Be sure to check out my previous article on creating a Likert scale, as we’ll be using the same restaurant survey dataset. However, we won’t be using any of the calculated fields from the Likert scale, so feel free to skip it if you’d like. That said, the final dashboard will feature both the Likert and NPS charts side by side—they always pair well together, don’t you think?
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Surveys are powerful tools for gathering feedback and insights, with Likert scales and Net Promoter Score (NPS) being two popular methods for measuring attitudes, opinions, and customer satisfaction. Likert scales assess the level of agreement or disagreement on a statement, while NPS measures customer loyalty by asking how likely respondents are to recommend a product or service.
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In the world of databases, SQL is a foundational language that serves as the backbone for interacting with relational databases. However, when delving deeper into SQL, you will come across terms like ANSI SQL and T-SQL, which may seem confusing at first. In this article, we’ll explore what SQL, ANSI SQL, and T-SQL are, how they differ, and their specific use cases.
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Power Query is a powerful tool used in Power BI, Excel, and other Microsoft products to clean, transform, and load data. While it simplifies data preparation, users often encounter various errors that can disrupt workflows and hinder progress. Understanding these errors and knowing how to resolve them is crucial for any data professional. In this blog post, we will explore some common Power Query errors, their causes, and practical solutions to fix them.
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