Advanced Analytics is a comprehensive set of analytical techniques and methods - Big Data, Artificial Intelligence, Machine Learning, and Continuous Intelligence that translate into different algorithms that are capable of learning to solve problems. The problems correspond to a company's strategic and operational objectives and its industry challenges or demands.
Artificial Intelligence and Machine Learning capabilities are still developing, and it is important to understand their limitations and requirements. The adoption time can be fast, but it depends on resources, quality of the data, how it will be used, the nature of each business, and its technology infrastructure.
Artificial Intelligence is today's new electricity. That's the way Kai-Fu Lee, a pioneer in AI, puts it. On the one hand, it's an accelerator of processes, and on the other hand, it is transversal. It isn't something you decide to use or adopt. It's already in your day-to-day life, at least as a citizen.
Artificial Intelligence and other technologies are reaching organizations in many different ways depending on the layers of analytics that each company has, its needs, and objectives. Below, we show a selection of relevant trends according to the degree of adoption in the market that will allow you to take advantage of their potential at the right time.
In the Data & Analytics world, Cloud-based data warehousing has begun to take hold as a leading practice for long-term data management success. However, organizations are finding it arduous to properly emerge ahead of the curve on this front.
Making business decisions based on the analysis of data must be done in conjunction with a company’s overall strategic goals. Without knowing what these said goals are, it is impossible to prioritize using data correctly.
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