Building an ETL Pipeline with Mage.ai : Using Netflix's Top 100 Movies from Kaggle скачать в хорошем качестве

Building an ETL Pipeline with Mage.ai : Using Netflix's Top 100 Movies from Kaggle

In this video, we will walk through the process of building an ETL (Extract, Transform, Load) pipeline using Mage.AI. Our data source will be Netflix's top 100 movies dataset from Kaggle. We will demonstrate how to extract data from the dataset, transform it into a usable format, and load it into a SQL database for further analysis. We will begin by discussing the importance of ETL pipelines and how they help in the data analysis process. Next, we will introduce Mage.ai, a powerful tool for data manipulation and transformation. We will demonstrate how to use Mage.AI to extract data from the Kaggle dataset and transform it into a format that can be easily loaded into a SQL database. Finally, we will show how to load the transformed data into a SQL database using Python in Mage.ai. This will enable us to perform various analyses on the data, such as generating reports, creating visualizations, and making data-driven decisions. By the end of this video, you will have a solid understanding of how to build an ETL pipeline using Mage.AI and how to use it to extract insights from a real-world dataset. #ETLpipeline #MageAI #NetflixTop100 #KaggleDataset #SQLDatabase #DataAnalysis #DataManipulation #DataTransformation #PythonProgramming #DataDrivenDecisionMaking #DataVisualization #BusinessIntelligence #BigData #DataScience #DataEngineering #MachineLearning #ArtificialIntelligence #TechTutorial #YouTubeTutorial #LearnToCode #CodingCommunity