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IBM Datacap Accelerator Integrations - Part 2

By Sunanda Rao posted Thu March 18, 2021 01:25 AM


Another integration with Datacap Accelerator is Business Automation Insights(BAI). Business Automation Insights is a combination of Kafka, Elastic Search(ES) and Kibana. It’s a visualization tool using which one can create business dashboards. Each of these dashboards consists of various visualizations.

BAI provides insights from the data stored in Elastic Search, document-oriented DB that allows us to store documents/events in a JSON format. The visualizations or the dashboards created helps us understand the data better.

Designed and developed a framework by creating a custom action that posts events from the Datacap to the Elastic Search instance of BAI which are then visualized using Kibana.

Datacap workflow.

To include custom action as part of the workflow – we’ll have to create a ruleset.

Ruleset - Each ruleset consists of set of rules and each of these rules are associated at one of the levels in the document hierarchy. Each rule can have one or more functions , as shown below - in the Rulesets definition. Each function can call one or more actions from list of action library (global / custom).

Rulesets definition

This ruleset is then added to the task profile, as shown below - in Task profiles. Each of these task profiles are linked to tasks. Tasks are part of the workflow.

Task profiles

When these actions are executed, it generates the logs or events. The events gives us an information about the batch, status of REST service invoked, if any and are stored in the events folder created under the current batch folder. The framework developed by creating the custom action is capable of connecting to the ES instance of BAI whose details are provided in the configuration file and posts these events to it.

Datacap extensions to support the framework.

The action library developed is made available as DLL. These are placed in the RULES folder in the Datacap application. The action library is then added to the rulesets and are associated at the batch level.

The custom action takes in two parameters - one, configuration file path and the other, absolute file path of the log file or the log folder.

The configuration file used has the properties, as shown below and is placed in dco_applicationName\annotators folder.

Configuration file

It parses the configuration file, builds the ES endpoint and then creates the index (by using the index name specified in the config file). These index are created by using the index API.

Indexing in elastic search.

Index is basically a collection of documents or events. Sub-set of these documents indexed are shards. These indexes are creating using an index API. Each of these indexes have a type or can have multiple types. By default, type is _doc. Type is a logical category of index that defines set of documents/events that have common fields. One could specify the document mapping while creating the index. These mappings could be either explicit or dynamic.
Request format - https://hostname:<port_no>/<index_name>/<type>

The custom action then reads the log file content and posts it to the ES instance of BAI.

Creating business dashboards using Kibana instance of BAI.

Kibana is a web-based visualization tool that lets us present the data in the visual format. It allows us to create various graphs, charts and customize the dashboards. To discover the data in Kibana, one must create the index pattern.

Using the various graphs and charts that it provides, one could create the dashboards/visualizations to provide better insights to the business users. By analyzing the visualized data, one can make better business decisions.


Similarly, we could leverage the capabilities of IBM Datacap Accelerator by integrating it with other applications to meet the business requirements.

Check this link to know more on IBM Datacap -