Fiza Loladiya

Data Analyst

[email protected]

Hello, I am

Fiza Loladiya.

2

Excel
Projects

6

PowerBI
Projects

4

SQL
Projects

About Me

I’m Fiza — the kind of data analyst who doesn’t start with charts. I start with a question: what decision needs to be made, and what information would actually change it? That mindset drives everything I build.

I use Excel, SQL, and Power BI to turn raw, messy data into clear insights teams can act on. In Excel, I clean and structure data, build reliable reporting workflows, and analyze trends using smart formulas and PivotTables. In SQL, I extract and shape data with joins, CTEs, and window functions to answer real business questions. In Power BI, I create interactive dashboards with strong modeling, DAX measures, and visuals that communicate the story fast—without noise.

What sets me apart is the mix of analysis, communication, and design thinking. I care about the details because details change decisions: KPI definitions, layout, drill paths, and the way a dashboard guides attention. My goal is simple: make insights obvious, reliable, and decision-ready.

Key Skills

Excel

Power BI

SQL

Data Cleaning

Data Visualization

Dashboard Building

Power Query

DAX (Power BI)

Data Modeling

Data Analysis

Statistics

My Projects

Call Center Performance Dashboard (Excel)

Domain/Function: Call Center Analytics / Customer Support Operations

Sales & Finance Reporting Dashboard (Excel) – AtliQ Hardware

Domain/Function: Business Reporting / Sales & Finance Analytics

Employee Attrition Insights: HR Analytics Dashboard

Domain/Function: Human Resources Analytics

Electric Vehicle Market Analysis Dashboard

Domain/Function: Automotive Industry Analytics

E-Commerce Sales Dashboard (Power BI | MS SQL Server)

Domain/Function: Sales Analytics

Retail Sales Analysis (SQL Case Study)

Domain/Function: Retail Analytics

Monday Coffee Expansion Analysis (SQL)

Domain/Function: Market Expansion Strategy

Mentor–User Performance Analysis (SQL)

Domain/Function: Learning Platform Analytics

Library Management System (PostgreSQL SQL Project)

Domain/Function: Database Design / Backend Systems + Reporting Analytics

Bank Loan Portfolio Analysis Dashboard

Domain/Function: Banking & Finance Analytics (Loan Portfolio / Credit Risk)

Call Center Performance Dashboard

Domain/Function: Customer Service Analytics / Operations Analytics

Pizza Sales Report Dashboard

Domain/Function: Food & Beverage / Sales Analytics

My Experience

📘Excel Course Content & Project Intern (Remote) | Coding Liquids | Nov 2025 – Dec 2025

Researched and shortlisted topics for an Excel course to create a clear, structured learning path.
Edited and refined the course curriculum to improve flow, clarity, and progression for learners.
Planned lectures and aligned them with practical learning outcomes and project-based practice.
Built project resources including Start/Complete Excel workbooks, datasets, and README documentation.
Organized course materials systematically to ensure learners could follow along and apply concepts easily.

Tools/Skills: Excel, Curriculum Design, Content Research, Documentation (README), Dataset Preparation, Attention to Detail

📊Data Analyst Intern | AtliQ Technologies | Jan 2026 (4 Weeks)

Performed data cleaning to handle missing values, inconsistencies, and formatting issues, improving dataset quality by ~10–20%.
Conducted data validation checks to ensure accuracy and completeness, reducing reporting errors by ~10–15%.
Created structured reports and KPI summaries, improving reporting efficiency by ~40–60% through standardized templates and reusable outputs.
Supported client handling tasks in the Insurance domain, aligning reporting requirements with business needs and improving turnaround time by ~15–25%.
Maintained clear documentation of workflows and updates to support smooth collaboration and tracking.

Tools/Skills: Data Cleaning, Data Validation, Reporting, KPI Tracking, Insurance Domain, Communication, Attention to Detail

Awards & Certificate

Excel: Mother of Business Intelligence

Get Job Ready: Power BI Data Analytics for All Levels 3.0

SQL Beginner to Advanced For Data Professionals

Data Analytics Bootcamp 5.0: Job Placement Support + AI Automation & Data Engineering Basics

Coding Liquids – Excel Data Analysis Consultant Intern

AtliQ Technologies — Letter of Experience (Virtual Internship) | Data Analyst Intern

Let's Connect

Feel free to get in touch with me. I am always open to discussing new projects, creative ideas or opportunities to be part of your visions.

