Stream wise join operator to convert data into RDBMs to a suitable format for Data Warehouses.
-
Updated
Feb 4, 2023 - Java
Stream wise join operator to convert data into RDBMs to a suitable format for Data Warehouses.
A dataware house is generated for streaming data of a superstore using extended mesh join by Syed Husnain Haider Bukhari
This repository contains a simulated real-time data warehouse for the METRO Shopping Store. The project utilizes streamed transactional (simulated) and a master database to create a warehouse using MESHJOIN, then performs advanced OLAP analyses on it. It was developed as part of the course Data Warehousing & Business Intelligence (DS3003).
Datawarehouse project that displays the power of using an extended mesh join to join incoming stream of transactional data with multiple master data using a single hash table with no collisions.
I Implemented a Near Real-time Data Warehouse Prototype for METRO. To mimic the near real-time Data Warehouse using 10,000 Transaction from METRO Against 100 products present in the Master Data.
A robust near real-time retail data warehouse system leveraging Java, MySQL, and MeshJoin for efficient ETL, star schema design, and actionable OLAP insights.
The METRO DW prototype uses Mesh Join & Star Schema for sales, customer & inventory data analysis. Implemented in SQL & Java for fast, accurate, & consistent data retrieval. Offers valuable insights & can be queried with standard BI tools.
MeshJoin-Streaming-ETL-Data-Warehouse integrates real-time transactional data with master data using the Mesh Join algorithm. It processes and enriches data, then loads it into a data warehouse for analysis, leveraging efficient ETL processes and OLAP-ready SQL queries.
To associate your repository with the meshjoin topic, visit your repo's landing page and select "manage topics."