How can data scientists think about business problems

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And when we talk about data, using this same approach will ensure that you are not thinking about a solution before exploring what you really need to solve. It's important for leaders to engage with data scientists early in the process . Despite the fact that 38% of data professionals are involved in decision making , they may not feel that their insights are accurately considered. Several questions may arise from this, but certainly a group of them are related to the difference between understanding the data and understanding the business itself . With this in mind, we can explore a deeper question: how can data scientists think about business problems if they don't understand the business deeply? ADVERTISEMENT I agree that data science project is not an individual activity, however, I strongly believe that data scientists can contribute to hypothesis design .

It is relevant to bring to the table the fact that in a field with Telegram Number Data a talent gap, the balance between industry knowledge and hard data skills can be crucial for successful projects. Data may be just the tip of the iceberg Deep diving into understanding the business should not be seen as a data scientist going beyond his job. This is not true. This kind of behavior is an inspiration to finally design the data set needed for the data science project and also to start another effort on other technical challenges. Keep in mind that data is just the tip of an iceberg that involves much deeper reflections on business objectives. If you don't get deeply involved, you can miss thousands of opportunities.




The effort to frame the business problem is probably the most visible characteristic I have noticed in several data scientists from different backgrounds. Naturally, it's not just up to the data scientist, but also the leadership to get them to the decision-making stage. Conclusion: Bring data scientists together to discuss the business To conclude, there are discussions related to data scientist roles being eliminated by new tools that can automatically apply machine learning. I totally disagree. These tools are probably eliminating roles and writing code without interpretation, that is, dealing only with the tip of the iceberg . Those capable of going deep into the ocean may not be easily replaceable.