The term big data has been around since the early 1990’s. With the advancement of technology over the past 10 years, it has proven its importance and relevance. With 2.5 exabytes of data being generated every day, it is expected to rise to 463 exabytes daily by 2025. With this, many organisations now find themselves storing large amounts of data. This can relate to anything from people, services, financial and biological information.

While companies have been storing this data, data scientists have been developing algorithms. Computer programs which can process large amounts of data quickly. Analysing and identifying key patterns and relationships from the data.

However, machine learning uses different methods of learning. Allowing it to process a higher quantity of data. This allows machine learning the capacity to process data that has limited structure. Giving organisations the software to process complex data that other learning methods would not be able to process.


Difference between Machine Learning and Algorithms

An algorithm is a type of automated instruction. These can be simple or complex but equate to a series of actions, “If this happens, then this should happen”.

An example

A thermostat would run an algorithm, checking the temperate of the room. If you room was colder that the set instruction, the algorithm would turn on the heating. This would keep looping until it reached the correct temperature. Always running the same loop until turned off.

Big data and machine learning

Machine learning is a set of algorithms. Where it can process data and complete its task without being told how to do it. This is an advanced algorithm that learns, based off passed actions.

An example

Listening to a set genre of music on Spotify. Machine learning could make recommendations or predictions on music you might like.

It uses statistics to find patterns in large amounts of data. It can then make an educated guess what you might be interested in. This could be based on other users listening habits based against your own. If different users listen to 4 different bands, which you have listened to 3 of them. The Machine learning algorithm would recommend the 4th band to you.

Machine learning is behind many of the services we use today. From social media platforms feeds, like Facebook and Instagram. Platforms such as Youtube and Netflix for their user recommendations.


So why is big data and machine learning important?

Companies can now collect vast amounts of data daily. Machine learning allows companies the solution of processing this data. Allowing them to solve problems fast, without having to know how to solve the problems or why a certain solution works. It can test millions of possible outcomes fast, to implement the best outcome for the better of the business. Saving business money, increasing ROI and improving user experience.

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