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  • Feature-Image-Data-Visualisation

    Data visualisation using Power BI: Key takeaways

    ByAdmin

    Introduction Insights can be communicated through written reports, visualisation reports, or dashboards. Visualisations are key in data analysis, and it’s common to see the terms “reports” and “dashboards” used interchangeably, even though they serve different purposes. Reports vs. Dashboards Reports provide detailed, static data, often with a focus on historical or specific information. They are…

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    Comprehensive guide to installing Microsoft SQL server

    ByAdmin

    Introduction This guide provides a comprehensive walkthrough for installing Microsoft SQL Server on Windows operating system. It covers the necessary steps to set up SQL Server, install SQL Server Database Management Studio (DBMS), and configure popular sample databases such as AdventureWorks and WideWorldImporters. Although the procedures outlined are tailored for the 2019 version, they are…

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  • Install-Power-BI

    How to Install Power BI: A step-by-step guide

    ByAdmin

    Introduction Power BI is a powerful business analytics tool by Microsoft that allows users to visualise data, share insights, and make data-driven decisions. Whether you’re new to Power BI or need a refresher on how to get started, this guide will walk you through the installation process and provide tips for getting the most out…

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    How to transform data using Power Query: A beginner’s guide

    ByAdmin

    Introduction Power Query is a powerful data connection technology that allows you to discover, connect, combine, and refine data across a wide variety of sources. This guide will provide a detailed step-by-step process on how to transform data using Power Query in Power BI. By following these instructions, you’ll be able to handle data more…

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    How to prepare data for Power BI dashboard using Excel dataset: A beginner’s guide

    ByAdmin

    Introduction Creating effective Power BI dashboards starts with properly prepared data. This guide provides a step-by-step approach to preparing data for visualisation in Power BI, using a sample Excel dataset. By following these instructions, beginners can transform raw data into meaningful insights that are ready for analysis and presentation. Please check out the lessons below…

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  • SQL-Retail-shopping

    SQL exercises on retail shopping: Multiple table queries

    ByAdmin

    We have explored Structured Query Language (SQL) problems in real-world business scenarios using single table queries in a previous post which can be accessed here. We will now focus on scenarios by using multiple table queries albeit still within a typical retail business. If you’re new to SQL and haven’t learned how to install SQL…

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  • Bank deposit - feature image

    Predicting bank deposit subscriptions using machine learning

    ByAdmin

    Introduction The ability to predict customer behaviour has become increasingly important for businesses, especially in the financial sector. For banks, understanding which clients are likely to subscribe to a term deposit can lead to more effective marketing strategies and better resource allocation. This analysis explores a beginner’s approach to predicting whether a client will subscribe…

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  • Income-levels-Feature-Image

    How to predict income levels using machine learning

    ByAdmin

    Introduction The ability to extract meaningful insights from raw data is more crucial now than ever. Among the many datasets available for analysis, the “Adult Census Income” data can be used to understand the socio-economic factors that influence income levels. This dataset, collected from the 1994 U.S. Census, includes a variety of demographic information, such…

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  • Heart-disease-feature-image

    How to predict heart disease treatment using Python

    ByAdmin

    Introduction Heart disease remains one of the leading causes of morbidity and mortality worldwide. Hence, understanding the factors that contribute to heart disease and the treatments that can mitigate its effects is crucial for improving patient outcomes. This project will explore a dataset related to heart attack patients and analyse various demographic, lifestyle, and clinical…

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    How to analyse call-centre-sentiments data using Python

    ByAdmin

    Introduction Customer service quality can make or break a company’s reputation. Call-centres are often at the frontline of customer interactions, making them a crucial component of customer satisfaction strategies. To ensure that these interactions meet customer expectations, it’s essential to analyse and understand the factors that contribute to positive or negative experiences. In this project,…

    Read More How to analyse call-centre-sentiments data using PythonContinue

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