Abstract: Disclosed herein are system, computer-implemented method, and computer program product (computer-readable storage medium) embodiments for implementing bill-of-materials (BOM) lifecycle management. An embodiment operates by creating a first database entry. The first database entry may also include a first executable code instance and list of items, which may include at least part of a BOM. Additionally, a second database entry may be created and may include a second executable code instance. Based on execution of the first code instance and the second code instance, at least one processor may automatically perform further processing.

Abstract: In an example embodiment, zone information is received from a distributed database, the zone information including a mapping between each of a plurality of client applications and a corresponding zone. Then a first adapter is assigned to a first client application based on the mapping. A second adapter is then assigned to a second client application based on the mapping. When data is received from the first client application, the data from the first client application is parsed using the first adapter, producing output to a search core and an indexing core associated with a zone corresponding to the first client application.

Abstract: Disclosed herein are system, computer-implemented method, and computer program product (computer-readable storage medium) embodiments for implementing bill-of-materials (BOM) lifecycle management. An embodiment operates by creating a first database entry. The first database entry may also include a first executable code instance and list of items, which may include at least part of a BOM. Additionally, a second database entry may be created and may include a second executable code instance. Based on execution of the first code instance and the second code instance, at least one processor may automatically perform further processing.

Abstract: A metadata management system receives metadata changes and automatically updates a metadata architecture which maps the data. The metadata changes may be received through a simple user interface by a user or administrator. Once received, the system may automatically update schemas and data transformation code to process data according to the new data mapping preference. The system may handle metadata updates in a multi-tenant system having one or more applications per tenant, and may update data for a single tenant and 1 or more tenant applications in a multitenancy.

Abstract: In an example embodiment, primary data is received from a first tenant in a computer network, the primary data formatted based on a first version of a schema. Then a schema definition for the first version of the schema is obtained. The primary data is then parsed, the parsing including storing a schema version number for the first version of the schema. The primary data is indexed, by obtaining, using the schema version number for the first version of the schema, a schema definition for a most recent version of the schema; applying schema evolution to the primary data by applying one or more transforms to the primary data, the one or more transforms created using the schema definition for the first and most recent versions of the schema, causing the primary data to be converted to the most recent version of the schema; and indexing the converted primary data.

Abstract: A system fetches consistent datasets in batches for a given period of time and provides the ability to retrieve each batch. Batches of data may be fetched for an interval of time. The present system may fetch new or changed data from different cloud/on-premise applications. It will store this data in the cloud or on-premise to build data history. As the system fetches new data, existing batches of data will not be overwritten. New batches of data are created as new versions so that change history is preserved. Past batches of data for a past time period may be provided to one or more tenants.

Abstract: A system fetches consistent datasets in batches for a given period of time and provides the ability to retrieve each batch. Batches of data may be fetched for an interval of time. The present system may fetch new or changed data from different cloud/on-premise applications. It will store this data in the cloud or on-premise to build data history. As the system fetches new data, existing batches of data will not be overwritten. New batches of data are created as new versions so that change history is preserved. Past batches of data for a past time period may be provided to one or more tenants.

Abstract: An extract-transform-load (ETL) platform fetches consistent datasets in a batch for a given period of time and provides the ability to rollback that batch. The batch may be fetched for an interval of time, and the ETL platform may fetch new or changed data from different cloud/on-premise applications. It will store this data in the cloud or on-premise to build data history. As the ETL platform fetches new data, the system will not overwrite existing data, but rather will create new versions so that change history is preserved. For any reason, if businesses would like to rollback data, they could rollback to any previous batch.

Abstract: A metadata management system receives metadata changes and automatically updates a metadata architecture which maps the data. The metadata changes may be received through a simple user interface by a user or administrator. Once received, the system may automatically update schemas and data transformation code to process data according to the new data mapping preference. The system may handle metadata updates in a multi-tenant system having one or more applications per tenant, and may update data for a single tenant and 1 or more tenant applications in a multitenancy.

Abstract: A system fetches consistent datasets in batches for a given period of time and provides the ability to retrieve each batch. Batches of data may be fetched for an interval of time. The present system may fetch new or changed data from different cloud/on-premise applications. It will store this data in the cloud or on-premise to build data history. As the system fetches new data, existing batches of data will not be overwritten. New batches of data are created as new versions so that change history is preserved. Past batches of data for a past time period may be provided to one or more tenants.

