The rate of data generation has increased throughout this century at a predictable rate more or less. According to Seagate UK, “By 2025, there will be 175 zettabytes of data in the global data-sphere”. Companies place a higher value on data. Companies are discovering new ways to use data to their advantage. They use data to analyze the current status of their business, forecast the future, model their customers, avoid threats and develop new goods. Data Engineering is the linchpin in all these activities.
Python is today’s most popular programming language with endless applications in various fields. It is ideally suited for deployment, analysis, and maintenance thanks to its flexible and dynamic nature. Python for Data Engineering is one of the crucial skills required in this field to create Data Pipelines, set up Statistical Models, and perform a thorough analysis on them.
The projects above showcase the power of Python for data analysis.