Hi, I'm Abhishek
Data Analyst
Welcome to my portfolio website! A passionate individual who always thrives to work on end to end products to provide meaningful insights & understand customer behavior to maximize the impact & maintain strong client relationships.
Contact meAbout Me
My introduction
I have worked as Data Analyst, During these experiences I have collaborated with the Clients & teams to transform business needs into actionable insights & used SQL queries to extract, clean, manipulate, transform data through ETL tool & create dynamic dashboards to find meaningful insights, KPI, metrices to stakeholders and maintain strong client relationships.
in data analytics
Skills
My technical levelProgramming Languages
SQL ( DBMS )
80%PYTHON / R
70%Java
60%C++
80%Analytics Skills
Data Anaysis & Cleaning
75%Data Visualization, Data Interpretation, Reporting,
75%Python(Numpy, Pandas), R, Machine Learning, statistics
50%Analytics Tools & Framework
SQL - Microsoft SQL SERVER(), MySQL, PostGreSQL, Oracle, Hadoop, BigData-Hive-spark
85%Visualisation - PowerBI, Tableau, Google Studio
80%Advanced Microsoft Excel for Analysis - Vlookup, Pivot, Formula, Macros/VBA, Data Cleaning
80%SOFT SKILLS
Work Focused, Adaptive, Good Communication, Storytelling, Presentation, Data-driven, Analytical, Results-oriented
90%Qualification / Education
My Education journeyClass 10th
ARMY PUBLIC SCHOOL, BOLARUMSenior Secondary School
Class 11th & 12th
Army Public School BolarumHiger Secondary School
College
Vellore Institute Of TechnologyCompter Science(I.T.)
EXPERIENCES
My Most recent Experience & worked on different projects where creativity meets innovation
Data Analyst | KPMG
• Worked in Data warehousing technologies and methodologies with knowledge in programming language SQL & reporting tool Tableau with understanding in Unix shell scripting • Worked & Collaborated with Data Analysts team to understand requirements, clean, extract, transform, manipulate data from various sources & provide strategies to improved business & kept a track of key metrics. • Built, Created, Developed, published interactive & dynamic Tableau dashboards & reports to identified trends & patterns and understand & visualize distribution of transaction amounts core KPIs to made impact on business & provided meaningful insights from data to understand customer behavior.
ETHNUS | MERN STACK DEVELEPOR
• Created and launched initial websites using the MERN stack, optimizing and modernizing the design to enhance user friendliness by 30%. • Managed user inputted data across multiple platforms through MongoDB resulting in 12% faster load times. • Built robust backend systems with Node.js and Express.js, ensuring efficient server-side performance and smooth data flow. • Collaborated with cross-functional teams to identify and resolve technical challenges, adhering to agile development methodologies to ensure timely project delivery.
TAKEN MIND | DATA ANALYST INTERNSHIP
• Worked as Intern Trainee and learned how to clean & analyze the data features, which comes under exploratory data analysis & finally visualize using libraries & various others tools. • By using some python libraries such as NumPy for multidimensional array & NumPy for feature Engineering & Feature Selection used for data cleaning & analysis and seaborn, matplotlib for visualization. • Got some insights of data wrangling & analysis and how to follow any life-cycle of any data science project
ETHNUS | AMAZON AWS TECHNICAL ESSENTIALS & ARCHITECTURE INTERNSHIP
Tasks that I completed during the course of this internship: • Work directly on AWS Cloud environment • Hands-on AWS cloud Qwik labs & where I have performed : • Hands-on 2 mini-projects AWS Techincal Essentials Topics include : • Understand the different AWS compute, storage, network, database services i.e., EC2 (virtual server, connect cloud to O.S.), S3, EBS, EFS, Glacier, VPC, CloudFront, RDS, DynamoDB • Examine IAM service i.e., users, groups, and roles, policies Architecting on AWS Topics include : • Identify the design and architectural patterns • Compared structured query language (SQL) with NoSQL databases • Select compute, storage, database, and networking resources to improve performance • Best practices to eliminate suboptimal resources
Projects
Discover my projects, where creativity meets innovation
Real-time Progressive Financial Analysis
• Developed a real-time financial analysis tool that tracks, visualizes, and forecasts financial data, empowering users to make informed financial decisions. • Incorporated data analysis techniques, specializing in time series analysis, to deliver valuable insights, and interactive dashboard creation, driving financial success. • Dashboard Creation: Created, Built, Monitored visually appealing interactive dynamic dashboards & reports added filters to allow user to explore dara at various levels of granularity • Designed and implemented interactive data visualizations using dynamic charts and graphs to present financial trends clearly and intuitively. • Implemented secure data management practices, safeguarding user data during storage and processing to ensure confidentiality and integrity. • Leveraged a robust tech stack, combining efficient front-end and back-end technologies to deliver a reliable and scalable application.
GitHub Repository See Live
WhatsApp Chat Analyzer
• This tool allows you to upload your WhatsApp chat history and get insightful analytics about your conversations. • The WhatsApp Chat Analyzer, built using Streamlit and Python, processes chat data with Pandas and Regex to provide comprehensive insights, including message statistics, timeline trends, activity maps, and word/emoji analysis. • Key algorithms involve data preprocessing and various analytical techniques to visualize and interpret chat dynamics.
GitHub Repository See Live
Virtual Mouse Using Hand Gesture Recognition
• Developed an innovative virtual mouse application using hand gesture recognition, enabling contactless control of a computer for enhanced convenience and hygiene. • Implemented real-time hand detection and tracking using the Mediapipe library, ensuring efficient and accurate gesture recognition. • Programmed customizable hand gestures to perform various mouse functions, including cursor movement, left/right clicks, and scrolling actions. • Achieved high accuracy in gesture recognition by leveraging machine learning models, enhancing usability and precision. • Built a platform-independent application, compatible with Windows, macOS, and Linux, providing accessibility across multiple operating systems. • Utilized a robust tech stack, including Python, OpenCV, Mediapipe, and PyAutoGUI, to deliver seamless functionality and a user-friendly experience.
GitHub Repository See Live
Path-Visualizer-using-DSA
• Designed an interactive web application to visualize pathfinding algorithms, aiding users in understanding their mechanics and efficiency. • Implemented multiple pathfinding algorithms, including Dijkstra's Algorithm, A* Search, Breadth-First Search (BFS), and Depth-First Search (DFS), for comprehensive educational demonstrations. • Developed an interactive grid system, allowing users to create obstacles, add weights, and set start and end points for customized visualizations. • Incorporated adjustable speed controls, enabling users to analyze algorithm performance step-by-step or in accelerated mode. • Built a responsive and user-friendly design, ensuring consistent functionality across various devices and screen sizes.
GitHub Repository See Live
COVID-19: Face Mask Detector
• Developed a detection Model with 92% accuracy in training & testing. It automatically detect whether a person is wearing a mask or not in real-time video streams. Process have 3 phases : loading dataset, training model & detecting features. OpenCV, Keras/TensorFlow, MobilNetV2 classifier, deep learning techniques & algorithm technologies used. • Used the highly efficient MobileNetV2 architecture & fine-tuned MobileNetV2 on our mask/no mask dataset and obtained a classifierthat is 97% accurate. • Extracted the face ROI & facial landmarks. And applied to the face by using the facial to compute & Determined the class label encoding based on probabilities associated with color annotation
GitHub Repository See Live