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FutureLearn Week 2: Post 1 of 4

Open data has been increasing for some time now with data being made open on various sites globally. There are many advantages to having open data, these advantages include being able to share public data sets so that they can be compared. These open data sources can also be used for environmental purposes or even health issues. Disadvantages of open data would include the fact that the site providing the data would be inherently biased and formed in the opinion of the creator.

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FutureLearn Week 2: Post 3 of 4

Two of the biggest challenges of big data is Analysing and Visualising the data. Firstly with analysing the data, the size of big data files can sometimes be substantial, there are many things that must be considered before downloading the data, for example the file size, how long the data file will take to download, will all of it be necessary or will part of the file suffice and is there enough storage space within the system itself. Visualisation is way to represent the data in a way that is easier to understand such as word clouds and things of the like. This will aid users in seeing the prominent and key terms from the analysis of the data sets. The first step after downloading the data would be to quality check it to ensure that each field had the appropriate data types in each field and to ensure that the user understood the meaning of each field. Keeping a copy of the original data would be essential as well as each documented version change for each stage of visualisation....

Post #6: Traditional Statistics: Descriptive and Inferential in Big Data

Two types of Traditional statistics in Big data include Descriptive and Inferential. Descriptive means averages and working on sets of numbers. Descriptive statistics is a type of statistic in which a data set is summarised and the characteristics are described. This descriptive data is usually displayed through the use of tables, charts etc. but is most commonly reported as a measure of a central tendency. A central tendency is a typical value for a distribution, it is also been known to be called a location or centre of the distribution. The arithmetic mean is the most common measure of a central tendency, this is the median and the mode. The mean is the average of all the values, the median is the exact middle of the data set while the mode is the most frequent value in the data set.  The goal of traditional statistics is analysing and summarising data, providing tight assumptions about the problem and data distributions as well as using conservative techniques and approaches....