Solving Business Problems with Data Science

There is no one size fits all solution/framework to convert any business issue to a data science solution. The best, a data science transformation team can manage is lay out an explicit plan of things they are going to undertake from problem to solution.

1. Once, the business analyst understands the pain points, he/she comes up with the business problem (see the chart above)

2. After finalising the business problem, a team of data scientists or senior data scientists, convert it to a tractable data science problem

3. The solution design stage takes into consideration the scope, assumptions & goals of the data science solution

                                 

4. Now, you need to implement it with the help of software engineers, data engineers & junior data scientists

5. To validate the implementation, the senior data scientist does the assessment, if it passes this stage we deploy the solution to business user. If it fails, we need to go back to the drawing board and start from the solution design stage again.

As, you might have understood, this is an iterative process.
You can check the video below: