Separating Data Analytics from Data Science and Machine Learning

When you see terms like big data analytics, machine learning and data science on the internet – do you know which one is which? Or do you even know any difference between them?

Many regular people don’t understand the difference or how they play into everyday life, or how they benefit businesses.

Machine Learning

Machine learning is a term we hear more and more over the last few years, and it is being used in many different types of industries to get better marketing results, sales and even in their HR departments.

Machine learning is the process of using algorithms to extract data to learn from it for more informative future business actions. Machine learning is something that you don’t realise you are interacting with every day. Your own Facebook account uses machine learning to understand more about you, gathering behavioural information that you display on the site and presenting more relevant ads and interests for you. It is the same way that Amazon works with their product recommendations, looking at what you purchase and presenting similar products and what people who also bought them have bought alongside it.

Data Science

Data science is quite a broad term, especially as definitions have changed several times over the last decade. What it comes down to is a combination of hacking skills, math, statistics and expertise.

In practice, data science tackles big data and understands the information that is taken from it. It includes data cleansing, preparation and analysis and is collected from multiple sources, including machine learning outputs. With all of these data sets collected, analysis can help make predictions for the future which are especially important to businesses to stay ahead of the curve.

Data Analytics

When we talk of big data analytics, we are looking at the process of understanding the gathered data of a business and using that to recommend directions based on the results.

This includes statistics, PIG/HIVE, coding and a bunch of other areas that need a data analyst to understand and gather the collated results – and put the results to good use. Data analytics is the big one for businesses, as many of them now require it no matter what industry they occupy. Today, businesses have access to more data than at any point in history, and the majority of these businesses have no idea of how to put it all to good use.

Data analytics is the process of interpreting all of that data and using aspects of the collated results to help a business grow.

Whilst all of these processes are different, they do overlap each other in some areas as you may expect. If you are a business looking to put these processes to use, it is critical to understand how they differ.

Check out the upcoming events from Whitehall Media for more information on any data analytics conference being held in your area.