According to Forbes, between 2016 and 2018, 90% of the data of the world was created! The value of that data to someone is incredible, so remember that when you use your 'free' service from a social media company.
Data analysis and visualisation is an area that excites me. Taking meaningless data, organising it to create meaning, and to provide 'insights' can be really eye opening.
Data is the raw numbers that are captured, information is what you notice about that data e.g. out of 100 bananas 10 are bruised, an insight is gained by analysing the data and information to understand why it's happened.
The image in this section shows where crime has occurred and although it is interesting to those who live in the area, the data could tell us a lot more. If this data is analysed to look at crimes over a period of time, in certain locations or some other factor, then we might get an 'insight'. This is why data is so exciting.
Data visualisation is a term that describes any effort to understand the significance of data by placing it in a visual context. Doing this allows patterns and trends that might go undetected in text-based data to be exposed and recognised easier.
Data visualisation is very powerful and even in this basic example which just plots where a crime was committed, so much more can be gleaned than from just looking at a list of text. You can interact with this 'viz' by selecting/deselecting thet type of crime, and zooming in or out to see crime over the region.
You can also view this on Tableau Public Server where additional 'vizzes' will be added.
Tip: Use shift and mouse left click to scroll around the map.
I've put together an example using UK Home Office data for crime in Suffolk, UK in March 2019. This is a huge data source hence why I've just taken a small subset of the data.
By seeing the 'viz' on Tableau Public Server, you will be able to view crime from high level regional crime data right down to street level. This data can be further refined by selecting only certain crimes, in this case it's drugs and shoplifting offences.
In this example, it's no surprise that the major population densities have clusters of crime. The exciting part is taking this data, expanding the data points, and drilling down to uncover something new.
As you can see, with the right tools and an inquisitive mind, data is a high value resource.