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ArtificialIntelligence development comes to the stage where non-technical people can use it in their everyday and professional life. So these days, you probably want to know how ArtificialIntelligence (AI) can affect the work of an IT Business Analyst. What is AI?
Last, and still a very painful challenge for most users, is the familiarity with the underlying data and datamodel. NLQ is gaining traction in the big data analytics tools domain for its quick answers and ease of use. In other words, how the variables are named, and the granularity of their values.
Many solutions require the use of different programming languages to perform advanced analysis such as R, Python, Javascript, just to name a few, and knowing them can significantly enhance your skillset. This could involve anything from learning SQL to buying some textbooks on data warehouses.
By incorporating features that analyze data, identify trends, and generate recommendations, applications can become more than just productivity tools; they can transform into strategic decision-making partners. This intuitive approach cuts through technical barriers, transforming even non-technical users into data-savvy decision makers.
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