Portfolio - Omkar Umesh Gadade

PowerBI Project

Global Business Insights 360

This Project is regarding IT Computer Hardware sales of a Company named AtliQ (Fictional) to it's various different customers present in various markets around many regions. The entire Project is created using PowerBI. The Project covers various Data Analytics concepts and topics.

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Finance View Dashboard consisting of Dynamic Profit & Loss Statement,Trend Chart,KPIs ,Top/Bottom list, Interactive Filters Panel and Navigation menu.

Supply Chain View Dashboard for analyzing KPIs like Forecast Accuracy% wrt customers and product and visualiztion by Line and Clustered Column Chart.

Project Details

The Project is divided in following Dashboards:-
📶 𝗙𝗶𝗻𝗮𝗻𝗰𝗲 𝗗𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱:-Insights of 𝗣&𝗟 𝗦𝘁𝗮𝘁𝗲𝗺𝗲𝗻𝘁 consisting of important metrics such as 𝗚𝗿𝗼𝘀𝘀 𝗠𝗮𝗿𝗴𝗶𝗻 %, 𝗡𝗲𝘁 𝗦𝗮𝗹𝗲𝘀, 𝗡𝗲𝘁 𝗣𝗿𝗼𝗳𝗶𝘁 %.
📶 𝗦𝗮𝗹𝗲𝘀 𝗗𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱:- Analyzing Performance of the Customers based on Revenue i.e 𝗡𝗲𝘁 𝗦𝗮𝗹𝗲𝘀 and Profit i.e 𝗚𝗿𝗼𝘀𝘀 𝗠𝗮𝗿𝗴𝗶𝗻 % achieved from those customers.
📶 𝗠𝗮𝗿𝗸𝗲𝘁𝗶𝗻𝗴 𝗗𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱:- Analyzing performance of products henceforth taking efficient steps to increase the Net sales and Gross Margin %.
📶 𝗦𝘂𝗽𝗽𝗹𝘆 𝗖𝗵𝗮𝗶𝗻 𝗗𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱:- Insights on the Supply Chain metrics- 𝗡𝗲𝘁 𝗘𝗿𝗿𝗼𝗿, 𝗔𝗯𝘀 𝗘𝗿𝗿𝗼𝗿, 𝗙𝗼𝗿𝗲𝗰𝗮𝘀𝘁 𝗔𝗰𝗰𝘂𝗿𝗮𝗰𝘆 %, 𝗔𝗰𝘁𝘂𝗮𝗹 𝗦𝗮𝗹𝗲𝘀 𝗤𝘁𝘆 𝗮𝗻𝗱 𝗙𝗼𝗿𝗲𝗰𝗮𝘀𝘁𝗲𝗱 𝗤𝘁𝘆
📶𝗘𝘅𝗲𝗰𝘂𝘁𝗶𝘃𝗲 𝗩𝗶𝗲𝘄 𝗗𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱: Gain quick Insights such as comparison of 𝗥𝗲𝘃𝗲𝗻𝘂𝗲 𝗖𝗼𝗻𝘁𝗿𝗶𝗯𝘂𝘁𝗶𝗼𝗻 %, 𝗠𝗮𝗿𝗸𝗲𝘁 𝗦𝗵𝗮𝗿𝗲 %, 𝗡𝗲𝘁 𝗦𝗮𝗹𝗲𝘀 wrt it's rivals.

Project video

Live Interactive Dashboard

PowerBI Project

Hotel Hospitality Domain

A Power BI Dashboard to analyze the key performance indicators of AtliQ Grants Hotel Chain present all across India. The Project belongs to Hospitality Domain and deals with the challenges faced by Hotel Chains and how they can be solved by undertaking data driven decisions.

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Hotel Hospitality Dashboard consisting of different vizualizations like Line Trend Chart, Doghnut Chart, line and stacked column chart and KPIs.

When selected on three bar Menu Button, a Filter Pane menu option appears for filtering the Data wrt month, week, city and room class.

Project Details

𝗞𝗲𝘆 𝗠𝗲𝘁𝗿𝗶𝗰𝘀 for 𝗛𝗼𝘁𝗲𝗹 𝗛𝗼𝘀𝗽𝗶𝘁𝗮𝗹𝗶𝘁𝘆 𝗗𝗼𝗺𝗮𝗶𝗻:-
💰 𝗥𝗲𝘃𝗲𝗻𝘂𝗲: This Kpi helps to monitor the revenue generated and track them across cities, weeks, room class.
📅 𝗔𝗗𝗥: Average Daily Rate is a measure which provides the daily rate of properties depending upon dynamic pricing.
🏠 𝗢𝗰𝗰𝘂𝗽𝗮𝗻𝗰𝘆 %: Gives an understanding of the successful bookings across properties within hotel chain.
✅ 𝗥𝗲𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻 %: Provides information for Actual Successful checkouts when compared to cancellation % or no show %.
📉 𝗥𝗲𝘃𝗣𝗔𝗥:Provides Revenue Per average Room across all properties.
🏘️ 𝗗𝗦𝗥𝗡:Daily Sellable room nights monitors total rooms sold on daily basis.
🏘️ 𝗗𝗕𝗥𝗡:Daily booked room nights monitors total rooms booked on daily basis.
🛎️ 𝗕𝗼𝗼𝗸𝗶𝗻𝗴 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺: Various Platforms available for bookings and how they contribute to the revenue of the hotel chain.
🌆 𝗖𝗶𝘁𝘆: The locations across which the properties are present.

