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Architecting Power BI Solutions in Microsoft Fabric
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Data science is the systematic process of getting valuable insights out of data. However, you may ask, isn’t it the same thing we do in Power BI or any other data engineering process? The key difference is that data science involves advanced techniques such as machine learning and deep learning, which are powered by complex statistical formulas to predict/forecast valuable insights out of data, while in data engineering the focus is to ingest, process, and model the data in a presentable way (for example, as facts and dimensions) for business intelligence applications. In data science, we are expected to predict outcomes/values or results (things such as the price of the stock in 6 months, which team is likely to win the match, and so on) based on the data available, while data engineering presents existing data in a way that makes it easier to gain insights. Hence, the process involved and tools used in a data science project are different...
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