Types of Problem suited to Big Data Analysis

predictive analytics


Predictive analytics is when we use big data to look for patterns which can help us predict what will happen in the future based on the pattern found. For example companies and investors can use big data analytics to predict what prices will be in the future from looking at past information of what sales have been in past years. This can help them in business decision making as they can make an estimate of what will likely happen.


diagnostic analytics


Diagnostic analytics is similar to predictive analytics in that it predicts a value, however it does not necessarily predict future values. It can have any 2 variables which can be compared. Using the existing information on the graph, the location of an unmapped value on the graph can be predicted by estimating where it would most likely be. For example the number of sales of hand held fans in a shop could be based on the temperature of that day. Using the information from previous sales and temperatures we can estimate how many fans are likely to be sold based on the temperature of the day. If the temperature is 5 degrees you may expect 1 sale. If the temperature is 30 degrees you might expect 400 sales.


descriptive analytics


Descriptive analytics is when we take data and map it onto a graph. Then see if there is any relationship between two variables. If a relationship is found we say what we think the relationship is. For example if we look at the previous example we can say that the warmer the weather is on a particular day, the more fans will be sold in the shop.


prescriptive analytics


Prescriptive analytics is when we look at the relationship and make decisions based on the relationship and what we can predict. It can be used to create the best outcome of something because we can make predictions based on the relationship. Businesses can use prescriptive analytics in order to maximise profits. Healthcare professionals can use it to give people the most effective treatment. Looking back to the shop example above we can make the decision that the business should buy less hand held fans for their stock during the cold winter and make sure there is a lot of fans stocked in the summer months to maximise profits.