Sql Server Data Analyst

Anusha Ratakonda Email Id: ***************@*****.***

Data Analyst & Data Migration Specialist Mobile: +1-330-***-**** https://www.linkedin.com/in/anusha-ratakonda

Professional Summary

• Highly skilled Data Analyst and Data Migration Specialist with over 7 years of experience in managing data migration, analytics, and reporting using a variety of technologies including Microsoft SQL Server, Azure Data Factory, Power BI, and Amazon Redshift.

• Proven expertise in designing and developing ETL processes using SQL Server Integration Services (SSIS), ensuring seamless data migration and integration from various sources to cloud-based environments like Salesforce and Azure.

• Strong background in utilizing Azure Data Factory (ADF) to automate and orchestrate data workflows, ensuring smooth data movement between on-premises and cloud environments while optimizing pipeline performance.

• Experienced in creating advanced Power BI dashboards and reports, utilizing DAX and Power Query for data modeling and optimization, delivering actionable business insights to support data-driven decision-making.

• Proficient in managing and optimizing SQL queries using T-SQL and SQL Server Management Studio (SSMS), ensuring high performance and the accuracy of data stored in SQL Server and Azure SQL Databases.

• Adept at leveraging SQL Server Analysis Services (SSAS) to design OLAP cubes and enhance business intelligence reporting, providing stakeholders with in-depth analytical capabilities.

• Experienced in performing data cleansing and validation using Azure Data Quality Services, ensuring data integrity and consistency across systems during migration processes.

• Knowledgeable in cloud-based database solutions such as Azure SQL Database and Amazon Redshift, providing scalable and secure data storage for business-critical applications and improving data accessibility.

• Expertise in version control and collaborative development environments using Git and Azure DevOps, streamlining team collaboration and ensuring smooth project deployments and rollback capabilities.

• Strong background in statistical analysis and predictive modeling using Python and R, developing data models to drive business forecasting and improve operational efficiency. Technical Skills

Database Management Microsoft SQL Server, Amazon Redshift, Azure SQL Database Data Integration & ETL SQL Server Integration Services (SSIS), Azure Data Factory (ADF), T-SQL, SQL Profiler

Data Warehousing SQL Server Analysis Services (SSAS), OLAP Cubes Business Intelligence Power BI, DAX, Power Query

Version Control Git, Azure DevOps

Programming Languages Python, R

Data Cleansing Azure Data Quality Services

Reporting & Analytics SQL Server Reporting Services (SSRS), Power BI Dashboards and Reports Cloud Technologies Azure SQL Database, Azure Data Factory, Azure DevOps, Amazon Redshift Collaboration Tools Git, Azure DevOps, Visual Studio Professional Experience

Client: Marriot Vacation Club Jul 2024 – Present

Dallas, TX

Role: Data Migration Specialist

Responsibilities:

● Managed data extraction, transformation, and loading (ETL) processes using Microsoft SQL Server, SQL Server Management Studio (SSMS), and T-SQL, ensuring seamless migration of large datasets from legacy systems into target systems like Salesforce.

● Designed and developed complex SQL Server Integration Services (SSIS) packages to automate data workflows, improving the efficiency of data migrations and integrations across various data sources.

● Utilized SQL Server Analysis Services (SSAS) to design and implement OLAP cubes, enabling advanced analytics and reporting capabilities for business intelligence.

● Developed and deployed SQL Server Reporting Services (SSRS) reports to generate actionable insights for stakeholders, helping teams make data-driven decisions during and after migration projects.

● Leveraged Azure Data Factory (ADF) to create and manage scalable data pipelines for data migration, monitoring, and orchestrating workflows across multiple cloud and on-premises environments.

● Implemented Azure SQL Database solutions for scalable cloud storage, ensuring efficient data migration, processing, and storage of structured data during Salesforce migrations.

● Used Azure Data Quality Services to perform data cleansing, ensuring data integrity and consistency before, during, and after the migration process, aligning with business requirements.

● Developed Power BI dashboards and reports to provide data visualization of key metrics and migration progress, helping stakeholders understand the impact and success of the migration process.

● Applied DAX and Power Query to optimize data models and query performance within Power BI, ensuring efficient processing of large datasets and streamlined reporting.

● Automated and managed data integration workflows using Azure Data Factory, coordinating data movement between on-premises systems, cloud storage, and Salesforce to ensure seamless migration and synchronization of business-critical data.

