PCORnet Ontology to OMOP - beta!

This module enables you summarize and identify the quality of the data using concepts such as aggregation and window functions.

This module covers performing descriptive analytics on time series data, geospatial data, complex data types (arrays, JSON, and JSONB), and text.

This module covers how to assemble multiple tables into a dataset using SQL queries. It also introduces how to transform and clean data using SQL functions.

Exploring the COVID-19 dataset to identify the trends in cases and deaths from 2019 to 2022

📊 Power BI report to track real time operating status with focus on its downtime with integrated ERP systems Data

The repository contains Structured Query Language (SQL) Scripts. The Multiple SQL scripts for various projects which includes data cleaning, data pre-processing, data processing, data transformation and insights gaining through Query Language.

This project analyzes sales data for AdventureWorks, focusing on revenue, customer segments, and product performance. The dashboard provides insights into top-selling products, sales by region, and customer trends across multiple years. It helps in identifying sales opportunities and optimizing marketing strategies.

The repository contains Structured Query Language (SQL) Scripts. The Multiple SQL scripts for various projects which includes data cleaning, data pre-processing, data processing, data transformation and insights gaining through Query Language.