Data-Driven Data Analyst with over 3+ years of experience specializing in data analytics, visualization, and predictive modelling. Expert in SQL, Python, Power BI, and Tableau, with a proven track record of optimizing data workflows, reducing processing time by 20%, and driving strategic decision-making. I am skilled in working with big data tools like Databricks and Apache Spark, as well as cloud platforms such as AWS. Adept at collaborating across business units to transform data insights into impactful business outcomes. I am passionate about solving complex data challenges and committed to advancing data-driven solutions.
● Spearheaded ETL pipeline automation, cutting reporting delays by 25% through Alteryx and SQL.
● Developed Power BI dashboards that enhanced KPI tracking and decision-making speed by 20%.
Developed and maintained ETL workflows using SSIS to automate data extraction, transformation, and loading from multiple source systems into SQL Server.
● Partnered with infrastructure teams to optimize AWS-based storage,reducing costs by 15% while scaling data accessibility.
● Integrated Hive with Hadoop ecosystem tools like HDFS, MapReduce, Pig, and Spark.
Developed and optimized T-SQL stored procedures, triggers, and user-defined functions in SQL Server.
Implemented error handling and transaction control in T-SQL to ensure data consistency and reliability.
Designed and implemented efficient ETL pipelines for large datasets, ensuring high data accuracy and integrity across production environments.
Assisted in grading assignments focused on statistical analysis and data modeling, providing detailed feedback that enhanced students’ comprehension of complex datasets and improved their academic performance by 20%.
Applied tools like SQL and Excel to teach practical data analysis techniques, leading lab sessions and one-on-one tutoring that increased student proficiency in handling real-world datasets.
Guided students in data cleaning and preprocessing, implementing best practices for managing missing values and outliers using python, resulting in a 30% improvement in data accuracy and reliability for analysis.
Automated business logic using T-SQL scripts for reporting, data transformation, and batch processing.
Used temporary tables, table variables, and CTEs to simplify complex queries in T-SQL.
Developed and maintained partitioned and bucketed Hive tables to improve query performance and manage big data efficiently.
Integrated datasets from multiple sources using Python and Power Query, saving 30% of reporting time.
Conducted statistical analyses that revealed insights, improving operational efficiency by 10%.
Tuned long-running T-SQL queries using execution plans and performance tuning techniques.
Integrated T-SQL scripts into SSIS packages for robust ETL workflows.
● Designed NLP models to process customer reviews, yielding actionable insights for product improvement.
● Designed and optimized complex HiveQL queries for ETL pipelines and data analysis tasks on
large datasets.
Performed data transformation tasks such as filtering, cleansing, deduplication, and applying business rules to support reporting and analytics.
Scheduled and monitored ETL jobs using SQL Server Agent, with proactive error handling and performance logging.
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