Maitreyi Das

Project Description: Data Integration and Analytics for Automotive and Industrial Replacement Parts

Role: Data Analyst

• Project Objective: To streamline and enhance data management processes for global automotive and industrial replacement parts company
• Project involved integrating data from legacy system (Informatica Power Center) into modern cloud-based platform (Google Cloud Platform) for efficient analysis and decision-making

Key Responsibilities:

Data Migration and Integration: Seamlessly transferred data from Informatica Power Center to IICS

• Implemented robust data integration pipelines using IICS to ensure data accuracy and consistency
• Mapped and transformed data to align with GCP's data model and standards

Data Analysis and Quality Assurance: Conducted thorough data analysis using IICS to identify any anomalies, inconsistencies, or potential data quality issues

• Implemented data cleansing and validation procedures to maintain data integrity
• Ensured that data migration process preserved original business logic and rules

Cloud Platform Integration: Successfully integrated customer data into Google Cloud Platform (GCP) for scalable and efficient data storage and processing

• Leveraged BigQuery's advanced analytics capabilities to extract valuable insights from data

Project Description: Developed a comprehensive attendance tracking system to monitor employee attendance accurately, aligning with company policies and holiday calendars

• System utilized hybrid approach, combining rule-based and data-driven techniques

Role: Data Analyst/SQL Developer

Project Objectives: Create a flexible and scalable attendance tracking system

• Ensure accurate and timely attendance data
• Provide insightful visualizations to track employee and manager attendance

Key Responsibilities:

• Designed and implemented SQL-based data pipeline to extract and transform attendance data from various sources
• Utilized advanced SQL techniques, including window functions, stored procedures, and stored functions, to efficiently process and analyze large datasets
• Developed hybrid attendance model that incorporates both rule-based and data-driven components to accurately calculate attendance
• Created user-friendly PowerBI dashboard to visualize key metrics, such as employee attendance rates, trends, and exceptions
• Collaborated with business stakeholders to understand their requirements and ensure system met their needs
• Provided ongoing maintenance and support to system

PERSONAL PROJECT
•Bi_Dashboard: Analyzed ecommerce sales data created interactive dashboard to track and analyze online sales data, used complex parameters to drill down in worksheet and customization using filters and slicers, used different types of customized visualization (bar chart, pie chart, donut chart, clustered bar chart, scatter chart, line chart, area chart, map, slicers etc.)
•Advance Excel: Analyzed Coffee Shop Sales and Healthcare data using Excel and advanced Excel concepts. In this project, I analyzed and created a dashboard using Power Query, Data Model, Measures, Pivot Charts, and Slicers etc.
•SMS Spam Detection Application: Develop a model to accurately classify SMS messages as spam or ham.
Approach:
o Data Collection and Preprocessing: Gather and clean SMS data.
o Feature Extraction: Extract relevant features from text data.
o Model Development: Train machine learning (e.g., Naive Bayes, SVM, Random Forest) and deep learning (e.g., RNN, LSTM, CNN) models.
o Model Evaluation: Assess model performance using metrics like accuracy, precision, recall, and F1-score.
o Deployment: Create a web application to integrate the model.
Skills: Python, Machine Learning, Deep Learning, NLP, Web/Mobile Development