Results-driven data analyst with 5 years of experience in digital marketing. I am passionate about utilizing my strong analytical skills and data-driven mindset to extract valuable insights and optimize digital strategies for improved performance. Proficient in data analysis and visualization tools such as Excel and Power BI, Tableau. I possess a solid understanding of statistical analysis techniques and methodologies. With expertise in Python, SQL, and database management, I have experience in data mining, data wrangling, exploratory data analysis, data cleansing, and applying statistical and machine learning techniques. Strong communicator with excellent problem-solving abilities and a collaborative Skills: * Data Analysis and Visualization: Excel, Power BI, Google Analytics, Data Studio * Power Bi DAX Functions * Statistical Analysis: Regression, Clustering, Decision Trees * Programming: Python (pandas), SQL Database Management * Data Mining, Data Cleansing, and Data Visualization. * Google Analytics and Google Ads * Machine Learning Techniques * Data Modelling with Jupyter Notebook and vs code * Problem-solving and Critical Thinking * Strong Communication and Presentation Skills * Business Analysis with Data Interpretation. * Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy * 5 years of Digital analytics experience with GA4 implementation and attractive visualizations with Data Studio Reports. * Strong knowledge of data engineering concepts, ETL principles, and data integration patterns. * Proficiency in SQL and experience with query optimization and performance tuning. * Experience with data modeling, schema design, and data warehousing concepts. Certifications: Great Learning Data Science Certification SQL Basic SQL Intermediate Google Analytics Certification * Projects: 1. Power Bi: Email Attachment Analysis with Power Query in Power BI (May 2023): Analyzed email attachment data, cleaned and processed it, and created visually appealing Power BI reports without opening the email. 2. Python: Exploratory Data Analysis on IPL Dataset 3. Machine Learning: Train the dataset using a Linear Regression model Analyzed cars dataset for selecting optimal dependent and independent features from a large dataset and calculated the model's efficiency using Linear Regression, ridge regression, and Decision Tree Algorithm. * Publications: 1. "Spam Email Filtering Techniques" 2. "Large Scales Spam Emails Filtering with MapReduce-based SVM"