Enhancing Analytics through Data Pipelines Data pipelines serve as the fundamental building blocks for all analytics projects. As the saying goes, a significant portion of data science involves the cleaning and transformation of data. This introductory course aims to refine your skills in constructing efficient, high-performing, and dependable data pipelines. Data pipelines form the bedrock of robust data platforms. Developing these pipelines is a crucial competency for data engineers, who play a pivotal role in enabling businesses to embrace a data-driven future. This introductory course will equip you with the expertise to construct effective, high-performing, and reliable data pipelines. Building and Sustaining ETL Solutions Throughout this course, you will delve into the comprehensive process of constructing a data pipeline. You will acquire proficiency in utilizing Python libraries such as 'pandas' and 'json' to extract data from both structured and unstructured sources. This data will then undergo transformation and be stored for downstream utilization. Along the way, you will gain confidence in employing tools and techniques such as architecture diagrams, unit-tests, and monitoring, which will distinguish your data pipelines from others. As you progress, you will apply your newly acquired skills through hands-on exercises. Boosting Data Workflows Upon completion of this course, you will be equipped to design, develop, and leverage data pipelines to enhance your data workflow in your current role, future career, or personal project.