Feature-Image-Data-Visualisation

Data visualisation using Power BI: Key takeaways

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…

Image by Freepik

Comprehensive guide to installing Microsoft SQL server

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…

Feature-Image-X-P.

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

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…

Bank deposit - feature image

Predicting bank deposit subscriptions using machine learning

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…

Income-levels-Feature-Image

How to predict income levels using machine learning

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…

Heart-disease-feature-image

How to predict heart disease treatment using Python

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…

Call centre Feature Image

How to analyse call-centre-sentiments data using Python

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,…