Data Analyst Power Bi

ANIL KUMAR GANGINENI

Phone no:+1-203-***-**** Email ID: ********************@*****.***

PROFESSIONAL SUMMARY

Results-driven Data Analyst with 7+ years of experience in data visualization, statistical analysis, and transforming complex datasets into actionable insights. Seeking to leverage expertise in SQL, Python, Tableau, and Power BI to drive data-informed decision-making, optimize processes, and contribute to the success of a dynamic organization. TECHNICAL SKILLS

Data Analysis & Visualization: Tableau, Power BI, QlikView, Excel (Advanced), Google Data Studio

Programming Languages: Python (Pandas, NumPy, Matplotlib, Seaborn), R

Databases: SQL (MySQL, PostgreSQL, Oracle, SQL Server), NoSQL (MongoDB, Cassandra)

ETL Tools: Alteryx, Informatica, Talend, SSIS, AWS Glue

Big Data Technologies: Hadoop, Apache Spark, Hive, Pig, HDFS

Cloud Platforms: AWS (Redshift, S3, Glue, Athena), Azure (Data Factory, Synapse Analytics), GCP (Big Query, Dataflow)

Machine Learning & Statistical Tools: Scikit-learn, TensorFlow, Keras, XGBoost, R (caret, ggplot2)

Data Warehousing: Snowflake, Amazon Redshift, Google Big Query

Data Integration & Streaming: Apache Kafka, AWS Kinesis

Version Control & Collaboration: Git, GitHub, JIRA, Confluence

Data Cleaning & Transformation: Python (Pandas), Alteryx, Excel (Power Query), Open Refine

Scripting & Automation: Bash, PowerShell

Business Intelligence: Google Analytics, Excel (PivotTables, Macros), SAS

API Integration: REST APIs, JSON, XML, Postman

WORK HISTORY

Role: Data Analyst

Client: M&T Bank - Bridgeport, CT, USA Mar 2024 - Present Description: M&T Bank is a U.S.-based financial institution, offering a wide range of banking, investment, and financial services for individuals, businesses, and commercial clients. Analyzed complex data sets and developed data models, dashboards, and automated pipelines using SQL, Python, Power BI, and Tableau to drive data-driven insights.

Responsibilities:

Utilize Power BI and Tableau to create visually appealing and interactive dashboards and reports for key stakeholders across various departments and develop automated processes for regular reporting and data transformation using Python and SQL, enhancing reporting efficiency.

Support data integration efforts by managing and transforming data using ETL tools such as Informatica and Apache NiFi, ensuring smooth data flow across systems and Analyse historical data trends and provide predictive models using machine learning algorithms with R or Python to drive data-driven decision-making.

Optimize and automate data pipelines using Apache Spark and Hadoop to process large volumes of structured and unstructured data efficiently for better business insights and implement and maintain data warehousing solutions using Amazon Redshift and Snowflake for scalable and reliable data storage, enhancing reporting and analysis capabilities.

Build and maintain real-time data streaming pipelines using Apache Kafka or AWS Kinesis to process and analyse live data streams for immediate decision-making and Leverage Docker and Kubernetes to containerize and deploy data applications, ensuring scalable and efficient operations.

Implement CI/CD pipelines for automated testing, deployment, and monitoring of data applications using Jenkins, improving workflow efficiency and Implement machine learning models using frameworks like TensorFlow or Scikit-learn to predict trends and business outcomes, optimizing operational strategies.

Perform data migration and transformation using Apache Airflow for orchestrating complex workflows in cloud environments, streamlining processes.

Develop and maintain interactive and visually engaging dashboards and reports using Tableau, Power BI, and Looker, enabling data-driven decision-making across departments.

Design and implement scalable data warehousing solutions using Snowflake to optimize storage, improve query performance, and enable seamless integration with cloud-based analytics tools. ENVIRONMENT: SQL, Power BI, Tableau, Python, SQL, Informatica, Apache NiFi, Apache Spark, Hadoop, Amazon Redshift, Snowflake, Oracle, APIs, GraphQL, NumPy, Pandas, SciPy, Apache Kafka, AWS Kinesis, Docker, Kubernetes, CI/CD pipelines, Jenkins, TensorFlow, Scikit-learn, Apache Airflow, Tableau, Power BI. Role: Data Analyst

Synchrony - Stamford, CT, USA Mar 2023 – Feb 2024

Description: Synchrony is a leading consumer financial services company that specializes in providing credit solutions for retail partners, healthcare providers, and consumers. Developed and implemented ETL processes, data pipelines, and interactive dashboards using SQL Server, Azure Data Factory, Power BI, and Python to drive data-driven insights and improve healthcare analytics.

Responsibilities:

Develop and implement ETL processes to cleanse, transform, and load data into various data storage systems using tools like SQL Server and Azure Data Factory.

Design and create interactive dashboards and reports for stakeholders using Power BI and Tableau to visualize key healthcare metrics and Utilize Machine Learning models to identify trends and forecast future outcomes, applying R and Python libraries like scikit-learn and TensorFlow.

Extract and manipulate data from different sources such as SQL databases, NoSQL databases, and cloud platforms like Azure, performing data mining and statistical analysis using R and Python, including techniques such as regression analysis, clustering, and classification and Leverage Hadoop and Spark for handling large-scale healthcare data sets, enabling efficient data processing and analysis for improved decision-making.

Work with NoSQL databases like MongoDB and Cassandra for storing and querying unstructured healthcare data.

Implement and optimize data warehousing solutions in Azure Synapse Analytics and Google Big Query for faster reporting and analysis, improving data accessibility and build automated reports and dashboards using PowerShell and Python scripts to streamline regular reporting processes and enhance operational efficiency.

