Cognitive automation platform

A method for analyzing data in a cognitive data platform, comprising:

• crawling data in a transaction system using at least one data crawler run with multiple connectors in a cluster,
• reducing network bandwidth consumed by compressing the at least one data crawler;
• processing the crawled data using at least one data processing engine configured to transform the crawled data;
• receiving the transformed crawled data into a cognitive data layer (CDL), wherein the CDL is configured to index the transformed crawled data, and wherein the transformed crawled data in the CDL is searchable using a natural language voice interface;
• generating a knowledge graph from the transformed crawled data, wherein the knowledge graph is used to enhance natural language search results;
• analyzing the transformed crawled data in the CDL;
• based on the analysis of the transformed crawled data in the CDL, detecting at least one specified condition in the CDL;
• reporting the at least one specified condition;
• analyzing an audit trail log, wherein the audit trail log comprises a list of artificial intelligence algorithms used for selecting a recommendation;
• and
• based on the analysis of the audit trail log, generating at least one recommendation to address the at least one specified condition;
• providing a drag and drop interface and a library of pre-defined visual constructs for building one or more skills;
• and
• building, using a cognitive development kit, a specific skill application on top of a cognitive operating system.

A non-transitory computer-readable media storing computer executable instructions that when executed cause a computing system to perform a method for analyzing data in a cognitive data platform comprising:

• crawling data in a transaction system using at least one data crawler run with multiple connectors in a cluster;
• reducing network bandwidth consumed by compressing the at least one data crawler;
• processing the crawled data using at least one data processing engine configured to transform the crawled data;
• receiving the transformed crawled data into a cognitive data layer (CDL), wherein the CDL is configured to index the transformed crawled data, and wherein the transformed crawled data in the CDM is searchable using a natural language voice interface;
• generating a knowledge graph from the transformed crawled data, wherein the knowledge graph is used to enhance natural language search results;
• analyzing the transformed crawled data in the CDL;
• based on the analysis of the transformed crawled data in the CDL, detecting at least one specified condition in the CDL, wherein the at least one specified condition is
• a supply shortage of at least one product;
• reporting the at least one specified condition;
• analyzing an audit trail log, wherein the audit trail log comprises a list of artificial intelligence algorithms used for selecting a recommendation;
• comparing previous decisions to historical demand of the product;
• identifying at least one accurate previous decision, wherein the at least one accurate previous decision accurately forecasted demand of the product;
• based on the analysis of the audit trail and the at least one accurate previous decision, generating at least one recommendation to address the at least one specified condition;
• providing a drag and drop interface and a library of pre-defined visual constructs for building one or more skills;
• and
• building, using a cognitive development kit, a specific skill application on top of a cognitive operating system.