Project video

Live Interactive Dashboard

PowerBI Project

Telecom Domain Analysis

A Dashboard is created for Atliqo which is a telecom company in telecom domain and is introducing a new 5G plan. The Stakeholders need to analyze various different KPIs and parameters performance before and after implementation of 5G plans.The project covers various Dashboards merged in one report.

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Provides Information regarding Plan P2 and its before and after Total Revenue, the user can also switch to Avg Revenue by selecting the toggle button.

Provides Information for Avg Revenue KPI across various cities in before and after 5G trend. User can also select different KPIs by clicking on them.

Project Details

𝗞𝗲𝘆 𝗠𝗲𝘁𝗿𝗶𝗰𝘀:-
💰 Total Revenue
💸 Avg. Revenue
👤 Average Revenue Per User (ARPU)
👥 Total Active Users
❌ Total Unsubscribed Users
🔍 Market Share %
💶 Revenue Before 5G
💵 Revenue After 5G
📈 ARPU Before 5G
📉 ARPU After 5G
🗣️ Active Users Before 5G
👥 Active Users After 5G
🌐 Unsubscribed users Before 5G
✨ Unsubscribed users After 5G

The PowerBI Project is a combiation of 5 Different Dashboard:
1. Total KPI Metrics Dashboard: Gives an insight on Telecom KPIs at aggregate Total level.
2. Market Share % Dashboard: The Dashboard has details regarding Market Share of various Telecom Players.
3. Avg. KPI Metrics Dashboard: This View provides insights of different Telecom KPIs at average level.
4. Plan KPIs Dashboard: Gives an understandig of various Plans data.
5. Plans Matrix Table and Top/Bottom Cities: Gives insights on Revenue for various Plans at Date level in Matrix Format and it also provides insights on Top/Bottom Cities with respect to revenue

Project video

Live Interactive Dashboard

SQL Project

SQL AdHoc Analysis

10 BUsiness Requests are asked by the stakeholders and management for gaining Insights. The project consist of solving this requests by appling and executing SQL queries to the MySQL database and assesing the Data thus providing answers to the questions asked.

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Executing an SQL query to find top 5 customers having High Average Pre Invoice Deductions in Indian Market during the Fiscal Year 2021.

The same Output is visualized in the form of Pie Chart and Matrix Table in Power BI software.

Project Details

Domain: Consumer Goods | Function: Executive Management

Atliq Hardwares (imaginary company) is one of the leading computer hardware producers in India and well expanded in other countries too.
However, the management noticed that they do not get enough insights to make quick and smart data-informed decisions. Therefore they have provided the sql database file for Data Analysis to provide relevent insights for their top management, such that they can take calculated business decisions.

TOOLS Used:-
MySQL Workbench - Covered SQL Concepts consisting of Joins, CTEs (Common Table Expression), Subqueries, Window functions, String
functions, Numeric functions, Date functions, etc.
PowerBI - For Presentation purpose by using various visuals like Bar Chart, Matrix, Line Chart, Maps, Donut Chart etc

Project video

Python Project

Data Analysis with Python Pandas

This Python project deals with various Python Pandas method used for Data Import and Exploration, Data Cleaning and Data Transformation and thus assessing the data required for Data Analysis using Python Programming Language.

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"pd.read_csv" method of Pandas library is used to import files into Jupyter notebook and assigning them to freshly created respective variables.

Data Transformation is performed and occ. pct column is created in df_aggregated_bookings table using apply function and Lambda function.

Project Details

The Project consist of a Jupyter Notebook named "Hotel_Analysis", we have Imported Pandas library and have read files using pd.read_csv method of Pandas, following tables are Imported: dim_date, dim_hotels, dim_rooms, fact_bookings and fact_aggregated_bookings.
Data Exploration, Data Cleaning and Data Transformation is performed on the imported tables in Jupyter notebook using Python Pandas.

Tools Required:
Python --version 3.8+
Jupyter Notebook
Microsoft Excel
Pandas Library

Excel Project

Advanced Excel Data Analysis

Microsoft Excel Advanced Features like Data Modelling, Connections, Queries, Power Query Editor, Power Pivot Data Field Pane and Power Pivot Tables are used for creating, transforming and providing valuable insights of data through Excel Reports.

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The above report depicts various countries Net Sales Performance in year 2019, 2020, 2021 and a comparison of year 2021 with Target and % change.

The above Report Shows performance of various P&L Metrics w.r.t Fiscal Years 2019 and 2020 which is further divided into Quarters.

Project Details

AtliQ hardwares is a consumer goods IT hardware manufacturing Company and the stakeholders want the Data Analyst to create reports using advanced excel techniques as follows:
1. Creating Connections by importing Data from folder/csv files.
2. Importing Data to Data Model by adding the same in Data Model.
3. Creating Data Model and connecting the respective tables in StarSchema SnowFlakes Model in one to many relationships.
4. Inserting PivotTable and Managing the Data within Power Pivot by dragging and droping data fields from Power Pivot Field Pane in Excel software.
5. Creating/Editing Measures and Managing them in Power Pivot.
6. Transforming Data in PowerQuery Editor like replacing values, promoting Headers, transposing tables, Trimming Characters etc.
7. Adding Conditional Formatting and KPIs for Color Grading with respect to different parameters.

Hello, I am

Omkar Umesh Gadade

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Global Business Insights 360

Hotel Hospitality Domain

Telecom Domain Analysis

SQL AdHoc Analysis

Data Analysis with Python Pandas

Advanced Excel Data Analysis

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Omkar Umesh Gadade

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