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Data Analyst Resume

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SUMMARY

  • 3+ years of Data Analyst experience.
  • Experience using MS Excel, SQL, and/or other applications to perform various types of analysis.
  • Skilled in Microsoft Access, PowerPoint, SQL Server, and various RDBMS.
  • Installation, testing, configuration, maintenance, and troubleshooting of all SQL Server components.
  • Experience with BI tools such as Tableau and PowerBI.
  • Proficient in Data Analysis, System Analysis, Business Requirement Gathering, and Data Warehousing concept.
  • Skilled in writing Business Requirement Documents (BRD), Use Cases, Functional Specifications; well versed with Use Case Diagrams, User stories, Process flow charts, and UML modeling tools such as MS Visio.
  • Expert in Agile Methodology of SDLC for implementing Business projects.
  • Experience with collaborative tools such as Rational Requisite Pro, Rational Team Concert (RTC), SharePoint, Clarity, and JIRA.
  • Knowledge of Power BI and Tableau to import and analyze data from various sources such as SQL Server.
  • Create various filters and parameters for reports using Tableau desktop.
  • Skilled in Microsoft Excel (e.g., formulas, pivot tables, graphing).
  • Experience in data migration tasks using T/SQL, SQL Loader.
  • Experience in Data Migration, Data Transformation, Data Conversion, and Data loading.

TECHNICAL SKILLS

  • T - SQL
  • PL-SQL
  • Excel
  • Access
  • Tableau
  • PowerBI
  • MicroStrategy
  • JIRA

PROFESSIONAL EXPERIENCE

Data Analyst

Confidential

Responsibilities:

  • Create and run queries as necessary for project deliverables using SQL
  • Work closely with the Risk, Team Leads, and stakeholder to come up with a plan to effectively find the correlation of at-risk enrollment behaviors.
  • Evaluate data pulled for accuracy and relation to data requests
  • The support leadership team in explaining and disseminating information to appropriate stakeholders
  • Develop statistical methods to evaluate and analyze numerical data using computer software, including MS Access, MS Excel, Oracle, SQL, and/or other applications, for assigned projects
  • Develop innovative analytical approaches and predictive modeling techniques for reactive or proactive data analysis, sampling, and study design
  • Develop trend reports to identify the potential program or systematic vulnerabilities
  • Provide expertise and guidance to unit and corporate staff as required.
  • Represents and participates in group or committee discussions.
  • Involve in designing and creating Tables, Views, complex Stored Procedures, and Indexes using T-SQL.
  • Improve query performance.
  • Data Profiling for accurate and better reporting and analysis.

Data Analyst

Confidential

Responsibilities:

  • Extracted, compiled, and tracked data, and analyzed data to generate reports
  • Participated with troubleshooting, and problem resolution efforts
  • Performed daily data manipulation using SQL and prepared reports on a weekly, monthly, and quarterly basis.
  • Used Excel functions to generate spreadsheets and pivot tables
  • Identified, analyze, and interpret trends or patterns in complex data sets
  • Cleansing and Blending multiple data sources to allow for different views on application data in a single dashboard
  • An aided team in data collection to be used for Tableau visuals
  • Conducted presentations to other lines of business as a meta role to show the value of Tableau as a BI tool
  • Perform data manipulation operations like import/export data from various external file formats using SQL
  • Generated a variety of business reports from SQL server using excel with a pivot table and pivot chart
  • Develop and implement databases, data collection systems, data analytics, and other strategies that optimize statistical efficiency and quality
  • Checked for invalid/out of range data
  • Perform data manipulation operations like import/export data from various external file formats using SSIS
  • Develop, update, and maintain current SQL programs
  • Develop and implement databases, data collection systems, data analytics, and other strategies that optimize statistical efficiency and quality
  • Acquire data from primary or secondary data sources and maintain databases/ data systems

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