What is variety?

The term variety describes the type and the nature of the data. For us, the following three types of data are relevant:

• Structured data: Structured data is defined in a data model or in any form of schema (schema-on-write model), where the data is described. As a solution for the structured data area, the Azure platform offers the so-called Azure SQL as a service, services.

• Semi-structured data: Semi-structured data does not have the formal structure of a data model, but contains tags or other types of markers to separate elements, and enforce hierarchies of records and fields within the data. Therefore, it is also known as the self-describing structure. Typical examples of a self-describing structure are XML or JSON. As a solution for the semi-structured data area, the Azure platform offers the so-called Azure NoSQL as a service,  services, but the Azure SQL as a service offers are also able to handle this type of data.

• Unstructured data: Unstructured data refers to information that either does not have a pre-defined data model or is not organized in a pre-defined manner. Unstructured data is typically text heavy but may contain data such as dates, numbers, and facts as well. For example, unstructured data may include documents, metadata, health records, audio, video, analog data, images, files, and unstructured text (for example the body of an email message), or web pages. As a solution for the unstructured data area, the Azure platform uses the Azure Storage services, or in individual cases, Azure NoSQL as a service.

To meet our original objective, this means you must answer the following questions:

• What type of data are you intending to store? For example, common data types are transactional data, JSON objects, telemetry data, or flat files.
• Does your scenario have one or more data types that you need to store? An IoT scenario includes, for example, telemetry data, diagnostics and debugging data, device management data, and much more.

Where do we go from here? Let's look at another V of the big Vs. This time V is for volume.