Integrate data from external sources such as third-party healthcare APIs into internal systems, ensuring seamless data flow and enabling comprehensive analysis and Use Jupyter Notebooks and Azure Notebooks to document, visualize, and share analysis findings with stakeholders, ensuring transparency and collaboration.

Create and automate data quality checks using Apache Airflow to monitor and validate healthcare data processes, ensuring accuracy and reliability and manage and monitor CI/CD pipelines for data integration and deployment using Jenkins and GitLab, optimizing workflow automation and deployment efficiency.

Conduct data profiling and validation using Talend and Alteryx to ensure the accuracy and completeness of healthcare data before analysis.

ENVIRONMENT: SQL, Python, Azure, Power BI, Tableau, scikit-learn, TensorFlow, R, Python, NoSQL databases, PowerShell, Jupyter Notebooks, Apache Airflow, CI/CD pipelines, Jenkins, GitLab, Apache Kafka, Talend, Alteryx, spaCy.

Role: Data Analyst

Zelis – Hyderabad, INDIA Jan 2020 – Nov 2022

Description: Zelis is a healthcare technology company that offers innovative payment and cost management solutions for healthcare providers, payers, and consumers. Identified and handled the missing data, outliers, inconsistencies, and duplicates to ensure data quality and Performing data transformations and standardizing data formats for analysis.

Responsibilities:

Collect, extract, and integrate data from multiple healthcare management systems, databases, and external sources using SQL, Python, and APIs to streamline analysis and reporting for health insurance claims, policies, and customer data.

Cleanse, validate, and transform healthcare data to ensure accuracy and consistency using Python (Pandas, NumPy), R, and SQL, ensuring compliance with health insurance regulations and industry standards.

Develop and maintain financial and healthcare data models to support decision-making processes and premium pricing strategies using R, Python, and SAS.

Design and generate standard health insurance reports, dashboards, and visualizations using Tableau, Power BI, and Excel, enabling stakeholders to monitor claims, customer trends, and policy performance in real-time.

Design and maintain automated ETL (Extract, Transform, Load) pipelines to integrate diverse healthcare data sources with Apache Airflow, Talend, and AWS Glue, ensuring seamless data flow across systems.

Perform risk analysis and predictive modelling for health insurance claims, customer retention, and fraud detection using statistical techniques and machine learning frameworks like Scikit-learn, TensorFlow, and Keras.

Ensure adherence to regulatory standards and financial compliance requirements, automating regulatory reporting processes with Python and BI tools such as Power BI and Tableau.

Integrate disparate healthcare data sources (claims, policies, and customer information) into cohesive datasets for financial and actuarial analysis using Informatica, SSIS, and Talend. Design and optimize data warehousing solutions using Snowflake to store large healthcare datasets, ensuring scalability, high-performance querying, and data integrity.

Leverage Looker to create interactive dashboards and reports, enabling real-time analysis of insurance claims, customer demographics, and healthcare costs.

ENVIRONMENT: Python, Pandas, NumPy, R, SQL, APIs, Tableau, Power BI, Excel, Apache Airflow, Talend, AWS Glue, Scikit-learn, TensorFlow, Keras, Tableau, Informatica, SSIS, Hadoop, Snowflake, Looker Role: Data Analyst

Amgen – Hyderabad, INDIA Jun 2017- Dec 2019

Description: Amgen is a global biotechnology company committed to discovering, developing, and delivering innovative therapies for serious illnesses. Involved in managing and organizing data sets from database management systems and Finding patterns and trends in data analysis and designing, creating and maintaining relevant and useful databases and data systems.

Responsibilities:

Utilize SQL for querying large pharmaceutical datasets, Python or R for statistical analysis and data processing, and Excel for managing clinical trial data and inventory tracking.

Develop dynamic and insightful dashboards and reports using tools like Tableau, Power BI, or QlikView to visualize key metrics related to drug development, sales performance, and market trends.

Monitor and optimize pharmaceutical data workflows with ETL tools like Informatica, Talend, and Alteryx to streamline data extraction, transformation, and loading processes across various systems.

Leverage big data technologies such as Hadoop and Spark for processing large-scale pharmaceutical datasets, including clinical trial data and production analytics, ensuring efficient analysis of big data.

Integrate and deploy machine learning models using frameworks like TensorFlow and scikit-learn for predictive analytics, such as forecasting drug demand, patient outcomes, and risk assessments and Utilize NoSQL databases like MongoDB or Cassandra for managing unstructured healthcare data, including patient records, medical research.

Work with Docker and Kubernetes for deploying scalable data analytics solutions in a containerized environment, ensuring the efficient processing of pharmaceutical data.

Design and implement data warehousing solutions using Redshift, Snowflake, or Google Big Query to consolidate and manage large datasets for research, clinical trials, and drug manufacturing processes.

Manage version control of pharmaceutical data and projects using Git, GitHub, or GitLab to enable efficient collaboration among cross-functional teams and track changes in complex datasets.

Perform real-time analytics using streaming platforms like Apache Kafka, AWS Kinesis, or Google Pub/Sub to monitor pharmaceutical operations, drug supply chains, and patient monitoring systems. ENVIRONMENT: Python, R, Tableau, Power BI, QlikView, Informatica, Talend, Alteryx, Hadoop, Spark, TensorFlow, scikit-learn, MongoDB, Cassandra, Docker, Kubernetes, Git, GitHub, GitLab, Apache Kafka, AWS Kinesis, Google Pub/Sub. EDUCATION

Masters: computer information system

New England college, New Hampshire, USA

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