Data Analytics involves the process of inspecting, cleansing, transforming, and modeling data to discover meaningful information, draw conclusions, and support decision-making. Our Data Analytics category provides a comprehensive exploration of this field, covering topics from fundamental analytics techniques to advanced data manipulation and interpretation strategies.
Whether you’re a data enthusiast starting your analytics journey, a seasoned data scientist, or a business professional leveraging data for strategic insights, this category offers valuable resources to enhance your knowledge and skills.
You can improve your data visualizations productivity by using the built-in table functionality available in Excel. This tutorial and sample Excel workbook, available on GitHub, will move you from raw table to interactive analysis in less than 5 minutes.
Needing to Generate test data can be very stressful. I like to produce sample data that contains realistic values, such as professional names so that the people involved in the training have a frame of reference and do not get tripped up on the data. Realistic datasets can be created by following these steps and utilizing the resources listed below.
How to use Excel Unpivot function to transform your data entry tables into fact tables for better data analysis. This comprehensive guide provides step-by-step instructions, making the process of converting Excel tables using Unpivot Columns functionality easy and efficient.
I added R to my toolkit and have had great success using it on many projects, for not only discovery but also for visualizations. R provides many packages and functions that let you perform data discovery over a data set.