Mail Me

[email protected]

https://www.linkedin.com/in/fiza-loladiya

GitHub

https://github.com/fiza-loladiya

Excel Project

Call Center Performance Dashboard (Excel)

Domain/Function: Call Center Analytics / Customer Support Operations

Designed an interactive Excel dashboard to track call center KPIs, agent performance, abandoned calls, and customer behavior. Includes monthly trends, reason-wise failure analysis, and agent-level drilldowns using slicers.

View Project
Engagement

View Project
on GitHUB

Main dashboard overview showing overall call center KPIs (total, successful, failed, abandoned), agent-wise call volume, call outcome rate, abandoned call reasons, product discussion (success vs failure), monthly trend, and state-wise call distribution.

Interactive drilldown view with Morning time filter and a different agent selected (MichaelPage). Shows how KPIs, call outcomes, abandoned call reasons, trends, and state-wise distribution update dynamically.

Project Details

Built a detailed, decision-ready Call Center Dashboard in Excel to summarize overall call performance, agent activities, and customer behavior. The dashboard highlights key KPIs (total calls, answered vs abandoned, success rate, avg handling time), compares agent-wise performance, and enables quick drilldowns with slicers/filters to view an individual agent’s outcomes, abandoned calls, products discussed, and customer locations. I also added monthly trend views to spot seasonality and a reason-wise breakdown to identify why calls were unsuccessful. Designed with a clean layout, consistent formatting, and interactive visuals so managers can review performance in seconds and take action fast.

Excel Project

Sales & Finance Reporting Dashboard (Excel) – AtliQ Hardware

Domain/Function: Business Reporting / Sales & Finance Analytics

Created Excel-based business reports to track Market Performance vs Target, P&L by Market, quarterly GM% trends, and customer net sales performance. Designed for quick comparison across years, markets, and regions using clean tables and KPI-focused views.

View Project
Engagement

View Project
on GitHUB

Market Performance vs Target report comparing 2019–2021 performance with target variance and % gap by country to quickly identify underperforming markets.

Customer-wise Net Sales Performance report for the India market showing 2019–2021 sales and 2021 vs 2020 growth %. Helps identify top customers, fast-growing accounts, and overall YoY performance trends.

Project Details

Built a set of Excel business reports for AtliQ Hardware to support sales and finance decision-making. The reports include Market Performance vs Target (year-wise comparison and target variance), a FY2021 P&L summary by market (Net Sales, COGS, Gross Margin and GM%), GM% trends by quarter across sub-zones for FY2019–FY2021, and customer-wise net sales performance for the India market. The reporting layout is designed to be management-friendly: easy to scan, consistent formatting, and focused on KPIs and variance analysis so performance gaps are visible quickly.

PowerBI Project

Employee Attrition Insights: HR Analytics Dashboard

Domain/Function: Human Resources Analytics

Built an interactive HR Analytics Dashboard in Power BI to analyze employee attrition trends, department-wise performance, age and gender distribution, and job satisfaction insights for better workforce decision-making.

View Project
Engagement

View Project
on GitHUB

Power BI HR Dashboard highlighting employee attrition trends, department analysis, age groups, gender distribution, education insights, and job satisfaction metrics.

Detailed analysis of department-wise attrition, age group distribution, education field trends, and gender-based attrition rates, providing deeper insights into workforce demographics and employee turnover patterns.

Project Details

This HR Analytics Dashboard was built using Power BI to analyze employee attrition patterns and workforce insights. The dashboard highlights key KPIs such as Total Employees, Attrition Count, Attrition Rate, Active Employees, and Average Age.

It provides department-wise attrition analysis, age group and gender distribution, education field insights, and job satisfaction ratings across different roles. Interactive visuals and slicers allow dynamic filtering for deeper analysis.

During this project, I worked on data cleaning, creating calculated columns and measures, designing meaningful KPIs, and selecting appropriate visuals for clear storytelling. The focus was to convert raw HR data into structured, decision-focused insights that can help HR teams reduce attrition and improve employee satisfaction.

