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OLAMIDE100/README.md

Hello👋🏾. Thank you for visiting my profile 👩🏾‍💻

As a Data/DataOps/Cloud-Intensive Engineer, my expertise lies in recognizing, choosing, and creating effective data systems and pipelines. These systems enable smooth and secure data flow throughout all processes, empowering data-driven decision-making.

Throughout my career, I have successfully overseen data management and business analytics tools tailored to meet the specific needs and challenges of the company. By integrating these tools with data warehouses, I have ensured efficient organization and accessibility of information.

My professional journey has been marked by involvement in projects that converge data science, data analytics, and data engineering. Notably, I have designed and maintained prediction systems that unveil hidden insights and offer valuable solutions to drive the company's growth and stability.

In pursuit of excellence, I leverage cloud technologies such as GCP and AWS, alongside DevOps best practices, for all my data projects. My proficiency in troubleshooting allows me to swiftly identify and implement solutions, ensuring timely project delivery.

My Skills include 👨‍💻





Apache Spark

Find me around the web 🌎:

     


OLAMIDE100       OLAMIDE100

Pinned

  1. Data-Engineering-Project Data-Engineering-Project Public

    This Project summarizes the data set of Tweets related to the forth coming 2023 general election in Nigeria targeted at the two leading presidential aspirants in the country

    Python 5

  2. Customer-Segmentation-RMF-Analysis Customer-Segmentation-RMF-Analysis Public

    The objective of this study is to optimally cluster the customer data to get a clear view of various customers, develop customized marketing campaigns, choose specific product features for deployme…

    Jupyter Notebook

  3. Pangaea-Shipment-Tasks Pangaea-Shipment-Tasks Public

    Jupyter Notebook

  4. Ecommerce Ecommerce Public

    JavaScript

  5. Prediction-of-Client-Compliant-Category Prediction-of-Client-Compliant-Category Public

    This data set has 312912 rows and 14 columns. for our Prediction we worked with just two columns, which are the issue columns later renamed to Consumer_complaint_narrative as the text features and …

    Jupyter Notebook

  6. Auto_Deployment_Project Auto_Deployment_Project Public

    TypeScript