Data Analyst Analysis

MEGHANA AGIRISHETTY

Data Analyst

Location: AL

Phone: 334-***-**** Email: *********************@*****.*** LinkedIn SUMMARY

Around 3 years of hands-on experience as a Data Analyst, analyzing and interpreting complex datasets to derive valuable insights for business decision-making.

Proficient in Python, R, and SQL, adept at utilizing these languages to perform various data analysis and manipulation tasks.

Demonstrated expertise in leveraging powerful libraries such as NumPy, Pandas, Matplotlib, SciPy, ggplot2, and Dplyr within Python and R environments for in-depth data analysis, visualization, and manipulation tasks.

Skilled in visualizing data effectively using tools like Tableau, Power BI, Microsoft Excel, and Google Analytics, enabling stakeholders to gain insights at a glance.

Experienced in working with various databases including MySQL, SQL Server, and PostgreSQL, ensuring data integrity and accessibility for analysis purposes.

Familiar with cloud technologies such as AWS and Azure, proficient in leveraging cloud services for scalable and secure data solutions.

Well-versed in Agile, Waterfall, and SDLC methodologies, ensuring efficient project management and delivery of analytical solutions.

Experienced in data cleaning, wrangling, and warehousing, ensuring data quality and integrity throughout the analytics process. Well-versed in data governance practices to maintain compliance and standardization.

Proficient in data mining and A/B testing methodologies, coupled with strong critical thinking abilities.

Skilled in effectively communicating insights through presentations, utilizing problem-solving skills to drive data-driven decision- making processes.

PROFESSIONAL EXPERIENCE

Auburn University at Montgomery Jul 2023-May 2024

The Center for Disability Services

CDS Note-Taker/ Data Analyst

Worked as CDS note-taker for the course cloud computing and Big Data Analysis where in a program has capacity of 50 students and the other has a capacity of 25.

I planned and organized course work and collect information related to the subject by working hands on experiments and gave notes.

Helped the students to complete their project work in their respective technologies like AWS, Azure, HTML5, CSS3, Angular JS, MySQL, and Mongo DB.

Leveraged Python programming language, alongside advanced libraries like NumPy and Pandas, to conduct comprehensive data analysis and manipulation, facilitating precise extraction of insights from complex datasets.

Employed ggplot2 and Dplyr in R to create visually compelling data visualizations and perform seamless data wrangling tasks, ensuring data integrity and facilitating insightful decision-making processes.

Engineered visually immersive dashboards and reports using Power BI and Microsoft Excel, employing intricate charting techniques and interactive features to present intricate findings and trends cogently to stakeholders, thereby facilitating informed decision-making processes.

Orchestrated the management of PostgreSQL databases, meticulously ensuring data integrity, security, and accessibility for analysis, while concurrently optimizing database performance to fortify efficient data retrieval and manipulation operations.

Developed and implemented Azure Databricks and Azure Data Lake Storage solutions to establish robust data processing pipelines, facilitating efficient integration, storage, and analysis of diverse data types.

Actively engaged within Agile/Scrum methodologies, actively participating in sprint planning, stand-ups, and retrospectives to ensure the punctual delivery of data analysis projects, aligned meticulously with business priorities and stakeholder requisites.

Conducted comprehensive data mining activities to unveil latent patterns and insights within expansive datasets, thereby furnishing stakeholders with invaluable insights crucial for informed decision-making and strategic formulation.

Orchestrated and executed meticulous A/B testing experiments to scrutinize the efficacy of various business strategies and initiatives, providing stakeholders with actionable insights for refinement and optimization purposes.

Championed the implementation of data warehousing and governance frameworks, ensuring the standardization, reliability, and accessibility of organizational data assets, thereby fostering precision and consistency in analytical outputs across multifarious departments.

Trigent Software, India Feb 2020-Jul 2022

Data Analyst

Leveraged Python and SQL to develop custom data processing scripts, automating data extraction, transformation, and loading

(ETL) tasks, enhancing efficiency and accuracy in data analysis workflows.

Employed NumPy and Pandas libraries for data manipulation tasks, such as cleaning, merging, and transforming datasets, ensuring data integrity and accuracy.

Integrated Matplotlib and SciPy to create insightful visualizations and statistical analysis reports, providing stakeholders with actionable insights into key business metrics and trends.

Utilized Tableau to perform data blending, seamlessly integrating data from multiple sources to create comprehensive datasets for analysis, and ensuring a holistic view of business metrics.

Executed optimized SQL queries to retrieve specific data sets efficiently, utilizing indexing and query optimization techniques to enhance database performance for faster data retrieval.

Created dynamic and informative charts in Excel to visually represent complex data trends and patterns, aiding stakeholders in understanding key insights at a glance.

Developed Pivot tables to summarize and analyze large datasets, providing actionable insights for business decision-making and strategic planning.

Employed AWS services such as EC2 and S3 for scalable and secure data storage, facilitating efficient access and retrieval of large datasets for analysis.

Implemented AWS Lambda functions to automate data processing tasks, reducing manual effort and increasing operational efficiency.

Collaborated within Agile methodologies to prioritize and execute data analysis tasks, ensuring alignment with business objectives and timely project delivery.

Conducted thorough data cleaning and wrangling processes to preprocess raw data, addressing missing values and outliers to enhance the quality and reliability of analysis results.

Applied data mining techniques to uncover patterns and trends in customer behavior, product performance, and market trends, informing strategic decision-making processes.

Designed and executed A/B testing experiments to evaluate the effectiveness of marketing campaigns and initiatives, driving data-driven optimization efforts.

Demonstrated strong communication and presentation skills, effectively communicating analytical findings and recommendations to stakeholders in clear and concise manner.

TECHNICAL SKILLS

Programming Language: Python, R, SQL

Packages: NumPy, Pandas, Matplotlib, SciPy, ggplot2, Dplyr Visualization Tools: Tableau, Power BI, Microsoft Excel, Google Analytics Databases: MySQL, SQL Server, PostgreSQL

Cloud Technologies: AWS(EC2, S3, IAM), Azure

Methodologies: SDLC, Agile, Waterfall

Other Skills: Data Cleaning, Data Wrangling, Data Warehousing, Data Governance, Data mining, A/B Testing, Critical Thinking, Communication Skills, Presentation Skills, Problem-Solving IDEs: Visual Studio Code, PyCharm

EDUCATION

Master of Science in Computer Science Aug 2022 – May 2024 Auburn University at Montgomery

PROJECTS

Predictive Modeling for Customer Churn

Analyzed telecommunications data to identify churn factors, employing logistic regression and decision tree algorithms for accurate predictions.

Visualized insights with Tableau, aiding stakeholders in enhancing customer retention strategies. Sales Forecasting using Time Series Analysis

Analyzed historical sales data using ARIMA and Prophet models for accurate sales forecasts.

Created interactive dashboards in Power BI to facilitate data-driven sales planning. Interactive Sales Dashboard Development

Designed and developed an interactive sales dashboard in Tableau to visualize key performance indicators (KPIs) for a retail company.

Enabled real-time data exploration and trend analysis, facilitating strategic decision-making for sales teams.

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