Article Draft Quantitative Models For Decision-makers Management Essay

Quantitative Models for Decision-makers
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Quantitative Models for Decision-makers
Most companies use artificial intelligence to conduct business operations in the technologically evolving world. The implementation of technology is almost similar in different organizations since they all work towards customer satisfaction and improvement in their fields of activities. On the other hand, data science is implemented in a different perspective. Although many companies may be using a similar idea in data science, they use different ways depending on the industry, business unit, and the goals in place for achievement (Bowne-Anderson, 2018). In this case, different data scientists use different methodologies in their work and fields of operation. For instance, data science works in a procedural manner in the tech industry. The scientists lay a solid foundation of the data to enhance quick performance during analysis, they then goa ahead to choose online experiments that can yield sustainable growth to finally build efficient machine methods of learning and personalizing data products for a better understanding of their customers and achievement of better decision-making processes (Bowne-Anderson, 2018). Data science deals with infrastructure, testing, machine learning for excellent decision making, and data products.
However, a data scientist should have the knowledge that their skills are evolving with the improvement in technology, and they should not rely on their experience and the deep understanding of past involvements. Data science leaders advocate for the essential skills in the field to enhance consistency, even under changing models. For instance, if a question like, “Which skill is more important for a data scientist: the ability to use the most sophisticated...