Build clickstream analytics on AWS for your mobile and web applications
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Updated
Jul 2, 2024 - TypeScript
Build clickstream analytics on AWS for your mobile and web applications
This project implements a data pipeline using Amazon Web Services (AWS) to process and analyze a Flight Dataset. The pipeline collects raw data, processes it, stores the processed data in a data warehouse, and performs analysis using SQL queries. The analysis results are visualized dynamically using Power BI dashboards.
Redshift Python Connector. It supports Python Database API Specification v2.0.
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Data pipeline from RDBMS to AWS
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This project aims to securely manage, streamline, and perform analysis on the structured and semi-structured YouTube videos data based on the video categories and the trending metrics.
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This project provides a comprehensive data pipeline solution to extract, transform, and load (ETL) Reddit data into a Redshift data warehouse. The pipeline leverages a combination of tools and services including Apache Airflow, Celery, PostgreSQL, Amazon S3, AWS Glue, Amazon Athena, and Amazon Redshift.
building etl pipelines to migrate music json data/ metadata files (semi-structured data) into a relational database stored in AWS Redshift cluster
Virtual Schema for connecting Redshift as a data source to Exasol
Build an ETL pipeline for a database hosted on AWS Redshift.
load local files to AWS Redshift using Python and Unleash Insights with Power BI
PySpark RDD and DataFrame Examples
Scan databases and data warehouses for PII data. Tag tables and columns in data catalogs like Amundsen and Datahub
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