Data dissemination can be defined as a mechanism that enables the communication of knowledge or information to an intended audience, using well-defined channels of communication (HTTP, FTP) and media format (json, xml). Disseminating data efficiently is an important business requirement because:

• Business want to elicit immediate action on the newly-gained knowledge
• We want to share new information or insights with our customers
• Automated response systems

Use cases such as business analytics, machine learning for generating new data models, and interactive data analytics are some of the more advanced scenarios where having the right data dissemination architecture offers benefits and speed.

Thus, when defining a dissemination architecture, the following should always be considered in the requirements-gathering phase:

• The communication protocol to be used to disseminate the information should be clearly defined.
• In order to define the communication protocol, you should know the target audience of the information. For example, if the target audience is a machine, the communication protocol could be an HTTP/REST-based API. If target audience is a business analyst, you may want to provide a SQL-like interface to interact with your data.
• Define the actual response schema for each type of query that the end user can have.
• Communication channel is also a very important piece of the puzzle. This ties in directly with your target audience.

Let's briefly discuss each of these aspects.