From this reality, it is important to reinforce

msthasna315

Bureau of Labor Statistics predicts that the number of jobs in the field of data science will grow by approximately 28% through 2026 . However, have you ever thought about what kind of problems data scientists can work on? ADVERTISEMENT Here at Rock Content, we use data to predict when a customer is going to cancel a contract, that way we can use retention techniques before they make the decision. When we detect that possibility, other teams proactively engage with customers to save this revenue. This is not the only application of data science . From challenges related to acquiring new customers to cross-selling opportunities in business: data scientists focus on consuming data to solve problems .

It is natural for data scientists to approach Telegram Number Data such business problems with different strategies. Although it is healthy, especially when a team is full of professionals from different backgrounds, there is one characteristic among the most successful that I would like to discuss. Data Science projects in real life are not exactly the same as those we find in learning environments or on data competition websites, such as Kaggle . This is not to say that those data competencies are bad, but dealing with those challenges does not mean that the same success will be achieved in real-life projects. 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 you want to be in the metaverse? What business problems do you want to solve? Remember: strategies always come before tactics .