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El Mehdi El Wafi's avatar
El Mehdi El Wafi
proMorocco
Linux VPS SysAdmin AWS & Oracle Cloud Architect | Terraform
$5k+
Earned
1x
Hired
9
Followers
Linux VPS SysAdmin AWS & Oracle Cloud Architect | Terraform
Cover image for 92% Cost OFF of EC2 Airflow/DBT Workers using Lambda
92% Cost OFF of EC2 Airflow/DBT Workers using Lambda
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11
Cover image for DevOps/Cloud & DataOps maintainer
$9.7K+ earned
DevOps/Cloud & DataOps maintainer
3
25
Cover image for 🛠️ DevOps Tips 🛠️ If
🛠️ DevOps Tips 🛠️ If your GitHub workflows or jobs are failing due to jobs concurrently accessing and/or modifying shared resources, You can control execution at the workflow or job levels using the concurrency. Jobs/Workflows in the same are prohibited from running at the same time, and you can cancel any jobs/workflow if you trigger another one. Groups let you define compartments in which you don't want concurrent workflows running. They can be organized however you like. I find that using them in separate environments is a great practice. Cancel-in-progress: specifies if the old running job/workflow needs to shut down. Read more in docs: https://docs.github.com/en/actions/how-tos/write-workflows/choose-when-workflows-run/control-workflow-concurrency
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3
492
Cover image for Enterprise VM Template for Proxmox VPS
Enterprise VM Template for Proxmox VPS
0
6
Apache Airflow(2)
Aishwary Dhare's avatar
Aishwary Dhare
proBengaluru, India
Full Stack Rapid Prototyping – Vision to Product in Weeks 🚀
5.0
Rating
6
Followers
Full Stack Rapid Prototyping – Vision to Product in Weeks 🚀
Cover image for Migration of ETL Pipelines to Apache Airflow
Migration of ETL Pipelines to Apache Airflow
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5
Cover image for Global FinTech Development for MishiPay
Global FinTech Development for MishiPay
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4
Cover image for Development of PayLater & PayLater Business Apps
Development of PayLater & PayLater Business Apps
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10
Cover image for Development and Launch of MishiPay Self-checkout Kiosks
Development and Launch of MishiPay Self-checkout Kiosks
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5
Apache Airflow(1)
Muhammad Arsalan's avatar
Muhammad Arsalan
Karachi, Pakistan
Data Engineer | Web Scraping | SQL | BI Dashboards
Data Engineer | Web Scraping | SQL | BI Dashboards
Cover image for Problem: Financial data from stocks and
Problem: Financial data from stocks and crypto APIs was scattered, refreshed manually, and not ready for analytics or ML use. Solution: Built an Apache Airflow pipeline to collect, transform, validate, and load real-time financial data from multiple APIs into PostgreSQL, MongoDB, AWS RDS, and Qdrant. Tools: Apache Airflow, Python, PostgreSQL, MongoDB, AWS RDS, Qdrant, APIs Result: Automated sub-hourly data refresh, processed thousands of records daily, and delivered clean data for dashboards, analytics, and vector search.
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Cover image for Problem: Batch data processing was not
Problem: Batch data processing was not suitable for real-time analytics and scalable cloud-based data ingestion. Solution: Created a real-time streaming pipeline using Kafka on AWS EC2, stored processed data in S3, cataloged it with AWS Glue, and queried it with Amazon Athena. Tools: Python, Apache Kafka, AWS EC2, Amazon S3, AWS Glue, Amazon Athena, Pandas Result: Built an end-to-end cloud data streaming workflow that supports real-time ingestion, storage, cataloging, and SQL-based analytics.
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74
Cover image for Problem: Finance data was difficult to
Problem: Finance data was difficult to analyze across sales, profit, orders, discounts, countries, and customer segments. Solution: Created an interactive Power BI dashboard with KPI cards, sales trends, profit analysis, country performance, and segment-level insights. Tools: Power BI, Power Query, DAX, Excel, Data Modeling Result: Delivered a clear executive dashboard for tracking financial performance, identifying trends, and making faster business decisions.
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Cover image for Problem: Users needed a faster way
Problem: Users needed a faster way to find the most relevant counselor based on specialization and available data. Solution: Built a recommendation workflow using PySpark for data processing and Redis for fast lookup and recommendation serving. Tools: Python, PySpark, Redis, Docker, Docker Compose Result: Created a containerized recommendation system that processes counselor data and returns relevant matches efficiently.
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57
Apache Airflow(1)
Umar Shaikh's avatar
Umar Shaikh
Pune, India
Data Scientist, Backend Engineer, Data Analyst
10
Followers
Data Scientist, Backend Engineer, Data Analyst
Cover image for Proud to share that I’ve earned the Oracle Cloud Infrastruct...
