Analysis vs Analytics. What is the difference?

Lot of confusion when you start asking people the differences between analysis vs analytics.

Analysis vs Analytics

Looking at the words, there is a clear difference with the letter “t” not being present into Analysis. Continue reading, and you will understand why I refer to this. 

 

Analysis:

The so-called observation. Let’s investigate a simple example

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You are in deep forest or some place with less traffic in a wonderful morning. You are enjoying nature and identifying its different sounds. A sound of bird chirping, an animal moving further down, an insect making a buzzy sound.

You then go to your friends to share your experience. While you explain to them how nice it was to listen to that parrot’s sounds, you friend interrupts you. He claims that there are no parrots in this forest. After this comment on your false observation, you are annoyed. 

As irrespective of wonderful experience your output data seems to be incorrect and now you want to either correct yourself or prove your friend wrong.

To make this happen, you go off researching. You look into forest conditions, birds available in your climate, parrots behaviour. As you have collected good data, you are analyse the forest’s real picture. What you’re enjoying now, we will call clear data.

 

This is turning into analytics. How? 

Analytics: As mentioned,  the”T” makes a difference. “T” stands for Tool.

Almost everyone can analyse lot of things. However, to prove your analysis is accurate,  you will need to use a tool. This tool will not only track the analysis you develop, but it will also provide the real world facts/picture.

Combining the two, analysis + analytics results, will prove to be the most successful and effective method.  When both analysis and analytics are equal or close to being equal, then your experiment is a workable case.

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i.e. A political party expects 40 seats and they have received only 5 which means somewhere in a process of analysing things the experiment failed. If, however, that same part gets >= 40 then that is a successful experiment

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Closing, analytics is a proof of data collected from all your analysis that you make on a day-2-day basis. i.e. You expect 2,000 visitors per day on your website. Using your analytics platform can help you forecast and view how close you are and how realistic your set target is.

Please do remember – A tool should and will be beneficial if it provides your data in the form of numbers.

 

Read also: TensorFlow.js: Machine Learning in Javascript

 

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Madhu Vadlamani

A Tech savvy - mentor trainer and traveller with over 10yrs of experience in data science and analytics.