Data can really be broken into two separate types. The first type is structured data. This is the most common type of data in the business environment. The second type of big data is unstructured data. Unstructured data is generally generated via the web or social media.

Architecting and implementing large structured data solutions within the corporate environment is a well-known practice leveraging solutions by companies such as Teradata, Oracle, IBM and SAP. These solutions are at the core of your information strategy. They generally reflect the size and complexity of your organization and business processes. It is important that your structured data solution is very well implemented and documented. Your master data and metadata will become key assets when you start building relationships with your unstructured data.

The generation of unstructured data has exploded over the last decade. Corporations’ ability to capture, analyze and use this unstructured data has lagged behind its generation. Some organizations have started the process of capturing and analyzing unstructured data. Many use map reduce tools such as Hadoop during this process. One of the key missing elements is understanding the relationship between the unstructured data and the structured corporate data. Implementing an information strategy that by design builds relationships between your unstructured and structured data will drive tremendous value for your organization. The relationships between the unstructured and structured data can have a sense of permanence or can be ad hoc depending on your needs.