Omar Mahmoud (@3amory99)
github

3amory99

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  • Stars
    star
    46
  • Global Rank 361,753 (Top 13 %)
  • Followers 17
  • Following 15
  • Registered over 5 years ago
  • Most used languages
    Jupyter Notebook
         65.2 %
    TSQL     13.0 %
    Python
         13.0 %
    MDX     4.3 %
    Java
         4.3 %
  • Location 🇪🇬 Egypt
  • Country Total Rank 3,041
  • Country Ranking
    MDX     4
    TSQL     4
    Jupyter Notebook
         65
    Python
         508
    Java
         1,030

Top repositories

1

Gravity-Books-Sales-End-to-End-Project

This project encompasses the complete data lifecycle, from data extraction and transformation to in-depth analysis and compelling visualizations. The process is divided into three main phases
TSQL
4
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2

Translator

Automatic language recognition and its ability to translate into any language
Python
3
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3

Singularity-Data-Analysis

In this repository I will take you on a comprehensive tour of Data Analysis track
Jupyter Notebook
2
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4

Building-Sales-Data-Mart-Using-ETL-SSIS

By using AdventureWorks2022 Dataset I have built a Sales Data Mart using (SQL Server Integration Services SSIS) SQL Server involves leveraging the capabilities of Integration Services (SSIS) and the Modeling of SQL Server, This Data mart offers several benefits, making them valuable components in the main purpose of data management and analytics wi
TSQL
2
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5

Amazon-Product-Scrapping-with-Selenium

Gather essential product data from Amazon with ease using this Python web scraper and Selenium. Extract product descriptions, prices, ratings, and more for insightful market research and analysis.ct data from Amazon with ease using this Python web scraper. Extract product descriptions, prices, ratings, and more for insightful market resear
Jupyter Notebook
2
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6

Telecom-ETL-Using-SSIS

Data, resources, and tools, to help your business thrive. GSMA Services are here to enable companies and organizations within the telecoms ecosystem, to do business together more effectively. As well as to maintain the standards and reputation of the industry. Our services are underpinned by unique, accurate, and comprehensive data. Information, on
TSQL
2
star
7

Web-Scraping

Jupyter Notebook
2
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8

Mastering-Python-Hackerrank-Workshop

This repo hosts the solutions for a comprehensive workshop on mastering Python programming through HackerRank challenges. Whether you're a beginner looking to learn Python from scratch or an experienced programmer aiming to enhance your Python skills, this workshop provides a structured learning path that covers a wide range of topics.
Jupyter Notebook
2
star
9

voice-over-creator

Python
1
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10

Singularity-Python-Programming

This is a Singularity-Python-Programming
Jupyter Notebook
1
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11

Building-Northwind-DWH-Using-Talend

Unlock the power of data with our comprehensive Talend project aimed at constructing a robust (DWH) from the renowned Northwind dataset. Divided into two pivotal phases, this project seamlessly integrates data from the Northwind Access Database and the Transactional Database in SQL Server.
Java
1
star
12

Wuzzuf-Job-Postings-Web-Scraping

Wuzzuf-Job-Postings-Web-Scraping
1
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13

Loading_and_Saving_JSON_Files

Working with JSON (JavaScript Object Notation) in Python is quite straightforward and commonly used, especially when dealing with data interchange between different systems or when storing configuration data. Python provides built-in libraries for working with JSON data. Here's how you can work with JSON in Python
Jupyter Notebook
1
star
14

Data-Cleaning-with-Python-and-Pandas

Jupyter Notebook
1
star
15

RedHat-CentOS-Linux-Commands-Cheat-sheet

Explore the power of Linux (CentOS) commands for efficient data engineering. This repository provides a comprehensive collection of essential Linux commands tailored for data engineers. From file manipulation to data transformation and pipeline management. It's mainly as a reference for me as a Data Engineer.
1
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16

EDA-IBM-HR-Analytics-Employee-Attrition

This challenge is designed to explore and analyze factors contributing to employee attrition in a simulated HR setting using a dataset from IBM.
Jupyter Notebook
1
star
17

Olympic-Data-Analytics-End-to-End-Project

1
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18

Analyze-A-B-Test-Results

Project to analyze A/B test results using python
Jupyter Notebook
1
star
19

Sparks-Foundation-Intern

Jupyter Notebook
1
star
20

OLAP-Cubes-in-SSAS

Build an OLAP Cube in SSAS from SQL Server Analysis Services Data
MDX
1
star
21

3amory99

1
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22

EDA-on-Netflix-Movies-and-TV-Shows-

Netflix is a leading player in streaming media with over 200 million global subscribers. Its transformation from DVD rental service to media publisher through its Netflix Originals program has made it a dominant player in the industry.
Jupyter Notebook
1
star
23

Converting-nested-JSON-structures-to-Pandas-DataFrames

Converting Nested JSON Structures to Pandas DataFrames
Jupyter Notebook
1
star
24

Podcust-Summary-Data-Pipeline-Using-Airflow

Creating a data pipeline using Airflow. The pipeline will download podcast episodes and automatically transcribe them using speech recognition. We'll store our results in a SQLite database that we can easily query.
Python
1
star
25

Data-Modeling-With-Apache-Cassandra-Using-Python

The Sparkify Music Streaming Analysis project focuses on creating a NoSQL database and an ETL pipeline for Sparkify, a music streaming startup. Sparkify aims to analyze the data collected from its new music streaming app, covering songs and user activities.
Jupyter Notebook
1
star
26

HealthCare-DWH-Integration-and-Analysis

Use Case: Data Warehouse Design and ETL Process for Healthcare Data and get insights using SSAS
1
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27

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28

Data-Cleaning-with-Python-Using-Pandas

It's a process of preparing raw, unstructured, or messy data for analysis by using the Python programming language and Pandas library. This involves tasks such as handling missing values, removing duplicates, correcting data types, and transforming data into a more usable format. Data cleaning is a crucial step in the data preprocessing pipeline.
Jupyter Notebook
1
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29

Sparkify-App-Data-Lake-Using-Apache-Spark-and-S3

Sparkify app, my objective is to assist Sparkify, a music streaming startup, in migrating its data warehouse to a data lake. To achieve this, I have developed an ETL (Extract, Transform, Load) pipeline. This pipeline is designed to extract data from S3, process it using Apache Spark, and subsequently load the processed data into a new S3 storage lo
Jupyter Notebook
1
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