Our worldview of data
We talked about our Data APIs at the startup saturday held recently in Bangalore, India. You can find the slides here. We presented our worldview of data and the unique challenges in dealing with different “kinds” of data.
The image above signifies the two fundamental axes that helps us in classifying data. The horizontal axis signifies temporality while the vertical axis represents the presence or absence of structure underlying the data. Any “kind” of data that we might think of falls into any one of these quadrants.
The reason why we try and classify data into one of these quadrants is because the underlying challenges of dealing with data from any of these quadrants are inherently different. For example, data that is unstructured requires sophisticated and text mining techniques to derive value from the data, while mining data based on freshness becomes important when dealing with data that is temporal in nature.
Most of the datasets that we deal with at DataWeave are primarily unstructured and temporal.
