BACKGROUND

Enterprises can use third-party systems to maintain data, and analyze data. In some examples, data maintenance, and data analysis are performed in different data centers. For example, an enterprise can maintain its production data in a first data center, and can perform analytics on its production data in a second data center. In analyzing the data, technological inefficiencies can occur. For example, transmitting data from the first data center to the second data center can require a significant amount of technical resources (e.g., processors, memory, bandwidth). Further, storing redundant data in multiple data centers (e.g., production data in the first data center, and a copy of the production data in the second data center for analysis) burdens technical resources (e.g., memory).

SUMMARY

Implementations of the present disclosure include computer-implemented methods for data analytics across multiple data centers. More particularly, implementations of the present disclosure are directed to computer-implemented methods for analytical application integration based on a remote services plug-in. In some implementations, actions include receiving, by a query manager service (QMS) executed within a first data center, a query definition provided from a browser of an analytics platform executed within the second data center, the query definition being stored in a query repository of the second data center, the query definition being validated by the QMS based on analytical metadata, and being stored in a mirror query repository of the first data center, providing, after validation of the query definition by the QMS, a calculation scenario as an object model based on the query definition, executing, by a calculation engine within the first data center, the calculation scenario to provide an analytical artifact including a query-level calculation view on transactional data stored in the first data center, 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. Other implementations of this aspect include corresponding systems, apparatus, and computer programs, configured to perform the actions of the methods, encoded on computer storage devices.

These and other implementations can each optionally include one or more of the following features: the analytical metadata is provided from an application server of the first data center, and is used by the QMS to validate the query definition; a plurality of query definitions stored in the query repository of the second data center are displayed in the browser, and the query definition is selected from the plurality of query definitions for sending to the QMS of the first data center; actions further include enhancing the calculation scenario based on analytical metadata; a query of the transactional data is executed based on the analytical artifact; at least a portion of the transactional data is provided from execution of an application within the first data center; and the query definition is provided to the QMS through one or more application programming interfaces (APIs).

The present disclosure also provides a 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 in accordance with implementations of the methods provided herein.

The present disclosure further provides a system for implementing the methods provided herein. The system includes one or more processors, and a computer-readable storage medium coupled to the one or more processors having instructions stored thereon which, when executed by the one or more processors, cause the one or more processors to perform operations in accordance with implementations of the methods provided herein.

It is appreciated that methods in accordance with the present disclosure can include any combination of the aspects and features described herein. That is, methods in accordance with the present disclosure are not limited to the combinations of aspects and features specifically described herein, but also include any combination of the aspects and features provided.

The details of one or more implementations of the present disclosure are set forth in the accompanying drawings and the description below. Other features and advantages of the present disclosure will be apparent from the description and drawings, and from the claims.

