Future of Enterprise Data Science: From Custom Build to Building Blocks
The value and importance of data, and the need to use machine learning and artificial intelligence for enterprises and their customers, is undeniable. Many companies have successfully completed the first phase of their data-driven transformation and are now faced with the task of creating sustainable value for the organization through scaling. In recent years, the majority of companies have taken the path of custom development for their data science projects, rather than looking into out-of-the-box solutions. With the advancement of current market-available solutions, the strategy is shifting towards "buy" in the "make vs. buy" decision process. Skills that were once rare and difficult to access are becoming "commodities" that can be standardized and automated, and companies are moving towards data science and AI ecosystems. The current development of Generative AI is boosting this transformation. The key questions remain the same: "What should the organization look like in the future for efficient scaling of data-driven solutions?", "What will be the role of data scientists?", and "What skills will be a competitive advantage?"