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Daisy Okacha
Data collection from an API provided by USGS_3DEP ( United States Geological Survey 3D Elevation Program).
I created a python module that domain experts and data scientists can use to fetch, visualise, and transform publicly available satellite and LIDAR data from the API.
Output may include a graphical display of the returned elevation files as either a 3D render plot or as a heatmap.
In this project, I implemented these Data Engineering skills:
In this project, I implemented these Data Engineering skills:
-Writing python packages and documentation
-Fetching data from an API
I used the Extract Load Transform (ELT) framework using DBT to set up a postgreSQL data warehouse.Airflow orchestrated the pipelines and redash visualized the data.
Later,i migrated the Data Warehouse to a mySQl Data Warehouse and used superset for visualization.
I worked with pNEUMA data .The PNeuma project captured all traffic during the morning rush hour in the business district of Athens, for 5 days.
In this project, I implemented these Data Engineering skills:
In this project, I implemented these Data Engineering skills:
Performing data transformation using dbt
Fetching data and loading it to a data warehouse
Orchestrating data pipelines using Airflow
Analyzed effect of new store openings and promotions on consumer behavior.
Using Sklearn pipeline,prediction of daily sales in various stores up to 6 weeks ahead of time.
Build Streamlit dashboard to communicate results with employees
Merged machine learning with causal inference using the Causal Nex Library.
I worked with the Wisconsin breast cancer data to infer the key factors that may influence breast cancer.
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