The term ‘big data’ is more and more often used in reports and analyses. Unfortunately, writing about ‘big data’ authors usually have in mind data which are ‘big’ in quantity. But this criterium is not sufficient. 

The easiest way to check whether we’re facing with the source of‘big data’ is to check whether it has the following 5V:

  • volume – data occupy huge space in the memory of electronic devices
  • velocity – data are dynamic and processed in real time
  • variety – data come from various sources, allowing that part of the data is unstructured
  • value – data are a valuable source of information, even if they’re unstructured
  • veracity – data sources are reliable which is a big challenge in view of volume, velocity and variety of sources.

Where can we find this kind of data? Almost every device we’re using can collect information which someone can analyse. Beginning with:

  • telephone (our location, the amount of downloaded data analysed by the operator),
  • computer (browsed websites, search engine history collected by companies),
  • credit card (the amount and places of shopping available for our banks),
  • shop monitoring (the way customers move around shops – used by marketing specialists)

Also municipalities have access to ‘big data’:

  • city monitoring (analysis of vehicles speed, traffic direction, traffic density, pedestrian count),
  • municipality’s bank account (cash flow),
  • administrative data (decisions, permits, certificates),
  • location of public transport vehicles,
  • energy consumption by street lamps,
  • number of people using local hot-spots,
  • information from the paid parking zones (number of occupied / unoccupied parking spaces)
  • number and type of comments on the social media sites of the city.

Properly collected (structured) and analysed, data are a valuable source of information not only for marketing professionals (based on our behavior in stores they can plan deployment of new products, based on visited websites we can be offered products that probably interest us) but they can also provide an excellent basis for managing the city.

Only on the basis of data concerning movement of the city residents you can determine whether the planned traffic routes meet their expectations, whether the paid parking zone is optimal and plays its role in the rotation of vehicles, which routes are most congested and which routes are commonly used as detours.

„Big data” =/= „open data”

Big data is not the same as open data. Big data can be open (eg. location of public transport vehicles, information about the level of air pollution), but at the same time open data do not have to be ‘big’ (eg. timetable of public transport, list of schools, ownership entities).

The text is based on  Blog.Gartner.com and the report of the Ministry of Administration and Digitization entitled “Information Society in Figures 2015”.