Numetric is a business intelligence platform that specializes in data analytics and visualization. It enables users to collect, analyze, and interpret large datasets to make informed decisions. The platform offers tools for data integration, dashboard creation, and reporting, making it easier for organizations to gain insights from their data.
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About Numetric
Numetric was founded in 2012 with the aim of simplifying data analytics and visualization for businesses. It provided tools to help organizations collect, analyze, and interpret large datasets efficiently. Over time, it evolved to offer comprehensive solutions for data integration, dashboard creation, and reporting. The platform gained traction for its user-friendly interface and robust analytical capabilities.
Strengths of Numetric included its user-friendly interface, robust data integration capabilities, and powerful visualization tools. Weaknesses involved limited customization options and scalability issues for very large datasets. Competitors included Tableau, Power BI, and QlikView, which offered similar data analytics and visualization solutions.
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How to hire a Numetric expert
A Numetric expert must have skills in data analytics, SQL for querying databases, and proficiency in data visualization techniques. They should also be adept at using Numetric's specific tools for dashboard creation and reporting. Knowledge of data integration processes and experience with handling large datasets are essential.
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Juscimara G.
Data Scientist
Skills
PyTorch Video
Numetric
Forecast
Seafile
Bio
Hire JuscimaraThis candidate possesses a robust academic foundation in Computer Science, complemented by a Master's degree and ongoing doctoral studies in the same field. With extensive experience in Data Science projects concentrated on Machine Learning applications, they have demonstrated proficiency in a wide array of tools including pandas, numpy, scipy, matplotlib, seaborn, sklearn, pytorch, and various AutoML frameworks such as H2O and TPOT. Current roles include leading AI initiatives focused on vulnerability analysis in information systems and conducting research on imbalanced regression problems. Previous engagements encompass collaborative research on time series and machine learning for renewable energy generation forecasting, as well as academic positions teaching critical computer science subjects, reflecting a strong blend of practical and theoretical expertise.
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