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Integration Workflow

Integrate with Visualization Tools and Technologies. 

There are two ways visualize the data in Big Data ecosystem. Big Data product has out of box visualization features in one way which can be used for analytics. There are various third party tools and technologies which are integrated with Big Data product through ODBC or JDBC connector or API with security key and token. There are benefits of using third party visualization tools and technologies. The benefits include majorly enhanced features and functionalities with visualization tools and centralized location for all types of visualization and analytics.

Integrate with Streaming Tools and Technologies.

There are various Streaming Technologies starting with Apache Kafka. Some of them are open source such Apache Kafka and others. Some of them are proprietary such as AWS Kinesis and others. Big Data product connects to either client version  or server version of Streaming technologies. There is a separate connection mechanism for either condition.

Integrate with Data Tools or Studios.

Data architecture is the main activity. The central point of data architecture is the getting data model. Data model is required at core in Big Data or Data Warehouse or Data Centric tasks. Such Data Centric tasks become seamless if Data Architecture tool is integrated with Big Data Product. There are third party Data Tools or Studios such as DBT tool. There are proprietary Data Tools or Studios from AWS, GCP, Azure, and Others.

Integrate with Other Big Data Tools and Technologies.

One Big Data product interacts with other Big Data tools and technologies through a defined connector. Such a connector consists of jar file, JDBC URL, and API key & token. JDBC URL is some time replaced by API endpoint.

Integrate with Third-party tools with ODBC/JDBC/SDK/API.

Big Data product connects with any of third party tools or technologies through ODBC/JDBC/SDK/API. Jar file, JDBC URL, and key & secret or token are required for ODBC/JDBC/SDK. There could be API endpoint used interchangeably for JDBC URL. Installation comes first for SDK in user environment before configuration. API endpoint, key, and token or secret are required for API integration.