What Are The Difference Between Machine Learning And Data Analytics

Difference Between Machine Learning and Data Analytics

Data Analytics and Machine Learning have progressed way beyond the boundary of buzzword technology and are now general terms in the technology industry. Both machine learning and big data analytics come under the umbrella of data science. Although they have an association, there are still some unique identities that separate them in terms of definition and application. This article will help you to understand which domain of expertise to choose Big Data Analytics or Machine Learning and how it will help you.

  What is Data Analytics?

Data analytics is a term for a set of a large amount of data that is too complex to be processed using traditional methods. It refers to the activity of studying these large sets of data using specialized software and analytical tools developed specifically for that purpose. To learn data analytics, you can join the Data Analytics Training Institute in Delhi.

What is Machine Learning?

Machine learning is a science which deals with the creation of algorithms and programs which predict results or takes actions in order to optimize a system based upon the data that is constantly generated. This data can also be big data and through machine learning, programs or algorithms can be created which learn from the information present in the data to predict future possible patterns. To learn machine learning, you can join Machine learning training in Delhi.                                                          

Difference between Data Analytics and Machine Learning

You will find both similarities and differences when you compare big data analytics and machine learning. However, the major differences lie in their application.

  • Big data analytics as the name suggest is the analysis of patterns or extraction of information from big data. So, in big data analytics, analysis is done on big data. Machine learning, in simple terms, is teaching a machine about how to respond to unknown inputs but still produce desirable outputs.
  • Most data analysis activities which do not involve expert task can be done through big data analytics without the involvement of machine learning. However, if the computational power required is beyond human expertise, then machine learning will be required.
  • Normal big data analytics is all about cleaning and transforming data to extract information, which then can be fed to a machine learning system in order to enable further analysis or predict outcomes without the requirement of human involvement.

Which one should you go for?

Big data analytics and machine learning can go hand-in-hand and it would benefit a lot to learn both. Both fields offer good job opportunities as the demand is high for professionals across industries while there is a lack of skilled professionals; machine learning professionals being in more demand when compared with big data analysts. When it comes to salary, both profiles enjoy similar packages and if you have skills in both of them, you are hot property in the field of analytics.

However, if you do not have the time to learn both, you can go for whichever you are interested in.

                                      

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