So, let’s talk about the most basic data concepts – Quantitative (numerical) and Qualitative (descriptive) data, in a workplace scenario.
Let’s say that you counted the number of customers that entered your workplace daily and how many purchased something – this is a collection of Quantitative data. But if you were to instead count how many customers were males and female, then go on to record what types of hair colour they all had – this takes the form of Qualitative data. Both types of data have varied attributes and are extremely valuable for your business operations.
Big Data on the other hand, is a relatively new term that refers to the vast collections of datasets that businesses can harness, which can be cultivated both inside and outside of biz operations. The challenges of Big Data in a business environment can include the capturing, curating, storing, searching, sharing, analysing, and visualising of the various data sets – as it all is so far reaching. But Big Data within businesses can be broadly classed into the following categories, which helps to clarify the concept:
- Internal data: consists of information inside your business, which is collected through it’s own systems and/or processes – e.g. hourly transactions, employee information, inventory records etc.
- Structured external data: generally available for owners through third-parties, with the ability to overlay the results with your own internal data. E.g. social-media profiles, ABS census results, Geo-location data etc.
- Unstructured external data: covers directly unrelated data sources. E.g. News outlets, Financial Markets, Climate reports etc.