This repository presents a comprehensive analysis of Superstore, a fictional retail company in the United States, covering the period from 2014 to 2017. Leveraging SQL queries and Looker Studio for visualization.

OCR con comunicación a la API de BigQuery y presentación de los datos en Looker Studio.

💨 'Live' presenting air condition in Poland

About Developed a dashboard that utilized an analysis of user behavior to identify opportunities for enhancing the Google Merchandise Store website, aiming to increase sales and revenue. More precisely to gain insights, utilized functionalities like Funnel Analytics and Cohort Analytics available in Google Analytics to gather valuable insights.

Documenation of the Streamlike Looker studio connector

This repository presents a comprehensive analysis of Education in indonesia.

This pipeline retrieves Yelp Fusion API restaurant data as JSON files, then loads it into Google Cloud Storage. The data is transformed while being moved into BigQuery and refined further with dbt. Finally, Looker Studio visualizes the processed data. Prefect orchestrates the entire workflow.

Repository containing Dinda's portfolio documentation on data preprocessing, visualization, and statistical data analysis.

Business Performance Dashboard

Dashboard Visualization

Data Insight Engine System is a comprehensive data analytics tool that helps users collect, analyze, and display data in a straightforward and interactive manner, aiding them in making informed decisions.

The officially supported Matomo Connector for Looker Studio enables you to explore your Matomo data in Looker Studio at no cost. You can connect to both Matomo Cloud instances or On-Premise instances using just a Matomo Auth Token.

Showcase of various projects that have been created during TuringCollege learning process 2022 -2023

Final project for DataTalks.Club Data Engineering bootcamp

Analyzing customer behavior, determine primary keys and ERD, visualize insights with dashboards and present business strategy recommendations.

An end-to-end data engineering project using Amazon S3, EC2, mage.io, Google BigQuery and Looker.

This repo presents a comprehensive Uber analysis using GCP, Looker, and Mage. From data collection to insights, it showcases integrated data techniques for a full understanding of the process.

For more details please visit the link below☺️