Hi all, Glad connecting you. I have a question that is left unanswered by many. I hope few can answer. Nowadays all talk about data science/analytics/ML/I want to start a career in analytics and all. And also the institutes talk about analytics courses that can get you good salary and all. My question is why no one is talking about how to build a business knowledge before they talk about analytics. How can anyone think of solving a problem before they understand the business behind it.People in in the industry tell 80 of the time is lost in cleaning the data. Well I understand. But if the data is cleaned the problem is solved? Noways. No body is talking about building a business knowledge and how to build a process map of the business that they are dealing with.In data hacakathons, companies give only data and ask us to solve in less time and they see the approach of solving a problem. But I am sure nobody tries to understand the business and they simply jump to the data and assume they can solve it. Hope I did not over comment my thoughts
Can you please share your comments?
Hi, I like the post ,the business knowledge is enterprenurship , and it differs from persons to persons. U need to study enterprenurship for business knowledge and it is not taught by institutes - institution’s said to everyone is to get a good job that’s it . It is not a weird u need to think out of the box for enterprenurship.
It is certainly critical with less than deserved focus across analytics and data science teams. There is a lot of one time problem solving that doesn’t layout the reusable language required to bridge the gap between business processes and data definitions, which is a cause of a lot of time wasted in the data cleansing as well as interpretation. But it can’t be taught from business point of view as each business has it’s own DNA. What can be taught though is the problem solving approach from a functional point of view that will make this meaning mapping exercise efficient and effective. It’s not rocket science, it’s just not valued enough. Who pay’s a data engineer these days A silent killer…