Live Interactive Dashboard

PowerBI Project

Electric Vehicle Market Analysis Dashboard

Domain/Function: Automotive Industry Analytics

Interactive Power BI dashboard analyzing electric vehicle adoption trends, manufacturer dominance, state-wise distribution, CAFV eligibility, and growth patterns from 2010 onwards to support market and policy decision-making.

View Project
Engagement

View Project
on GitHUB

Overview of EV market KPIs including total vehicles, BEV vs PHEV distribution, growth trends from 2010, and state-wise adoption analysis.

In-depth analysis of EV adoption growth, regional penetration, brand leadership, and CAFV eligibility impact, highlighting market dominance and consumer preference trends.

Project Details

The Electric Vehicle (EV) industry is rapidly evolving due to environmental awareness, government incentives, and technological advancements. This project analyzes electric vehicle data to understand market growth, regional adoption patterns, and manufacturer dominance.

The dashboard provides key insights such as total vehicles, average electric range, BEV vs PHEV market share, state-wise distribution, and top manufacturers and models. A time-series analysis from 2010 onwards highlights the acceleration in EV adoption, especially after policy support and technological improvements.

CAFV eligibility analysis helps evaluate the role of clean fuel incentives in influencing adoption trends. Interactive filters allow users to explore EV performance by state, vehicle type, and manufacturer.

This project demonstrates my ability to transform raw automotive data into structured KPIs and visually engaging dashboards that support strategic decision-making.

Live Interactive Dashboard

PowerBI Project

E-Commerce Sales Dashboard (Power BI | MS SQL Server)

Domain/Function: Sales Analytics

Interactive Power BI dashboard to compare YTD vs PYTD and YoY trends for an e-commerce business. Quickly identifies category and region performance, product winners/losers, and shipping contribution to support faster decisions.

View Project
Engagement

View Project
on GitHUB

Other Tools

Power BI

DAX

Power Query

MS SQL SERVER

Data-modeling

Full dashboard overview showing KPI cards with sparklines and YoY %, category performance table, sales by state map, top/bottom products, region contribution, and shipping type breakdown. Designed as a one-screen performance summary.

This screenshot focuses on the detailed performance visuals: Top 5 Products by YTD Sales Bottom 5 Products by YTD Sales YTD Sales by Region YTD Sales by Shipping Type It is designed for quick product and operational insights.

Project Details

Designed a decision-focused E-Commerce Sales Dashboard that summarizes performance at a glance and supports drill-down analysis. The top KPI cards show YTD Sales, Profit, Quantity, and Profit Margin with YoY indicators and trend sparklines. Deeper sections break down results by category (YTD vs PYTD with YoY%), geography (state map and regional contribution), product performance (Top 5 and Bottom 5 by YTD sales), and shipping mix (share by shipping type). Segment buttons (Consumer/Corporate/Home Office) allow quick filtering to compare customer behavior. The dashboard helps stakeholders spot growth/decline drivers, prioritize products, and focus regional and operational improvements.

Live Interactive Dashboard

SQL Project

Retail Sales Analysis (SQL Case Study)

Domain/Function: Retail Analytics

Analyzed retail transaction data in MySQL: designed the sales table, cleaned missing values, performed EDA, and answered 10 business questions (revenue by category, top customers, peak months, shift-wise demand) using joins, CTEs, and window functions.

View Project
Engagement

View Project
on GitHUB

Other Tools

MySQL

GitHub

Case Study PDF

Project overview & objectives: defined the business context, primary goal, data foundation, and key deliverables for turning raw retail transactions into actionable insights using SQL.

Key dataset metrics summary: 1,987 transactions, total revenue 908.23k, 155 unique customers, across 3 product categories—used as the base for SQL-driven analysis and insights.

Project Details

Retail Sales Analysis using SQL (MySQL). I created the retail_sales table, explored the dataset, cleaned missing/invalid records, and performed EDA to understand sales performance and customer behavior. I answered key business questions such as: category-wise revenue and order volume, high-value transactions, best-selling month/year, top customers by total spend, and shift-wise demand (Morning/Afternoon/Evening). The project ends with insights and actionable recommendations to improve operations, staffing, and category strategy.

