Abdelrhman Y. Profile

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$7 USD / час

giza,

egypt

$7 USD / час

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Abdelrhman Y.

@abdyassein

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(0 отзывов(-а))

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$7 USD / час

giza,

egypt

$7 USD / час

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Data Engineer | ETL Developer | Hadoop | Spark

Abdelrhman is a Data Engineer with more than Five years of coding experience with skills • Python • Pandas • Big Data Tools (Spark , Hive , Pig , HBase , Sqoop) • SQL • Data Engineering (Data Pipeline Creation, Data Pipeline Partitioning , ETL , Data Extraction, Data Pipeline Maintenance, Data Pipeline DAGs) • Data wrangling • Data Warehousing, Data Modeling , Database Design • Hadoop • Data Automation Tools (Apache Airflow ) • AWS ( Redshift , AWS Data Lakes, Amazon Web Services Basics, Amazon Web Services Setup, Amazon S3,AWS Data Warehouse) • Database ( Database Fundamentals, Database Denormalization, Database Normalization, Table Partitioning) Abdelrhman has worked on several projects that are mainly about Data Data Modeling , Data Warehouse ,Data Lake and Data Pipelines: • Data Modeling • Data Modeling With SQL Server • Data Modeling with Postgres. • Data Modeling with Apache Cassandra • Data Warehouse • Data Lake • Data Pipelines • ETL Using Deafferent Tools If you are looking for a Highly professional Data Engineer and excellent communicator then Abdelrhman is the one.

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Портфолио

In this project, We will Automate transform and transfer data and build a data warehouse to make analysis easier Using Mysql Server And AirFlow

Call Center Data Warehouse And ETL Project With AirFlow

In this project, We will transform and transfer data and build a data warehouse to make analysis easier

Call Center Data Warehouse And ETL Project

A startup called Sparkify wants to analyze the data they've been collecting on songs and user activity on their new music streaming app. The analysis team is particularly interested in understanding what songs users are listening to. Currently, there is no easy way to query the data to generate the results, since the data reside in a directory of CSV files on user activity on the app.

This project uses python to read the contents of the csv files and then stores the data in Apache Cassandra databases.

Data Modeling with Apache Cassandra

This data comes from the US National Tourism and Trade Office. A data dictionary is included in the workspace; this is where the data comes from. There's a sample file so you can take a look at the data in csv format before reading it all in. You do not have to use the entire dataset; just use what you need to accomplish the goal you set at the beginning of the project.

Data Engineering Capstone Project

Sparkify is a music streaming startup with a growing user base and song database.

Their user activity and songs metadata data resides in json files in S3. The goal of the current project is to build an ETL pipeline that extracts their data from S3, stages them in Redshift, and transforms data into a set of dimensional tables for their analytics team to continue finding insights in what songs their users are listening to.

Build Data warehouse On Aws

A music streaming company, Sparkify, has decided that it is time to introduce more automation and monitoring to their data warehouse ETL pipelines and come to the conclusion that the best tool to achieve this is Apache Airflow.

They have decided to bring you into the project and expect you to create high grade data pipelines that are dynamic and built from reusable tasks, can be monitored, and allow easy backfills. They have also noted that the data quality plays a big part when analyses are executed on top the data warehouse and want to run tests against their datasets after the ETL steps have been executed to catch any discrepancies in the datasets.

The source data resides in S3 and needs to be processed in Sparkify's data warehouse in Amazon Redshift. The source datasets consist of CSV logs that tell about user activity in the application and JSON metadata about the songs the users listen to.

Data Pipelines with Airflow

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Опыт работы

free lancer

нояб. 2022 - Настоящее время

Build and maintain data systems.Design Architecture and build pipelines.

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Квалификация

Udacity

2022

Learn to design data models, build data warehouses and data lakes, automate data pipelines, and work with massive datasets

Udemy

2022

Learn the concepts of Spark's DataFrames and Resilient Distributed Datastores Develop and run Spark jobs quickly using Python and pyspark Translate complex analysis problems into iterative or multi-stage Spark scripts Scale up to larger data sets using Amazon's Elastic MapReduce service

DataCamp

2022

discover how to build an effective data architecture, streamline data processing, and maintain large-scale data systems. In addition to working with Python