A data pipeline refers to a series of connected tasks that handles the extract, transform and load (ETL) as well as the extract, load and transform (ELT) operations and integration from a source to a target storage like a data lake or data warehou...
The design and planning phase of a data engineering project is crucial for laying out the foundation of a successful and scalable solution. This phase ensures that the architecture is strategically aligned with business objectives, optimizes resou...
we will delve into the essential building blocks of data engineering, placing a spotlight on the discovery process. From framing the problem statement to navigating the intricacies of exploratory data analysis (EDA) using Python.
With the help of electronic health records (EHR) and a wealth of health-related data, there is a significant opportunity to leverage machine learning techniques for predicting and assessing the risk of heart disease in individuals.
Understanding how to harness the potential of data is paramount. Understand data analysis and visualization using a code-centric and low-code approach.