ICDL Types of Data Analytics【ICDLって何よ？番外編３】
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Types of Data Analytics
In this video, I’ll be sharing more on one of the most topical technology trends of recent times, Data Analytics.
Now, let’s find out what is Data Analytics?
Data Analytics refers to the techniques and processes used to collect, organise and examine data sets to create meaningful and useful information.
Organisations are using data analytics to find meaningful and useful insights that they can use to meet their organisational goals such as predicting future sales better or anticipating customer issues before they happen.
In recent times, there has been a rapid rise in the use of data analytics across all types of organisations and sectors due to among other things the technological advances in data analytics.
And also, useful data can be collected from an increasing range of sources,
for example,
- Mobile Devices
- Online Platforms
- Payment Systems
- Cameras
- and others
There are different categories and types of data analytics which, although interrelated have different purposes and provide different insights.
Four different types of data analytics broadly classified by their different purposes:
First, Descriptive Analytics, which is the simplest type, Followed by Diagnostic Analytics, Then Predictive Analytics and, Finally Prescriptive Analytics Descriptive Analytics.
Descriptive Analytics is used to find out what happened in the past. Although considered the most basic form of data analytics it still provides valuable insights into the past by summarising raw or historical data from multiple sources.
Descriptive analytics uses descriptive statistics such as arithmetic operations, mean, median, and percentage. Descriptive analytics can be used to create management reports providing insights into past performance. It allows you to see whether something happened as expected for example, if targets were met.
Diagnostic Analytics.
Diagnostic analytics is used to find out why something happened in the past. It takes a deeper look at the data to understand the root causes of events and to determine the factors that contributed to the outcome.
Diagnostic analytics uses techniques such as drill-down, data discovery, and correlations. And it uses probabilities, likelihoods, and the distribution of outcomes for the analysis.
Predictive Analytics.
Predictive analytics is used to find out what is likely to happen in the future. It uses the findings of descriptive and diagnostic analytics to forecast the probability of a future outcome. The forecast is an estimate, the accuracy of which depends on the quality and consistency of the data.
Predictive analytics might be used by organisations to predict the impact of a proposed change to predict customer purchasing trends or to predict a customer’s ability to repay a loan on time.
Prescriptive Analytics
Prescriptive analytics is used to identify what is the best action to take now.
It is useful for avoiding problems that may arise in the future or for making the best use of trends. It is a relatively new and complex type of analytics.
Prescriptive analytics uses the findings of predictive analytics combined with historical and transactional data, real-time data feeds from both internal and external sources, mathematical models and various business rules.
Techniques include optimisation, simulation, and decision-analysis methods. The diagram illustrates the value-added contribution and complexity of the various types of data analytics in relation to each other. So which type of Data Analytics would be most suitable for you and your organisation?
We hope this short video is beneficial and useful for you.
Remember to always Be Informed, Be Alert, Be A Tech-Ready Citizen!
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