SQL Project

Monday Coffee Expansion Analysis (SQL)

Domain/Function: Market Expansion Strategy

SQL case study to recommend the best 3 Indian cities for Monday Coffee’s store expansion. Analyzed demand proxies, Q4 2023 revenue, product sales, customer penetration, rent vs sales (unit economics), and monthly growth using CTEs and window functions.

View Project
Engagement

View Project
on GitHUB

Other Tools

MySQL

CTEs

Window Functions

GitHub

Objectives: analyze Monday Coffee’s sales performance, customer demand, and city-level metrics to recommend the best 3 Indian cities for opening new coffee shops and ensuring profitable expansion.

Final recommendation: Pune, Delhi, and Jaipur. Chosen based on strong unit economics (low rent per customer), proven demand (high revenue/consumers), scalable customer base, and solid sales per customer for profitable store expansion.

Project Details

Monday Coffee plans to open 3 new stores in India. Using MySQL, I analyzed city-level demand and performance to shortlist the best expansion markets. I estimated coffee consumers as 25% of city population, evaluated Q4 2023 revenue by city, identified best-selling products, measured customer penetration, and calculated average sales per customer. To validate profitability, I compared average sales vs average rent per customer (unit economics), and tracked monthly growth using LAG. Finally, I combined market size, customers, sales, and rent to recommend the top 3 cities for expansion with clear business reasoning.

SQL Project

Mentor–User Performance Analysis (SQL)

Domain/Function: Learning Platform Analytics

Analyzed mentor/practice platform submissions using MySQL to track engagement and performance. Built activity + points leaderboard, daily/weekly top performers, accuracy profiles (correct vs incorrect), and DAU/submission trends using aggregations, CASE logic, and DENSE_RANK window functions.

View Project
Engagement

View Project
on GitHUB

Other Tools

MySQL

Window Functions

CTEs

GitHub

EDA validation checks: verified total submissions, unique users, date-range coverage, and missing/invalid values to ensure the leaderboard and trend analysis is accurate and not impacted by dirty or incomplete data.

Actionable recommendations from SQL insights: accuracy coaching for high-incorrect users, weekly rewards for top performers, track DAU vs submissions to spot friction early, and promote repeated winners into peer mentor roles.

Project Details

In this SQL mini project, I analyzed user submission data from a mentor/practice platform to understand engagement health and performance patterns. I performed EDA checks (submission count, unique users, date coverage, missing/invalid values) to avoid misleading results. Then I built an overall leaderboard (submissions + points), daily average points for consistency, daily top 3 users by correct submissions, top 5 users with most incorrect submissions, and weekly top 10 performers using YEARWEEK and DENSE_RANK. I also measured Daily Active Users (DAU) and total submissions to monitor platform “heartbeat,” and created correct vs incorrect accuracy profiles to identify strong performers vs struggling users. Finally, I translated insights into recommendations like accuracy coaching, weekly rewards, and engagement monitoring.

SQL Project

Library Management System (PostgreSQL SQL Project)

Domain/Function: Database Design / Backend Systems + Reporting Analytics

Built a mini real-world library backend in PostgreSQL: designed a normalized schema (branches, employees, members, books, issue/return), enforced PK/FK relationships, performed CRUD operations, created CTAS reporting tables, and wrote queries for revenue, overdue tracking, active members, and branch

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Engagement

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on GitHUB

Other Tools

PostgreSQL

ERD

CRUD

CTAS

GitHub

Database schema (ERD): designed a normalized Library Management System with PK/FK relationships across branches, employees, members, books, issued_status, and return_status—supporting accurate tracking of borrowing, returns, and branch operations.

CRUD + operations: executed real library workflows in PostgreSQL—INSERT new books, UPDATE member details safely using WHERE, and DELETE issue records only for corrections—ensuring clean, reliable data for analysis and reporting.

Project Details

Built a complete Library Management System in PostgreSQL from scratch. I created a clean relational schema with core entities (branch, employees, members, books, issued_status, return_status) and defined primary/foreign keys to ensure data integrity and prevent orphan records (ERD-driven design). After loading data, I performed real operational SQL tasks (CRUD) such as adding inventory, updating member details, and handling transaction corrections. For reporting, I used CTAS to create summary tables like book-wise issue counts, active members, and branch performance. Finally, I ran advanced analysis queries to track rental revenue by category, identify books not yet returned, generate overdue lists (30-day policy), and evaluate staff/branch workload for operational decision-making.