Environment: Microsoft SQL Server, SQL Server Management Studio (SSMS), T-SQL, SQL Server Integration Services

(SSIS), SQL Server Analysis Services (SSAS), SQL Server Reporting Services (SSRS), Azure Data Factory, Azure SQL Database, Azure Data Quality Services, Power BI, DAX, Power Query, Azure Data factory Amazon Dec 2018 – Dec 2022

Hyderabad, India

Role: Data Analyst

Responsibilities:

● Analyzed and processed large datasets using Amazon Redshift, AWS Glue, and SQL to ensure efficient querying, reporting, and database management.

● Designed and optimized ETL processes with AWS Glue and Lambda to automate data workflows and integrate data into centralized databases.

● Utilized Amazon Quick Sight to create interactive dashboards, providing actionable insights and visualizing key performance indicators (KPIs).

● Orchestrated data pipelines using AWS Data Pipeline, automating data movement between on-premises and cloud environments.

● Conducted performance tuning and troubleshooting of SQL queries using Amazon Redshift Spectrum to improve query execution efficiency and resolve bottlenecks.

● Managed version control of SQL scripts and data models using AWS CodeCommit to ensure collaboration, versioning, and rollback capabilities across teams.

● Developed scalable cloud-based storage solutions using Amazon S3 and AWS RDS to ensure data integrity, security, and high availability.

● Implemented CI/CD pipelines using AWS CodePipeline to automate deployment processes and ensure seamless integration and delivery.

● Implemented data analytics models and algorithms using Python, R, and SageMaker, providing predictive analytics to improve business processes.

● Collaborated with cross-functional teams to define data requirements, optimize workflows, and ensure data models aligned with business needs.

● Automated data processing and reporting tasks with Python and R, reducing manual effort and improving processing efficiency and accuracy.

● Developed data visualizations and reports using Amazon QuickSight, delivering interactive dashboards to track business metrics.

● Provided ad-hoc reports and data extracts based on user requests, ensuring accurate and timely delivery of data.

● Conducted gap analysis on current data extract processes, identifying inefficiencies and proposing improvements for smoother data integration.

● Supported the development of Key Performance Indicator (KPI) Collection Tools and Reports, assisting in performance monitoring and decision-making.

● Produced business and system documentation consistent with Amazon's standards, ensuring transparency, accuracy, and compliance.

Environment: Amazon Redshift, AWS Glue, AWS Lambda, AWS Data Pipeline, Amazon QuickSight, Amazon S3, AWS RDS, SageMaker, Python, R, AWS CodeCommit, AWS CodePipeline, Visual Studio Code, SQL Profiler. Pulp Jan 2017 – Dec 2018

Hyderabad, India

Role: Data Analyst

Responsibilities:

● Utilized Microsoft SQL Server and Amazon Redshift to manage and analyze large datasets, performing complex queries and data transformations to support business intelligence and reporting needs.

● Developed and optimized SQL queries and scripts using SQL to extract, transform, and load (ETL) data, ensuring seamless integration from multiple data sources into centralized repositories.

● Created interactive Power BI dashboards and reports to visualize key business metrics, providing stakeholders with real-time insights to drive data-informed decision-making.

● Employed DAX in Power BI to create complex measures, calculated columns, and KPIs for advanced analytics and dynamic reporting.

● Managed and maintained database environments and queries using SQL Server Management Studio (SSMS), ensuring smooth performance, regular optimizations, and quick issue resolution.

● Collaborated with development and operations teams using Git for version control, managing SQL scripts and reports, and ensuring efficient team collaboration and deployment processes.

● Integrated data pipelines and automated workflows streamlining the deployment of analytics solutions and ensuring version consistency across various environments.

● Conducted data validation and quality checks to ensure accuracy and consistency, resolving any discrepancies and ensuring the integrity of the data used in reporting and analytics.

● Worked closely with business stakeholders to gather requirements, define data needs, and translate business objectives into actionable data models and visualizations.

● Continuously monitored and optimized SQL queries and Power BI reports, improving performance and ensuring that end-users had timely access to reliable and accurate data. Environment: Microsoft SQL Server, Amazon Redshift, SQL, Power BI, DAX, SQL Server Management Studio (SSMS), Git, Azure DevOps.

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