Skip to main content

Post 11: (Question 7) Limitations of traditional data analysis

As with all things there will always come limitations to data analysis due to the fact that it is created by humans and is subsequently subject to human error. Some of the limitations that you may come across would be that the data may be incomplete, whether it be missing values, or lack of a section of necessary data. This could severely limit the data's usability.
Survey data can also be scrutinised due to the human component. People do not always provide accurate information through surveys and many are likely to not answer truthfully. For example if a person were asked how much alcohol they consume within a week they are likely to say less than their actual intake. 

Comments

Post a Comment

Popular posts from this blog

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.
Post a Comment
Read more

FutureLearn Week1: Post 2 of 3

The best example of environmental big data is that of weather forecasting, as discussed in the video on futurelearn. The use of drones to monitor and measure atmospheric pollutants is another form of environmental big data. This can all be used to reduce carbon footprint by making use of the data to reduce or introduce more efficient transport in areas with high levels of pollution.
Post a Comment
Read more

Post #3: Growth of Big Data

There was an incredible amount of internet growth in the 1990s, and personal computers became steadily more powerful and more flexible. Internet growth was based both on Tim Berners-Lee’s efforts, CERN’s free access, and access to individual personal computers. In 2005, Big Data, which had been used without a name, was labelled by Roger Mougalas. He was referring to a large set of data that, at the time, was almost impossible to manage and process using the traditional business intelligence tools available. Additionally, Hadoop, which could handle Big Data, was created in 2005. Hadoop was based on an open-sourced software framework called Nutch, and was merged with Google’s MapReduce. Hadoop is an Open Source software framework, and can process structured and unstructured data, from almost all digital sources. Because of this flexibility, Hadoop (and its sibling frameworks) can process Big Data. Big Data is revolutionising entire industries and changing hum...
Post a Comment
Read more