How different is it to handle data in real life
How different is it to handle data in real life and in a learning environment? Data is the main driver of results, but in your daily routine, you may not have a ready-made data set for every scenario. From this reality, it is important to reinforce: data science definitely begins long before data . That's why I always strongly recommend to data scientists to also put a lot of energy into the problem definition and not just think about the analytical product that will be delivered at the end. The business concept always comes first. This is very similar to when marketers do their annual planning, for example. It's tempting to throw your presence into the metaverse just because everyone is talking, for example.
But, you should also ask yourself first: why do Telegram Number Data you want to be in the metaverse? What business problems do you want to solve? Remember: strategies always come before tactics . 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 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. |
