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Hi, I'm Kartikay.
I'm currently pursuing an MBA in FinTech and enjoy working with data. I help businesses organize, analyze, and visualize data using Excel, Power BI, and Python. I like building dashboards, automating repetitive tasks, and creating reports that are simple to understand. I'm always willing to learn and deliver quality work on time!
English
MBA FinTech Student Chandigarh University
Ghaziabad,
- By Narayan Biswas
attended Class IX-X Tuition
"He is very committed in his work. He is very patient in making me understand the subject well. His commitment towards teaching and his attitude of responsibility has impressed me. "
Reply by Divesh
Thanks, Shriyash, I would really happy if my teaching would help you to crack the UPSC exam.
"Which is the best UPSC coaching institute in Kolkata?" in Exam Coaching/UPSC Exams Coaching, Exam Coaching/UPSC Exams Coaching/IAS (Indian Administrative Service) Coaching
Join ALS Online class in Kolkata.


Full time course of B. Com and training done of advanced Excel. I am working last 4 years as a freelancer and getting satisfactory result from Client.

Data Analyst with 4+ years of experience in MIS, data analysis, and business reporting. Skilled in SQL, Python, Power BI, Excel, and Power Automate, with expertise in data cleaning, dashboard development, and workflow automation. Passionate about transforming raw data into actionable insights that support data-driven business decisions

Professional Journey and Full-Time Experience: In my full-time role as a Lead Data Analyst with a major electrical utility company, I oversee complex analytics projects that drive operational efficiency, strategic planning, and data-driven innovation. I partner with cross-functional teams to define requirements, architect data solutions, and deliver key performance dashboards. My day-to-day responsibilities combine hands-on technical work with mentoring junior analysts, coordinating with business stakeholders, and managing end-to-end project lifecycles. Freelance Data Analyst, Trainer, and Consultant: Parallel to my corporate role, I operate as a freelance data analyst and trainer. My freelance engagements include: • Student Training: I deliver hands-on training in Excel, Power BI, Tableau, SQL, and Python, crafting curricula that blend fundamental concepts with advanced applications. • Custom Projects: As a freelancer, I tackle analytics projects for businesses and individual clients. These include building bespoke dashboards, creating training datasets, implementing automated reporting systems, optimizing database queries, and developing machine learning prototypes.

I am a seasoned Data Analyst and Researcher with over 10 years of experience in gathering, organizing, and interpreting data to support strategic decision making. My core strength lies in making sense of complex information through thorough research, logical analysis, and clear communication. Over the years, I’ve worked across diverse sectors to identify trends, extract key insights, and deliver well structured reports that support business growth, policy development, and operational improvements. I specialize in converting raw data into meaningful narratives that inform and influence. Highly detail oriented and driven by curiosity, I excel at identifying the right data sources, asking the right questions, and drawing conclusions that matter. Whether it’s analyzing survey results, evaluating business performance, or studying market patterns, I bring clarity and value through deep, non technical analysis.

Higher Qualification: Master's Degree in Statistics and Computer Science from Pondicherry Central University with an aggregate of 87% Work Experience: Role: Data Analyst Company: Artificial Penetration Software Solutions, Hyderabad Duration: January 2019 – December 2021 Conduct Data Mining, Data Modelling, Statistical Analysis, Business Intelligence gathering, trending, and Forecasting. Data analytics supports decisions for high-priority, enterprise initiatives involving IT/product development, customer service improvement, organizational realignment, and process reengineering. Used quantitative data gathered to develop an understanding of customer behaviour, demographics, and lifecycle. Presented data that helped guide decisions of the Organization. Perform qualitative and quantitative analysis to support day-to-day decision making and support reporting and analytics, such as KPIs, Financial reports, and create interactive dashboards for better analysis using Power BI or Tableau Used Machine Learning and Statistical Modelling techniques to develop and evaluate algorithms to improve performance, quality, data management, accuracy and making predictions Project : Title: Magic Straw Restaurant Sales Analysis and Revenue Prediction Role: Data Analyst Technologies: Excel, Power BI, Python, Machine Learning Description: The Basic idea of Magic Straw restaurants analysis is to get a fair idea about the factors affecting the establishment of different types of restaurants at different places in Hyderabad and aggregate rating and Revenue of each restaurant. This dataset contains details (including ingredients), images and reviews of 241 ice cream flavours & COMBO thick shakes across the city. There are a total of 21,674 reviews, with each review containing star ratings and text. Responsibilities / Accomplishments: • Data Mining and Modelling: Collected, cleansed, and provided modelling and analyses of structured and • unstructured data used for major business initiatives. Outcomes: — A 15% reduction in transportation costs, resulting in annual savings. — Improved demand forecasting that reduced backorders to retail partners by 17%. — Completed Revenue Analysis and BI research that helped boost NW region sales by 15%. Dashboards: Created visually impactful reports /dashboards in Power BI for data reporting and data analysis by using pivot tables and VLOOKUP. Extracted, interpreted, and analysed data to identify key metrics and transform raw data into meaningful, actionable information. eCommerce: Designed and built Machine Learning analysis models on large data sets that helped increase online sales (up to 15% per product) and lowered the Orders-Cancellation rate by 23%.