The digital revolution and the rise of big data have created an enormous volume of data for the average business. In a 2017 study, Data Age 2025: The Evolution of Data to Life-Critical, IDC predicted that global data will grow to 163ZB (zettabytes, or one trillion gigabytes) by 2025.
The emergence of big data has spawned a wide range of data types that companies must manage and secure. These data types include:
- Structured data, which is largely numeric and comes from transactional systems and technology tools like enterprise resource planning (ERP) systems.
- Unstructured data, which consists of random files types — including images, audio/video recordings and Microsoft Office files — which are not subject to rules.
- Semi-structured data, which represents a hybrid of these types, where the file may contain numeric information, but that data is hard to extract (for example, a Microsoft Excel spreadsheet).
Each of these data types poses unique challenges in terms of creating a data governance strategy that stores the information, protects privacy and security, and complies with government regulations about data.