SAIANJANIREDDY ENUGALA

Results-driven Automation Test Engineer with a Bachelor's in Electronics and Communication Engineering and a Master's in Computer Science, bringing 10 months of hands-on experience. Proficient in SQL and data validation, demonstrating a strong foundation in data analysis, visualization, and business intelligence tools through various projects. Committed to leveraging technical expertise to transition into a Data Analyst role and enhance data-driven decision-making processes.

• [AWS Certified Cloud Practitioner] [Amazon Web Services Training and Certification] [2024]

Sales Performance Analysis

Objective: Analyze sales data to identify trends, high-performing regions, and product performance.
Tools: SQL, Python (Pandas, Matplotlib), Microsoft Power BI
Highlights: 

• Extracted and cleaned sales data from multiple sources (CSV, SQL databases).
• Created interactive dashboards to visualize KPIs such as monthly sales, revenue, and customer segmentation.
• Delivered actionable insights, such as recommending regions for targeted marketing campaigns.

Movie Database Analysis

Objective: Analyze a movie database to extract insights about genres, ratings, and revenue.
Tasks: Write SQL queries to find the most popular genres based on average ratings and box office revenue.

• Identify directors with the most movies in each genre.
• Calculate the average revenue and ratings per year.

Highlights: 

• Show advanced SQL skills like GROUP BY, JOIN, CASE, and window functions (RANK, ROW_NUMBER).

Employee Performance Dashboard

Objective: Track employee productivity and performance metrics across departments.
Tools/Skills: SQL, Power BI/Tableau, Excel.
Highlights: 

• Wrote SQL queries to calculate metrics like project completion rates, average task duration, and team productivity.
• Created a dashboard showing performance by department and individual employees.
• Identified underperforming areas and suggested actionable improvements.

E-Commerce Product Analysis

Objective: Analyze product performance to identify top-selling products and categories.
Tools/Skills: SQL (AWS Redshift), AWS QuickSight, AWS S3.
Highlights: 

• Loaded large datasets into AWS Redshift for efficient querying and analysis.
• Performed SQL queries to find top-selling products, underperforming categories, and seasonal trends.
• Created dashboards in AWS QuickSight to visualize sales trends and share insights with stakeholders.