- Location
- Vancouver, British Columbia, Canada
- Bio
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I am a Statistics student at the University of British Columbia (UBC) with a solid foundation in Mechanical Engineering, which has equipped me with a unique blend of analytical and problem-solving skills. Currently, I am actively contributing to the data analytics field as a Data Analyst, where I specialize in harnessing the power of data through Python, R, and SQL. My expertise extends to data visualization, where I excel in crafting compelling insights using tools like Tableau and Power BI.
In addition to my technical proficiencies, I am certified by Microsoft, underscoring my commitment to staying on the cutting edge of technology and ensuring intensive exposure to Azure AI. However, my journey in data analytics is more than just a profession; it's a passion. I'm an enthusiastic AI/ML aficionado, continually seeking opportunities to bridge the gap between data science and machine learning. This enthusiasm has driven me to work on a variety of data analytics projects, allowing me to apply my skills in real-world scenarios. I earned the LeetCode 30 Days of Pandas badge by solving thirty problems covering six essential classes of data operations, including data filtering, string methods, data manipulation, statistics, data aggregation, and data integration. Throughout the journey, I tackled challenging problems in both Pandas and SQL schemas, honing my skills and gaining invaluable insights into data analysis.
One of my significant projects involved conducting a comprehensive market analysis for the automotive industry, utilizing advanced data analytics techniques to identify market trends, consumer behavior, and competitive landscapes. This analysis contributed to data-driven strategies resulting in a 15% increase in market share for the client, who implemented our recommendations, leading to substantial revenue growth. I've also had the opportunity to collaborate with cross-functional teams to optimize business processes. One such project involved streamlining inventory management for a retail company, where my data analytics solutions led to a 20% reduction in carrying costs and a 10% increase in order fulfillment efficiency. I have dealt with bike-sharing data, where I applied basic data preprocessing, regression modeling, exploratory data analysis, and visualization techniques to extract insights and generate meaningful visualizations. This project not only deepened my understanding of data science but also reinforced the importance of data quality and its impact on analysis outcomes.
My diverse background, from engineering to statistics, empowers me to approach challenges with a multidisciplinary perspective. I thrive on leveraging my skill set to tackle complex problems and translate data into actionable solutions. Whether it's enhancing business intelligence, conducting market research, or delving into the intricacies of AI and ML, I'm driven by the transformative potential of data.
I'm excited about the limitless possibilities in the data-driven world and look forward to contributing my expertise, analytical mindset, and unquenchable thirst for AI and ML advancements to any team or project. Let's explore the data-driven future together. - Resume
- Farhana_Resume.pdf
- Portals
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Vancouver, British Columbia, Canada
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- Categories
- Data visualization Data analysis Data modelling Machine learning Data science
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Achievements
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Recent projects
Data Analytics and Visualization Project
The goal of this project is to create a dashboard template using EHASE/ifdha business intelligence software( New data visualization platform similar to Power Bi and Tableau) This will involve several different steps for the students, including: - Analyzing existing datasets and understanding the data structure. - Developing a dashboard template for various business/client use cases using EHASE/IFDHA business intelligence platform/web portal using data analysis and visualization software. - Optimizing software runtime performance and assessing areas for improvement. - Research other variables that can improve the quality of the dashboard. - Testing the developed data visualization templates and making improvements based on additional data.
Data Centralization and Dashboard Creation for Nonny Beer
The main goal for the project is to create a database and dashboard that centralizes data from different platforms like Stripe, Shopify, and wholesale ordering platforms. This will allow Nonny Beer to pull correct data points such as total sales per account, active account list, velocity of product sales per account, and last reorder date by account. This will involve several different steps for the learners, including: - Analyzing the data stored across different platforms. - Designing and creating a database to centralize the data. - Developing a dashboard to visualize the centralized data. - Testing the database and dashboard for accuracy and efficiency. - Implementing security measures to protect the centralized data.