MyBigDataBlog

Today, I learned about the types of data visualisation. Data visualisation is the methods used to present data in a way that is easy to understand, usually a graphical representation such as a graph or a map of the data. Data visualisation will typically represent the data as statistics such as numbers or percentages.   Visualising data allows us to interpret and understand the data easier than trying to understand the data in its unstructured format, which is important when it comes to making informed decisions based on the insight the data can provide.  Some types of data visualisation that I have learned about are: Charts such as pie charts in which data is represented as a percentage of a circle with labels to show the percentage and index of the data.  Tables which store data in rows and fields of cells, with a field name at the top of each field to distinguish the type of data being stored in that field. For example a table could store personal details with the...

Today, I learned about data mining techniques. Data mining is a method used in BIG Data to find correlations and patterns within massive data sets. There are various data mining techniques which allow organisations to lower costs and increase their revenue.  Data mining allows you to sort through massive amounts of unstructured data to figure out which parts are relevant so you can use those parts to predict outcomes, allowing you to make informed decisions faster.  One data mining technique is to track patterns in the data set, such as data that is repeating at regular intervals or anomalies within the data. This can help organisations to recognise trends within the data which could provide information such as a spike in the sales of a product at a specific time of the year. The other data mining technique is classification which is more complicated than just tracking patterns as it combines a collection of variables into different categories which can be used to provide insi...

 Today, I learned about the types of problems that are suited to BIG Data analysis, including making it easier to measure what consumers actually want. There are problems within every industry that are suited to BIG Data analysis, such as the healthcare industry where BIG Data analysis is used to personalise healthcare plans for patients, or the shopping industry where predictive analysis is used to order inventory based on insights gained from customer and product data, and the security industry where BIG Data has a massive impact on cybersecurity protocols and monitoring due to the real-time data monitoring aspect of BIG Data.  I also learned that the longer data is collected the more accurate the data set becomes in terms of how predictive it is, so data collected for 5 years will be more accurate than data collected for only 3 years.

 Today, I learned about some strategies to limit the negative effects of BIG Data. One of these strategies could be to give the person that generates the data power over the decision for how the data can be used and who is allowed to use the data, however some people believe that this solution is not enough and that there should be stronger restrictions. The data protection act 2018, which is based on the EU's GDPR legislation, is another strategy to limit the negative effects of big data. The data protection act lists strict rules for data controllers about how the data is stored and used, such as processing personal data is only allowed if consent is given by the owner of the data.   

 Today, I learned about the implications BIG Data has on society, specifically the implications big data has on society when used in politics. BIG Data is being used by every political party to influence who people vote for, the result being that BIG Data has a massive impact on who is running governments.  By collecting massive amounts of data sets from social media posts, BIG Data allows political parties to send targeted messages to specific individuals based on keywords from social media posts to persuade their voting decisions.  Another implication of BIG Data has on society is that we are constantly being surveilled as the data from everything you do is collected and stored, yet only less than 1% is actually being analysed, which has resulted in many public cases of privacy breaches. There is also concern that all of the surveillance and data collection that is happening could result in a similar situation to china where they are under constant surveillance with eve...

Today, I learned about the implications BIG Data has on individuals, the biggest of which being the infringement of BIG Data on civil liberties.  One concern about the implications BIG Data has on civil liberties is the investigatory powers act which allows certain organisations to obtain a warrant to bug phones and computers, for which companies would be required to provide assistance as well as encryption keys to decrypt customer communications.  These organisations can collect massive datasets of communication data, such as a dataset of NHS records, and, by using BIG Data analysis, are able to analyse the data to search for keywords. However, these operations require authorisation from a panel of judges which provides a safeguard from misuse of the investigatory powers act.  Another implication of BIG Data for individuals is that since all of the data from social media posts are being collected and stored in massive data sets, then it is possible for everyone, includin...