Anudeep

Data Analyst

Hyderabad, India 4+ yrs exp 89 · Excellent

About

Results-driven Data Analyst with 4+ years of experience in Data Analytics, Business Intelligence, Reporting Automation, Dashboard Development, and Business Analytics. Experienced in collecting, cleaning, analyzing, and interpreting large datasets to support strategic business decisions. Proficient in SQL, Python, Power BI, Tableau, and Advanced Excel, with expertise in developing interactive dashboards, automating reports, KPI tracking, statistical analysis, data modeling, and ETL concepts. Skilled at collaborating with cross-functional teams, ensuring data quality, identifying trends, and delivering actionable insights that improve operational efficiency and business performance. Familiar with cloud platforms (AWS, Azure, GCP) and data warehousing concepts.

Skills & Expertise (53)

Data Visualization Advanced

8.3/10

Years Exp

SQL Advanced

8.2/10

Years Exp

Python Advanced

8.0/10

Years Exp

Pandas Advanced

8.0/10

Years Exp

Data Analysis Advanced

8.0/10

Years Exp

Data Storytelling Intermediate

7.8/10

Years Exp

Tableau Intermediate

7.5/10

Years Exp

ETL Concepts Intermediate

7.5/10

Years Exp

AWS Intermediate

6.5/10

Years Exp

Google Cloud Platform Intermediate

6.5/10

Years Exp

Azure Data Cleansing Data Warehousing concepts Data Modeling Problem Solving BigQuery Jupyter Notebook Git REST APIs Postman Jira Business Reporting Report Automation KPI development Data Quality Management Stakeholder Management Business Requirement Gathering Cross-Functional Collaboration Process Improvement Documentation Forecasting NumPy Matplotlib Microsoft Power BI Microsoft Excel Power Query DAX Dashboard Development KPI Reporting Business Analytics Statistical Analysis Trend Analysis Data Validation Root Cause Analysis Customer Analytics Sales Analytics Marketing Analytics Operations Analytics SQL Server MySql Postgresql Data Integration Data Transformation

Work Experience

Data Analyst

DataQ Software India Pvt. Ltd.

Mar 2022 - Present

Collected, cleaned, transformed, and analyzed structured and unstructured data from multiple business systems to support strategic business decisions. Wrote advanced SQL queries using joins, subqueries, CTEs, window functions, views, and aggregate functions for reporting and data analysis. Developed and maintained interactive Power BI dashboards and automated reports for Sales, Marketing, Operations, Finance, and Management teams. Designed KPI dashboards to monitor revenue, sales performance, operational efficiency, customer behavior, productivity, and business growth. Performed exploratory data analysis (EDA), statistical analysis, and trend analysis to identify business opportunities and operational bottlenecks. Built reusable data models and optimized Power BI datasets using DAX and Power Query for improved report performance. Automated recurring reporting processes using SQL, Python, Power BI, and Excel, significantly reducing manual effort. Performed data validation, reconciliation, and quality checks to ensure reporting accuracy and consistency across multiple data sources. Assisted in ETL processes involving data extraction, transformation, integration, and loading for reporting purposes. Used Python (Pandas & NumPy) for data preparation, automation, cleansing, and analytical workflows. Collaborated with business stakeholders to gather reporting requirements and deliver scalable analytical solutions. Prepared ad-hoc reports, business presentations, and executive summaries to support leadership decision-making. Documented analytical processes, KPI definitions, reporting logic, and business rules for knowledge sharing and governance. Worked closely with cross-functional teams to improve reporting efficiency and business intelligence capabilities. Improved Power BI dashboard performance by 30% through optimized DAX calculations and efficient data modeling. Reduced SQL query execution time by 25% using indexing strategies, CTE optimization, and query tuning. Automated recurring reporting processes, saving 10+ hours per month in manual reporting effort. Improved reporting accuracy by implementing automated validation and reconciliation processes. Delivered interactive executive dashboards that enabled faster, data-driven business decisions across multiple departments.