Originally published on Quora. Link Here
“Machine Learning” is a subset of “Data Analysis” — it’s just one of the activities that you could apply to solve a data analysis problem, you just need to find a problem that can use machine learning wizardry! What kind of activities?, you say — well, to answer that we will need to step back and categorize what problems could be solved by Data Analysis. There are broadly three kinds of problems:
- “What” Problems. Few example: What are my sales number for last quarter? Can we compare it to same quarter last year? Now, can we break it down by Regions and Product Categories? — you see all these questions could be answered by a querying your data stores or by your Business Intelligence platform. Yo do NOT need machine learning for this. Moving on…
- “Why” Problems: Few example: Why did the customer cancel their contract? Why is the profit in region A declining Quarter over Quarter? You see this is little bit more challenging than “what” questions — you will need to structure the problem and pull data from multiple sources. Why did customer cancel? You may want to look at internal (e.g. customer complaints) and external (e.g. bankruptcy) data. Usually you won’t need to apply Machine Learning here — you might benefit in some cases where you “cluster” all churned customers and see if you can find some patterns but again Machine learning is not you primary tool here. Moving on…
- “What’s next” problems: This what you have been waiting for — this is where Machine learning could be applied. Example: Which customer accounts will cancel their account this fiscal year? — This is where you train a machine learning algorithm to predict which customers will churn this year. Note that the work you did for “why” problems where you identified some characteristics of churned customers will still be applicable here — and that brings me to: Most organizations don’t usually jump from “What” to “What’s next” stage — every organization is at a different stage depending on their maturity and you can’t apply machine learning to every data analysis problem. Also, with more and more companies using “data” to gain competitive edge, if you are not using machine learning then chances are high that your competitor is and they may out-compete you and that’s why it’s important to continuously invest and reach the highest level — more and more companies and executives are realizing this and it’s a great thing for the data community!
To conclude: Depending on the analytics maturity of your organization and the business problem at hand, you might have to use Machine learning to solve a data analyis problem…And it never hurts to pick up Machine learning basics along with other data analysis skills that you might have.
Hope that helps.
