When you work in business intelligence, you inevitably deal with files—lots of them. Sometimes you’ll get a flood of daily CSV exports from your data warehouse. Other times, you’ll inherit a single monster file so large that Excel waves the white flag before it even opens.
Continue reading
When you’re building a data warehouse, the way you model your data can make the difference between fast, intuitive analytics and a never-ending maze of joins. Two of the most common data modeling approaches are Star Schema and Snowflake Schema. Both serve the same purpose—structuring your data to support reporting and analysis—but they differ in design, performance, and usability.
Continue reading
If you’re learning data analysis with Python, mastering the pandas DataFrame is essential. A DataFrame is a powerful, table-like data structure that lets you load, explore, clean, and analyze data quickly.
Continue reading
In Business Intelligence (BI), SQL is used to extract and manipulate data from databases, while Python adds flexibility for data processing, visualization, and automation. Combining both enables you to build powerful, automated BI pipelines and dashboards.
Continue reading