Results-driven Data Analyst with over 5 years of experience in analyzing and interpreting complex data to deliver actionable business insights. Proficient in SQL, Python, Excel, Tableau, and Power BI, with extensive expertise in statistical modeling, data visualization, and predictive analytics. Proven ability to identify trends, optimize operational processes, and support decision-making across cross-functional teams. Skilled in managing large datasets, utilizing advanced Excel functions (VLOOKUP, INDEX MATCH, etc.), and integrating diverse data sources into analytical tools and reporting systems. Experienced in developing and optimizing SQL queries (DDL & DML) for efficient data retrieval and manipulation from large-scale relational databases. Adept at integrating multiple data sources into platforms like Domo to provide strategic recommendations that align with business objectives.
Programming Languages: Python, R, SQL, PL/SQL, HTML, UNIX Shell Scripting, VB Script
Integrated Development Environments (IDEs): Google Colab, Anaconda, Jupyter Notebook
Data Analytics & Visualization Tools: Tableau, Power BI, Domo, Excel (Pivot Tables, VLOOKUP, INDEX MATCH, Advanced Functions)
Libraries & Packages: NumPy, Pandas, Matplotlib, SciPy, Seaborn, Scikit-learn
ETL Tools: SSIS, Informatica, Azure Data Factory, Data Stage, Talend, Data Profiling, Data Cleaning, Data Warehousing
Databases: MySQL, SQL Server, Oracle, DB2, Teradata, NoSQL
Cloud Platforms: AWS (S3, Redshift), Azure (Data Factory, SQL Database, Data Explorer)
Data Engineering Tools: Snowflake, Apache Airflow, SAP, MS Visio, Erwin, Git, GitHub, Jira
Machine Learning Techniques: Linear Regression, Logistic Regression, Random Forest, K-Means, XGBoost, Neural Networks
Methodologies: SDLC, Agile, Scrum, CI/CD
Big Data Tools: Azure Data Explorer, Power BI, Looker