Proud to share that I’ve earned the Oracle Cloud Infrastructure (OCI) 2025 Certified Data Science Professional certification (https://tinyurl.com/dsmlaidl) — issued by Oracle. This certification validates my expertise in Machine Learning (ML) | Data Science | Artificial Intelligence (AI) | Cloud Computing, showcasing my ability to design, build, deploy, and manage end-to-end ML solutions using OCI Data Science and Oracle AI Services. 💡 Core Expertise: 🔹 Scalable ML pipelines on OCI Data Science 🔹 AI, MLOps, and Cloud best practices for model optimization 🔹 Leveraging OCI Data Flow, Data Catalog, and AI Services for automation 🔹 Skilled in Python | TensorFlow | Scikit-learn | OCI SDKs for production-grade workflows 💪 Passionate about applying ML | Data Science | AI | Cloud Innovation to drive real business transformation.
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2
163
Cover image for main_palmer_penguin_EDA_2024-project
main_palmer_penguin_EDA_2024-project
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14
Cover image for main_palmer_penguin_EDA_2024-project
main_palmer_penguin_EDA_2024-project
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9
Cover image for Fraud_Transaction_Detection-Fraud_Finder_ID12254…
Fraud_Transaction_Detection-Fraud_Finder_ID12254…
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14
Apache Airflow(1)
Cesar Ramos's avatar
Cesar Ramos
Omaha, USA
Data expert turning chaos into insights
Data expert turning chaos into insights
Cover image for One of the most common problems I see as companies grow isn’...
One of the most common problems I see as companies grow isn’t a lack of data — it’s too many disconnected reports. In this project, leadership relied on spreadsheets and ad hoc reports. Numbers didn’t always line up, and answering basic questions took too long. What I did: Centralized reporting in Power BI Defined clear, decision-driven KPIs Modeled data so metrics reconciled across teams Designed dashboards focused on clarity The result: Leadership gained a trusted, real-time view of performance they could rely on week after week.
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Cover image for Financial dashboards shouldn’t just show trends — they shoul...
Financial dashboards shouldn’t just show trends — they should explain what’s driving profitability. In this project, I built a Tableau dashboard that connects weekly sales, costs, profit, and ROI in a single view, allowing leaders to see where and when returns were actually being generated. What I focused on: Aligning sales, cost, and profit to the same time grain Making ROI visible alongside volume, not buried in spreadsheets Enabling quick comparisons across venues, vendors, and performers The result: Teams could identify high-ROI weeks and segments and make informed decisions about pricing, spend, and future bookings.
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114
Cover image for From Disorganized Reporting to Executive Power BI Dashboards
From Disorganized Reporting to Executive Power BI Dashboards
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2
Cover image for Adding a new company into an existing reporting suite this w...
Adding a new company into an existing reporting suite this week as our client continues to grow. The work isn’t just wiring in new data — it’s making sure metrics stay consistent, historical trends remain intact, and leadership can still compare performance across the business without friction. Growth is exciting, but it definitely stress-tests your analytics.
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58
Apache Airflow(1)
ANIMESH SINGH's avatar
ANIMESH SINGH
Delhi, India
Data & AI Engineer
Data & AI Engineer
Cover image for Problem: Many organizations still process invoices
Problem: Many organizations still process invoices manually by reading PDF documents and entering key details (invoice number, vendor, amount, etc.) into systems. This process is slow, error-prone, and difficult to scale, and it also makes it harder to detect duplicate invoices or incorrect totals. Solution: This project builds an automated invoice processing pipeline that converts uploaded invoice PDFs into structured data. It uses OCR to extract text, LLMs to identify invoice fields, validation checks to ensure correctness, and Kafka-based event streaming to manage the processing pipeline. The extracted data is stored in PostgreSQL and visualized through a dashboard, enabling faster, scalable, and more reliable invoice processing.
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Cover image for Problem Statement Urban traffic management systems
Problem Statement Urban traffic management systems lack real-time, integrated data combining traffic conditions with weather patterns. This results in poor routing decisions, delayed emergency responses, and inefficient traffic flow management. Solution Developed a comprehensive real-time ETL pipeline that integrates traffic APIs and weather data sources, processes millions of data points, and delivers actionable insights through interactive dashboards for traffic management and route optimization.
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Cover image for A fully Dockerized real-time IoT
A fully Dockerized real-time IoT ETL pipeline that simulates device telemetry, processes events through MQTT and Kafka, orchestrates workflows with Airflow, and delivers real-time alerts and insights to CRM systems with monitoring via Grafana and Loki.
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Cover image for A fully local RAG pipeline
A fully local RAG pipeline that transforms your PDFs into a queryable knowledge base using FAISS vector search and Ollama LLMs. No cloud, no API keys - just private, grounded document intelligence running entirely on your machine.
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39
Apache Airflow(3)