4+ years of experience as a Data Analyst with an understanding of Data Modeling, Evaluating Data Sources, and understanding of Data Warehouse/Data Mart Design, and Client/Server applications. Good Knowledge of the Softwa…
4+ years of experience as a Data Analyst with an understanding of Data Modeling, Evaluating Data Sources, and understanding of Data Warehouse/Data Mart Design, and Client/Server applications. Good Knowledge of the Software Development Life Cycle (SDLC), Agile, and Waterfall Methodologies. Understanding of different python IDEs such as Visual Studio Code and Jupyter Notebook. Working knowledge of Python and R libraries such as NumPy, Pandas, Matplotlib, SciPy, and ggplot2. Proficient in designing stunning visualizations using Tableau and Power BI software and publishing and presenting dashboards, and Storyline on web and desktop platforms. Knowledge of various Relational Database Management Systems (RDBMS) such as MySQL and SQL Server. Capable of all phases of data mining, data collection, data cleaning, developing models, validation, and visualization.
Implemented the Agilemodelthroughout the application development lifecycle, enabling iterative progress, continuousfeedback, and faster timeto-market; successfully delivered a feature-rich application that met customer needs and boosted revenue by 15%.
Employed ggplot2 in R Studio to create visually compelling scatter plots and high-low graphs, facilitating the exploration and understanding of
complex data relationships, thereby informing data-driven decision-making processes.
Developed and implemented a highly intuitive manager dashboard in Tableau, enabling real-time analysis of call centermetrics and KPIs; increased
team performance by 22% through data-driven decision-making.
Enhanced data-driven decision making by implementing Excel PowerPivot for querying and analyzing test data; customized end-user requests,
resulting in a 40% reduction in error rates and data accuracy
Executed comprehensive data analysis on MS SQL database, extracting and mapping data from source to target schemas, resulting in a 25%
reduction in data errors and enhanced accuracy of reporting metrics.
Understanding of Data Modelling, Data Collection,Data Cleansing, Data Warehouse, and Client/Server applications.
Implemented the Agile model throughout the application development lifecycle, enabling iterative progress, continuous feedback, and faster time-to-market; successfully delivered a feature-rich application that met customer needs and boosted revenue by 15%.
Employed ggplot2 in R Studio to create visually compelling scatter plots and high-low graphs, facilitating the exploration and understanding of complex data relationships, thereby informing data-driven decision-making processes.
Developed and implemented a highly intuitive manager dashboard in Tableau, enabling real-time analysis of call center metrics and KPIs; increased team performance by 22% through data-driven decision-making.
Enhanced data-driven decision making by implementing Excel PowerPivot for querying and analyzing test data; customized end-user requests, resulting in a 40% reduction in error rates and data accuracy
Executed comprehensive data analysis on MS SQL database, extracting and mapping data from source to target schemas, resulting in a 25% reduction in data errors and enhanced accuracy of reporting metrics.
Understanding of Data Modelling, Data Collection, Data Cleansing, Data Warehouse, and Client/Server applications.
Spearheaded the utilization of the Waterfall Methodology to drive the successful delivery of a software project; produced meticulous artifacts throughout the SDLC, resulting in project visibility and stakeholder alignment.
Created custom SQL scripts to automate data pulls for business analysis, reducing manual effort by 80% and freeing up 15+ hours per week for strategic analysis and project implementation.
Executed data quality monitoring reports, enabling proactive identification and resolution of data issues, reducing data errors by 30% and ensuring reliable and trustworthy data for business operations.
Directed end-to-end data lifecycle management, covering data collection, cleaning, wrangling, analysis, and machine learning model development using R and Python. Instrumental in achieving a significant 25% increase in customer retention rate through the implementation of targeted marketing campaigns driven by predictive modeling.
Conducted comprehensive data analysis, profiling, and assessment using Python and libraries SciPy, NumPy, and Pandas; identified and resolved data discrepancies, ensuring accuracy and quality of datasets.
Applied Power BI analytics to optimize supply chain management; reduced inventory holding costs by 25% and improved fulfillment accuracy by 30% through real-time inventory tracking and demand forecasting.
Optimized data analysis and profiling through the utilization of advanced SQL queries on various source systems, including SQL Server; performed data cleansing techniques, resulting in a 30% improvement in data accuracy and enhanced decision-making processes.
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