What is Analysis & What is Analytics
Madhu Vadlamani
?? Data Analytics & AI Specialist | Transforming Data into Strategic Insights | Speaker and Mentor
"Analysis = Analytics?? or Analytics = Analysis?? Data Analysis or Data Analytics?"
A lot of confusion when you start asking people what is analysis and analytics. Are both the same??? Then why do we use 2 different terms? Okay… Let me try to explain in the most simple way
Please find the image above. I have just framed 2 words up down and tried to separate them. Now if you observe there is “T” which actually made the 1st difference after 5 letters. Which actually has an answer.
Analysis: Analysis is noticing things(observation).. collecting things and come to a point of conclusion.
Example: Imagine…You are in the deep forest or someplace with less traffic on a wonderful morning. You started enjoying nature and started listening to different sounds. A sound of bird/animal.. and you are able to identify the sounds. Now you have shared this awesome experience with friends and in a conversation, you said that you are happier by listening to Parrot sounds. Now your friend stopped you there and says that the Parrots are not available in this forest and for no reason, you are hurt. Now irrespective of the wonderful experience your output data seems to be incorrect and now you want to either correct yourself or prove your friend wrong. Now to make this happen — You started researching forest conditions/ birds available/parrot behavior before you to the forest. Now that you have all the good data — You started to analyze the real picture of a forest. Now you also started enjoying a lot of clear data
NOW, THIS IS ANALYTICS… How is this ANALYTICS
ANALYTICS: As is said the “T” makes a difference — T is nothing but a TOOL. The T for proof and the T which can help to predict. Trust me everyone in the world can analyze a lot of things but to prove that your analysis is correct or closely correct you have to take the help of tool or some software which not only tracks the analysis you made but also give them real-world fact/picture.
Example: You performance report/scorecard is a Analytics tool which has proof that you are THE TOPPER. Firms numbers are the proof for companies performance
A successful method is a combination of Analysis + Analytics results
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If both analysis and analytics are at least closely equal or equal then that experiment is always said to be a workable case
"In our day - day activity - Noticing things/collect things/think about things is by default process and the challenge comes in when the amount of data increases. We save our contacts in mobile and in brain tool. Our brain itself is a tool which has capacity to store 2.5 petabytes of memory which is bigger than a capacity of avg.. Hadoop system"
Example: A political party predicts 35 40 seats and if they have received only 5 which means somewhere in a process of analyzing things the experiment failed. The failure has lot of reasons as well as success too have many metrics behind it. On the other side: If that same part gets >= 40 then that is the most successful experiment. Both examples are visible in the world
Finally: Analytics is simply proof that has data for all your analysis made on Day — day basis. There are many examples again. Best ever example is — You expect 2000 Visitors/day to your website but you use an Analytics platform like google analytics which shows your view is correct as the no of visitor count is tracked and that also helps forecasting things for future
Please do remember — Tool only gives data in the form of numbers. KPI’s/Metrics has to be designed by us. Finally - we who has to pen recommendations after taking the help from tools available. Tools are always a support mechanisms which will make our job easy.
Thanks for reading
Madhu Vadlamani
Lead Researcher - Cognitive at Innovation Labs
2 年Interesting