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Business Data Analyst Resume

SUMMARY:

With 5+ years of experience in field of Business/Data analysis, ETL Development, Data Modeling, and Project Management. Strong experience in Data Profiling, Big data, Data Migration, Data Conversion, Data Quality and Data Integration. Experience in Visualizing and Analyzing data to find the pattern with Statistical Analysis (Regression modelling) and bring logical results and conclusion. Expertize in communicating complex technical data outcomes to non - technical audience. Expertise in Data Science Methodology, Data Analysis with Python, Database and SQL for Data science, Python for Data science and AI, Data Visualization with Python & Machine Learning with python.

TECHNICAL SKILLS:

Programming language: Python, C

Databases: MySQL, MS Access, PostgreSQL, Oracle SQL

Tools: JMP, Minitab, MS Excel, VBA, MS office suite, Visio, AutoCAD, Tableau, SAS, Power BI, Juptyer Notebook, Sublime Editor, SQL, Spot fire, Qlik, SAP Predictive Analysis, Micro Strategy, Machine learning libraries.

WORK EXPERIENCE:

Business Data Analyst

Confidential

Responsibilities:

  • Collaborated with clients to gather project requirements, establish scope of project, create technical specification documents (S.O.P), process mapping in Visio to make understanding of desired functionality.
  • Analyzed the existing data, improved the future state facility layout that would increase productivity, reduce scrap rate and increase their on-time delivery rate by at-least 36% across five different plant locations in US effecting around 2000 employees.
  • Designed, developed and maintained daily, weekly and monthly reports that provide company leadership with information used in decision-making process for various projects.
  • Developed and Automated on-demand Business Intelligence dashboard and ad-hoc reporting for visibility into cost and performance metrics, monitoring KPIs in Power BI, Excel.
  • Updated and manipulated content and files by using python scripts.
  • Analyzed historic data, executed a project that reduced the processing time in manufacturing plant from 36 hours to 24 hours by implementing DMAIC and lean techniques, resulting in obtaining $ 518,400 annual savings.
  • Developed a Statistical Multiple linear Regression model to forecast the demand precise to a daily, hourly level in each day around the southwest region of US serving 20,000 customers resulting in a 25% increase in sales and saving around $452,350 over a period of a year.
  • Designed relational data model to represent relationships between entities of order management system, normalized the schema design and created tables and integrity constraints using Microsoft SQL Server, increasing the forecast capability to 15%.
  • Achieved 50% performance improvement by database tuning initiatives including query optimization, indexing and creation of query execution plans.
  • Leveraged SQL Server Integration Services (SSIS) tool of SQL Server to populate data from various data sources, creating packages for different data loading operations for application.
  • Initiated the project in creating and scheduling SQL Server Integration Services (SSIS) packages and visualizing the big raw datasets for business improvements, saved a tedious data entry problem, and validated datasets containing 10M+ records of financial, employee data.
  • Worked on Spark SQL and Data frames for faster execution of Hive queries using Spark Sql Context.
  • Worked directly with stakeholders, data science, marketing, Engineering, product managers to develop new analytics solutions, identifying new data useful for analytics projects and support analytics best practices.
  • Conducted profit and loss analysis, A/B Hypothesis testing and optimized spending on operational activities by 17%.
  • Used multiple transformations including Fuzzy lookups and Fuzzy grouping in the data cleansing process.

Environment: Agile, Data Analysis, Data profiling, logical data model, LEAN methodology, SQL, TOAD, MS Office Suite (Word, Excel, Access, Power Point, Spark, Outlook),PL/SQL, Python, Oracle, SQL and Windows.

Business Data Analyst

Confidential, Houston

Responsibilities:

  • Standardized scorecards and modified data queries enabling project managers to effectively analyze vendor lead times.
  • Coordinated with project managers for benchmarking various parameters required to monitor vendor performance.
  • Analyzed data from Oracle database, Excel - VBA, Tableau to create vendor reports detailing performance measures.
  • Analyzing various logs that are been generating and predicting/forecasting next occurrence of event with various Python libraries.
  • Used Python scripts to update content in the database and manipulate files.
  • Implemented standard vendor performance report to be accessible to all project managers and vendors
  • Reduced data server load by 61% and time spent by project managers to generate vendor reports by 80%
  • Wrote clear, concise detailed system requirements specification (SRS) documents and user documentation in accordance to guidelines and standards of a level where developers can interpret, design and develop the application with minimum guidance.
  • Responsible for data analysis, project plan, gap analysis, mapping, all business analysis functions/artifacts, documentation and implementation.
  • Performed data profiling and analysis applied various data cleansing rules designed data standards and architecture/designed the relational models.

Environment: logical data model, agile methodology, Excel, Python, Word, PowerPoint and MS Project, UAT, Agile, MS Visio, TOAD, SWOT analysis, ETL, SQL, Windows.

Business Data Analyst

Confidential

Responsibilities:

  • Recommended multiple cost-saving solutions for battery making processes by analyzing category-based data in SQL and Tableau, thus reducing cost by 8%
  • Developed Supplier process for Contract Manufacturers, Performed Supplier Performance and Risk Assessment considering cost, delivery, quality, and specifications and presented data to Executives.
  • Analyzed the data to identify areas for improvement that would increase the number of continuous improvement projects and optimized spending saving around 21% costs within the company.
  • Introduced statistical quality control in the company by establishing proper control charts for inspection process increasing the ongoing project performance by 15%
  • Used python APIs for extracting daily data from multiple vendors.
  • Performed Gap analysis by identifying existing technologies, documenting the enhancements to meet the end state requirements.
  • Working with Apache Spark for batch and interactive processing
  • Performed exploratory data analysis like calculation of descriptive statistics, detection of outliers, assumptions testing, factor analysis, etc., in Python
  • Preparation of test data required for build and executing test cases in SIT and UAT environments before and after releases.
  • Designed and developed Use Cases, Activity Diagrams, Sequence Diagrams, OOD using UML.
  • Assisted with user testing of systems (UAT), developing and maintaining quality procedures, and ensuring that appropriate documentation is in place.
  • Wrote SQL scripts in TOAD for Oracle and Teradata SQL Assistant for Teradata.
  • Conducted data analysis in order to map data from source system to the target system and validated whether the data is correctly written in the target tables by using SQL queries.
  • Managed business requirements in Rational Requisite Pro while making them available to all team members.
  • Examined, analyzed and modeled test plans, test scripts, test procedures and use case scenarios based on RUP methodology.

Environment: logical data model, agile methodology, Excel, Python, Spark, Word, PowerPoint and MS Project, UAT, Ms. Visio, TOAD, SWOT analysis, ETL, SQL, Windows.

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