Shared connections

Shared connections are connections to the Data Lake that may be reused across spaces within an account. Users within your account can see all shared connections in all of their spaces and use them to import objects into their space without having to share the connection's credential information with a large subset of users. This is defined in Admin > Shared Connections. See the Birst Online Help for more information on Shared Connections.

Infor Data Lake is an Amazon S3 storage which stores Infor Message System (IMS) messages. An IMS is a business object stored using the JSON Streaming protocol (LDJSON). In the case of M3 Analytics, these messages are transactional events from M3 and are usually based on the underlying table schema. One JSON file may contain one or several transactional records of an M3 table. The message arrives in the Data Lake through Intelligent Open Network (ION). In this case, ION provides business process integration (iPaaS) between M3 and the Data Lake. A middleware layer implemented by M3 is responsible for publishing the messages to ION and providing a unique transaction variation number for each object. The variation number is an integer that indicates the sequence of updates. It is defined as the mechanism used to ensure that earlier updates do not incorrectly overwrite later ones.

The Infor Data Lake connection is intended for custom spaces and queries and provision with Birst.

The M3A Infor Data Lake connection is designated for M3 Analytics and provisioned with the M3 Analytics solution. This also comes with predefined queries for each M3 source required by the solution. The queries retrieve all columns of an M3 table, filtered by the lastModified date field that is the date and time in UTC when the JSON file was saved in the Data Lake. The range of dates to retrieve is determined by the incremental loading strategy, which is described in Data Lake incremental load.

Extraction groups are also defined in the M3A Infor Data Lake connection. These allow you to group tables or queries, so specific objects may be extracted separately from others. M3 Analytics has two extraction groups: M3A Fact Sources and M3A Dim and Lookup Sources. Fact sources contain all transaction tables that are used by all measure tables. Dim and Lookup Sources contain the main tables which populate dimensions and other supporting tables, such as currency conversion rate tables. The purpose of these groups is to extract all fact-related tables first before the dimensions to lessen the possibility of late-arriving dimensions.