PowerBI Project

Bank Loan Portfolio Analysis Dashboard

Domain/Function: Banking & Finance Analytics (Loan Portfolio / Credit Risk)

Built an interactive Power BI dashboard for bank loan portfolio monitoring using SQL + DAX. Tracked KPIs, MTD/MoM trends, and Good vs Bad loans with segment filters (state, purpose, grade) for risk insights.

View Project
Engagement

View Project
on GitHUB

Other Tools

MS SQL Server (SSMS)

Power Query

DAX

Summary page showing key KPIs (Applications, Funded Amount, Amount Received, Avg Interest Rate, Avg DTI) with MTD/MoM trends and Good vs Bad loan split to quickly understand overall portfolio performance and risk.

Details page for drill-down analysis with filters (State, Purpose, Grade) to explore specific loan segments, validate performance, and identify patterns in risky vs healthy loans.

Project Details

Bank Loan Portfolio Analysis project built using SQL and Power BI to monitor lending performance and portfolio risk. The dashboard provides a clear view of Total Applications, Funded Amount, Amount Received, Avg Interest Rate, and Avg DTI, along with MTD/MoM tracking. It also highlights portfolio health using Good vs Bad Loans and loan status breakdown. Users can filter by State, Purpose, and Grade to quickly identify high-demand segments and risky categories, and drill down into details for deeper investigation.

Live Interactive Dashboard

PowerBI Project

Call Center Performance Dashboard

Domain/Function: Customer Service Analytics / Operations Analytics

Designed an interactive Power BI dashboard to analyze 32.94K customer calls, 824.22K total call minutes, response time performance, sentiment trends, call reasons, and channel-wise activity. The dashboard helps track service efficiency, identify issue patterns, and support faster operational decisio

View Project
Engagement

View Project
on GitHUB

Other Tools

Power Query

DAX

Excel

Overview dashboard showing total calls, total call duration, response time, call reasons, sentiment trends, state-wise distribution, and call center performance.

Detailed grid view showing call-level records including customer name, channel, state, reason, response time, city, and call duration for deeper analysis.

Project Details

In a call center, every call reflects a customer issue, a service delay, or a response challenge. I built this Call Center Performance Dashboard in Power BI to turn raw call data into a clear operational story. The dashboard tracks total calls, call duration, average call time, and response time while also showing why customers are calling, how they feel, which channels they use, and which call centers handle the highest volume. It includes analysis by day, state, reason, sentiment, channel, and center, along with a detailed grid page for record-level review. Using Power Query for cleaning and DAX for KPI creation, this project helps uncover service patterns, monitor efficiency, and support faster, data-driven decisions.

Live Interactive Dashboard

PowerBI Project

Pizza Sales Report Dashboard

Domain/Function: Food & Beverage / Sales Analytics

Built an interactive Power BI dashboard to analyze pizza sales performance using KPIs, daily and monthly order trends, category-wise sales contribution, pizza size preferences, and best/worst-selling products. The report helps track revenue, order behavior, and product performance for better busines

View Project
on GitHUB

Other Tools

Power Query

DAX

Data Visualization

Main dashboard view showing revenue KPIs, daily and monthly order trends, category-wise sales share, pizza size contribution, and total pizzas sold by category.

Best/Worst Seller analysis page showing top and bottom 5 pizzas by revenue, quantity sold, and total orders to identify strongest and weakest products.

Project Details

This project is a Power BI sales analysis dashboard created to monitor and evaluate pizza business performance. The dashboard tracks key KPIs such as Total Revenue, Average Order Value, Total Pizzas Sold, Total Orders, and Average Pizzas per Order. It also provides trend analysis by day and month to identify peak business periods and customer ordering patterns.

A separate Best/Worst Seller page was designed to highlight the top and bottom 5 pizzas based on revenue, quantity sold, and total orders. In addition, the dashboard analyzes sales distribution by pizza category and pizza size, helping identify which products contribute most to overall performance. Interactive filters for category and date range allow flexible analysis. This project demonstrates skills in data cleaning, DAX calculations, KPI reporting, interactive dashboard design, and business insight generation using Power BI.