Abstract: In an example embodiment, primary data is received from a first tenant in a computer network, the primary data formatted based on a first version of a schema. Then a schema definition for the first version of the schema is obtained. The primary data is then parsed, the parsing including storing a schema version number for the first version of the schema. The primary data is indexed, by obtaining, using the schema version number for the first version of the schema, a schema definition for a most recent version of the schema; applying schema evolution to the primary data by applying one or more transforms to the primary data, the one or more transforms created using the schema definition for the first and most recent versions of the schema, causing the primary data to be converted to the most recent version of the schema; and indexing the converted primary data.

Abstract: A metadata management system receives metadata changes and automatically updates a metadata architecture which maps the data. The metadata changes may be received through a simple user interface by a user or administrator. Once received, the system may automatically update schemas and data transformation code to process data according to the new data mapping preference. The system may handle metadata updates in a multi-tenant system having one or more applications per tenant, and may update data for a single tenant and 1 or more tenant applications in a multitenancy.

Abstract: In an example embodiment, zone information is received from a distributed database, the zone information including a mapping between each of a plurality of client applications and a corresponding zone. Then a first adapter is assigned to a first client application based on the mapping. A second adapter is then assigned to a second client application based on the mapping. When data is received from the first client application, the data from the first client application is parsed using the first adapter, producing output to a search core and an indexing core associated with a zone corresponding to the first client application.

Abstract: An extract-transform-load (ETL) platform fetches consistent datasets in a batch for a given period of time and provides the ability to rollback that batch. The batch may be fetched for an interval of time, and the ETL platform may fetch new or changed data from different cloud/on-premise applications. It will store this data in the cloud or on-premise to build data history. As the ETL platform fetches new data, the system will not overwrite existing data, but rather will create new versions so that change history is preserved. For any reason, if businesses would like to rollback data, they could rollback to any previous batch.

Abstract: A system fetches consistent datasets in batches for a given period of time and provides the ability to retrieve each batch. Batches of data may be fetched for an interval of time. The present system may fetch new or changed data from different cloud/on-premise applications. It will store this data in the cloud or on-premise to build data history. As the system fetches new data, existing batches of data will not be overwritten. New batches of data are created as new versions so that change history is preserved. Past batches of data for a past time period may be provided to one or more tenants.

Abstract: A system fetches consistent datasets in batches for a given period of time and provides the ability to retrieve each batch. Batches of data may be fetched for an interval of time. The present system may fetch new or changed data from different cloud/on-premise applications. It will store this data in the cloud or on-premise to build data history. As the system fetches new data, existing batches of data will not be overwritten. New batches of data are created as new versions so that change history is preserved. Past batches of data for a past time period may be provided to one or more tenants.

Abstract: An extract-transform-load (ETL) platform fetches consistent datasets in a batch for a given period of time and provides the ability to rollback that batch. The batch may be fetched for an interval of time, and the ETL platform may fetch new or changed data from different cloud/on-premise applications. It will store this data in the cloud or on-premise to build data history. As the ETL platform fetches new data, the system will not overwrite existing data, but rather will create new versions so that change history is preserved. For any reason, if businesses would like to rollback data, they could rollback to any previous batch.

Abstract: An extract-transform-load (ETL) platform fetches consistent datasets in a batch for a given period of time and provides the ability to rollback that batch. The batch may be fetched for an interval of time, and the ETL platform may fetch new or changed data from different cloud/on-premise applications. It will store this data in the cloud or on-premise to build data history. As the ETL platform fetches new data, the system will not overwrite existing data, but rather will create new versions so that change history is preserved. For any reason, if businesses would like to rollback data, they could rollback to any previous batch.

Abstract: A system fetches consistent datasets in batches for a given period of time and provides the ability to retrieve each batch. Batches of data may be fetched for an interval of time. The present system may fetch new or changed data from different cloud/on-premise applications. It will store this data in the cloud or on-premise to build data history. As the system fetches new data, existing batches of data will not be overwritten. New batches of data are created as new versions so that change history is preserved. Past batches of data for a past time period may be provided to one or more tenants.

Abstract: A metadata management system receives metadata changes and automatically updates a metadata architecture which maps the data. The metadata changes may be received through a simple user interface by a user or administrator. Once received, the system may automatically update schemas and data transformation code to process data according to the new data mapping preference. The system may handle metadata updates in a multi-tenant system having one or more applications per tenant, and may update data for a single tenant and 1 or more tenant applications in a multitenancy.