Big Data, Analytics, and Data Science Life Cycle - Getting Started with Greenplum for Big Data Analytics - page 9

• Organized in semantic entities
• Similar entities are grouped together
• Entities in the same group may not have the same attributes
• Order of attributes isn't important
• There might be optional attributes
• Same attributes might have varying sizes
• Same attributes might be of varying type
• Unstructured : Unstructured data refers to the data that has no standard
structure and it could mean structure in its isolation. For example, videos,
images, documents emails, and so on. File-based storage systems support
storing this kind of data. Some key characteristics of unstructured data is lis-
ted as follows:
• Data can be of any type
• Does not have any constraints or follow any rules
• It is very unpredictable
• Has no specific format or sequence
Data is often a mix of structured, semi-structured, and unstructured data. Unstruc-
tured data usually works behind the scenes and eventually converts to structured
data.
Here are a few points for us to ponder:
• Data can be manifested in a structured way (for example, storing in a re-
lational format would mean structure), and there are structured ways of ex-
pressing unstructured data, for example, text.
• Applications that process data need to understand the structure of data.
• The data that an application produces is usually in a structure that it alone
can most efficiently use, and here comes a need for transformation. These
transformations are usually complex and the risk of losing data as a part of
this process is high.
In the next section that introduces data analytics, we will apply the multi-structured
data requirements and take a deep dive on how data of various formats can be pro-
cessed.