In the first Lecture Pod we were introduced to the idea of Data Visualisation and what it is. Data are values of qualitative or quantitive variables belonging to a set of items. Typically, Data is the result of measurements and can be visualised using graphs. By itself data carries no meaning, for data to become information it must be interpreted for it to take on a meaning.
The first important point made was that data is growing at an exponential rate and their is now more data than any previous records throughout history. Records shows that 23 exabytes (1 exabytes = 1 billion gigabytes) of information was recorded and replicated in 2002, now we do this in seven days. Even as individuals we are recording large amounts of data each day, whether its data collected from a fitful or Apple Watch, internet history and credit card purchases. Due to increasing levels of data being accumulated, we have developed strategies to deal with the growing amounts of data. From dynamic weather maps, heritage and epidemiology, tracking polluted water and crimes, new visualisation strategies along with old ones, help us to make sense of it all.
Data Visualisation is the visualisation of data that is viewed by many disciplines as a modern equivalent of visual communication. It involves the creation and study of the visual representation of data, meaning that information has been abstracted in a schematic form and includes its variables and attributes for the units of information.
The most important point to remember from this lecture is that Data Visualisation is now a mass medium and an essential part in the communication process. It is important for us as designers to engage with the overall aesthetic, forms and politics of data presentations. By using effective visualisation methods it helps users to analyse and think about data and makes complex data more accessible, understandable and usable.
DATA VISUALISATION 
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