.

5. The method of claim 1 , wherein the raw calculation scenario is processed by a filter and wrangling engine to provide the enhanced calculation scenario, the filter and wrangling engine applying column-specific filters and enabling combination of arbitrary columns to tailor the analytical artifact.

6. The method of claim 1 , wherein the one or more filters comprise at least one scope filter that describes joining of at least a portion of data from a data sources, and that indicates at least one parameter to affect data that is to be joined.

7. The method of claim 1 , wherein at least a portion of the transactional data is provided from execution of an application within the first data center.

8. A non-transitory computer-readable storage medium coupled to one or more processors and having instructions stored thereon which, when executed by the one or more processors, cause the one or more processors to perform operations for data analytics in a first data center using transactional data of a second data center, the operations comprising:

receiving, by a query manager service (QMS) executed within the first data center, a query definition provided from a browser of an analytics platform executed within the second data center, the query definition being associated with a user having cell-based permissions, row-based permissions, and field-based permissions assigned thereto for accessing at least a portion of transactional data stored within the first data center;

providing, by the QMS, a raw calculation scenario as an object model based on the query definition and one or more filters;

processing, by the QMS, the raw calculation scenario to provide an enhanced calculation scenario, the enhanced calculation scenario incorporating one or more relationships based on at least one of the one or more filters;

executing, by a calculation engine within the first data center, the enhanced calculation scenario to provide an analytical artifact comprising a query-level calculation view on transactional data stored in the first data center, executing comprising using one or more of a row permission base join, a cell permission base join, and a permission compound join to provide a root compound projection to determine the transactional data that the user is allowed to access based on the field-based permissions; and

transmitting, by the first data center, the analytical artifact to the second data center to perform analytics on at least a portion of the transactional data stored in the first data center.

9. The non-transitory computer-readable storage medium of claim 8 , wherein the raw calculation scenario is an analytical calculation scenario represented by a directed acyclic graph, in which one or more base calculation views from the first data center are connected using join relationships.

10. The non-transitory computer-readable storage medium of claim 8 , wherein the one or more filters are provided based on user-specific permission metadata that is retrieved from an application executing within the first data center.

11. The non-transitory computer-readable storage medium of claim 8 , wherein the enhanced calculation scenario is transferred into an analytical representation that is passed to the calculation engine for execution to provide the analytical artifact.

12. The non-transitory computer-readable storage medium of claim 8 , wherein the raw calculation scenario is processed by a filter and wrangling engine to provide the enhanced calculation scenario, the filter and wrangling engine applying column-specific filters and enabling combination of arbitrary columns to tailor the analytical artifact.

13. The non-transitory computer-readable storage medium of claim 8 , wherein the one or more filters comprise at least one scope filter that describes joining of at least a portion of data from a data sources, and that indicates at least one parameter to affect data that is to be joined.

14. The non-transitory computer-readable storage medium of claim 8 , wherein at least a portion of the transactional data is provided from execution of an application within the first data center.

15. A system, comprising:

a computing device; and

a non-transitory computer-readable storage device coupled to the computing device and having instructions stored thereon which, when executed by the computing device, cause the computing device to perform operations for data analytics in a first data center using transactional data of a second data center, the operations comprising:

receiving, by a query manager service (QMS) executed within the first data center, a query definition provided from a browser of an analytics platform executed within the second data center, the query definition being associated with a user having cell-based permissions, row-based permissions, and field-based permissions assigned thereto for accessing at least a portion of transactional data stored within the first data center;

providing, by the QMS, a raw calculation scenario as an object model based on the query definition and one or more filters;

processing, by the QMS, the raw calculation scenario to provide an enhanced calculation scenario, the enhanced calculation scenario incorporating one or more relationships based on at least one of the one or more filters;

executing, by a calculation engine within the first data center, the enhanced calculation scenario to provide an analytical artifact comprising a query-level calculation view on transactional data stored in the first data center, executing comprising using one or more of a row permission base join, a cell permission base join, and a permission compound join to provide a root compound projection to determine the transactional data that the user is allowed to access based on the field-based permissions; and

transmitting, by the first data center, the analytical artifact to the second data center to perform analytics on at least a portion of the transactional data stored in the first data center.

16. The system of claim 15 , wherein the raw calculation scenario is an analytical calculation scenario represented by a directed acyclic graph, in which one or more base calculation views from the first data center are connected using join relationships.

17. The system of claim 15 , wherein the one or more filters are provided based on user-specific permission metadata that is retrieved from an application executing within the first data center.

18. The system of claim 15 , wherein the enhanced calculation scenario is transferred into an analytical representation that is passed to the calculation engine for execution to provide the analytical artifact.

19. The system of claim 15 , wherein the raw calculation scenario is processed by a filter and wrangling engine to provide the enhanced calculation scenario, the filter and wrangling engine applying column-specific filters and enabling combination of arbitrary columns to tailor the analytical artifact.

20. The system of claim 15 , wherein the one or more filters comprise at least one scope filter that describes joining of at least a portion of data from a data sources, and that indicates at least one parameter to affect data that is to be joined.