Customers can provide user-generated data, such as reviews for products or corrections for mapping errors. This data needs a greater degree of checking, both for meaning and to avoid deception.

Messaging is a popular way for software systems to communicate, and one of the advantages is that these messages can also be processed by analytic systems. Synchronous calls can be fed into monitoring systems. In such ways we can analyze application communications. Sometimes this data can be very well structured - but then is usually non-uniform, with different messages having varied structures. Some messages, such as email, carry very little structure at all.

It is increasingly affordable to equip physical devices with sensors, which monitor their location, condition, and physical environment. For many years we've taken advantage of bar-codes and RFID tags to track objects through supply chains. Increasingly physical devices can be more active sources of information, sensors with memory and simple communication devices can record continuously and download to networks when they have the opportunity.

Sensor data is usually fairly well-structured and uniform. It can present challenges to handle the volumes both in storage terms and lots of writes to a data store.

Every time a customer, employee, or partner interacts with an application, that interaction can be logged - and these application logs are often a valuable source of information. This is most common for web sites where analytics software commonly traces the paths that users follow through a sequence of web pages. The data in these logs can be used to improve the user experience of the application, and also suggest information for new features and products.

Application data like this requires a good bit of work to tease out intent and make it consumable by analytic systems. Furthermore there's lots of it, so this is one of those cases where the bigness of the data is part of the challenge.

Mobile devices can be used both as explicit application interfaces, and also as sensors in a similar way to remote devices. For example Google uses real-time phone data to help estimate traffic delays to improve travel-time estimation.

Such usage has similar challenges to that of any physical device sensor, but with additional privacy issues. While it's useful for an airline to track its passengers and employees continuously, many people will reasonably object to the police-state implications of such scrutiny.

Much important data is stored in organizations in the form of documents: word-processing, pdfs, spreadsheets, and presentation decks. This is very ill-structured data, but often contains critical information - indeed much critical computation is done inside spreadsheets.