Explore

F23 IN6003 Systems Modelling Lab 1 The Power BI Real Estate Analysis

Due October 10

Dropbox Upload for final Power BI FILE:

https://www.dropbox.com/request/5HeO5uRWRS2rWvSu7SLs⁠

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Learning Purpose: Doing the Real Estate Business Analysis with PowerBI.

What you will do in this Assgnment.

Make a Analytic Dashboard with 3 cities in the Greater Toronto Area to do Exploratory Data Analysis on the Real Estate prices and market activity.

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How to proceed:

Download PowerBI from Windows Store.

Mac Users: Microsoft does not make a PowerBI Desktop Version available for Mac → Mac users will work in the Cloud.

Let’s prepare our Data Set. Copy / paste the data from a web page into Excel.

Lab Activities Workbook: Exploratory Data Analysis Using PowerBI

Introduction:

In this lab, students will practice conducting Exploratory Data Analysis (EDA) on a real estate dataset using PowerBI. The dataset, provided in Excel format, contains various details about real estate transactions. Students will create five different visualizations to uncover trends and insights within the data.

Objectives:

Familiarization with the PowerBI interface and tools.

Importing and processing data from an Excel file.

Creating meaningful visualizations to conduct EDA on real estate data.

Lab Instructions:

I. Importing the Data:

Launch PowerBI:

Open the PowerBI Desktop.

Import Data:

Go to the "Home" tab.

Click on “Get Data” and select “Excel”.

Navigate to the real estate Excel file provided by your professor and open it.

Load the dataset into PowerBI.

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II. Data Preparation:

Explore the Dataset:

Familiarize yourself with the data and clean it if necessary.

Manage the Data:

Create relationships, measures, and calculated columns as necessary.

III. Creating Visualizations:

Create a Pie Chart:

Illustrate the distribution of property types (e.g., condos, single-family homes, etc.).

Go to the "Visualizations" pane and select "Pie chart".

Drag and drop the "Property Type" field into the "Legend" area and "Count of Property Type" into the "Values" area.

Create a Scatter Plot:

Examine the relationship between property age and price.

In the "Visualizations" pane, select "Scatter chart".

Drag and drop "Age" into the "X-Axis" and "Price" into the "Y-Axis".

Create a Bar Chart:

Show the average price per neighborhood.

In the "Visualizations" pane, select "Bar chart".

Drag and drop "Neighborhood" into the "Axis" area and "Average of Price" into the "Values" area.

Create a Map Visualization:

Display the geographic distribution of properties.

In the "Visualizations" pane, select "Map".

Drag and drop the "Latitude" and "Longitude" fields into their respective areas, and "Count of Property" into the "Size" area.

Create a Line Chart:

Visualize price trends over time.

In the "Visualizations" pane, select "Line chart".

Drag and drop "Date" into the "Axis" area and "Average of Price" into the "Values" area.

IV. Saving and Exporting Your Work:

Save Your Report:

Go to the "File" tab, select "Save As", and save your report with an appropriate name.

Export Your Visualizations:

Export your visualizations for your presentation.

V. Presentation:

Prepare a brief presentation (5-10 slides) outlining your findings from the EDA. Include each visualization and describe the insights you gathered.

Grading Rubric:

Data Import and Preparation (20 points):

Successful data importation (5 points)

Data cleaning and management (15 points)

Visualization Creation (50 points):

Proper creation and configuration of pie chart, scatter plot, bar chart, map visualization, and line chart (10 points each)

Analysis (20 points):

Correct interpretation of each visualization (4 points each)

Presentation (10 points):

Clear and concise presentation of findings (10 points)

Total: 100 points

Note: Students should submit the PowerBI report file (.pbix) along with the exported visualizations and presentation for grading.

Save your PowerBI Desktop file (windows users) or Excel File (mac users)

Name the file as StudentName_StudentID

and upload to :

Dropbox Upload for final Power BI FILE:

https://www.dropbox.com/request/5HeO5uRWRS2rWvSu7SLs⁠

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Lecture: Understanding PowerBI, Analytic Dashboards, and Exploratory Data Analysis for New Graduates

Introduction:

Greetings class,

Today, we are diving into an informative lecture about PowerBI, analytic dashboards, and exploratory data analysis (EDA), and we will also discuss their relevance to new graduates entering the professional world. This knowledge will enhance your understanding of data analytics tools, enabling you to make more informed, data-driven decisions in your future roles.

Part I: What is PowerBI?

Definition:

PowerBI is a collection of software services, apps, and connectors by Microsoft that work together to turn unrelated sources of data into coherent, visually immersive, and interactive insights.

Components:

PowerBI Desktop: A Windows desktop application.

PowerBI Service: An online SaaS (Software as a Service).

PowerBI Mobile: A mobile application available on Android and iOS devices.

Functions:

Import and clean data from a wide range of sources.

Create and share reports and dashboards with interactive visualizations.

Utilize natural language query functions.

Part II: Analytic Dashboards:

What is an Analytic Dashboard?

Analytic dashboards are information management tools that visually track, analyze, and display key performance indicators (KPI), metrics, and key data points to monitor the health of a business, department, or specific process.

Types of Dashboards:

Operational Dashboards: Provide day-to-day insight for active monitoring.

Strategic Dashboards: Focus on long-term objectives and KPIs.

Analytical Dashboards: Enable users to analyze large volumes of data to discover trends and insights.

Benefits of Analytic Dashboards:

Centralize and visualize data for easier analysis.

Enhance decision-making capabilities.

Simplify complex data sets.

Enable real-time data tracking.

Part III: Exploratory Data Analysis (EDA):

What is EDA?

EDA is an approach to analyzing datasets to summarize their main characteristics, often with visual methods. EDA allows users to explore data in-depth and to identify underlying patterns and trends.

Techniques in EDA:

Histograms, boxplots, and scatter plots.

Data transformation.

Correlation analysis.

Outlier detection and handling.

Benefits of EDA:

Unveil patterns and insights in the data.

Identify anomalies and outliers.

Assist in model selection and validation.

Part IV: Relevance to New Graduates:

Why is this Important for New Graduates?

As you step into the professional world, the ability to analyze data effectively is a valuable skill, regardless of your role or industry.

Application of Skills:

In Marketing: Understand consumer behavior, and optimize marketing strategies.

In Finance: Analyze financial trends, and make informed investment decisions.

In Operations: Optimize supply chain and improve operational efficiency.

In HR: Analyze employee satisfaction and optimize recruitment processes.

Career Advancement:

Proficiency in PowerBI and data analysis tools can set you apart in the job market, paving the way for roles in data analytics, business intelligence, and more.

Conclusion:

In summary, PowerBI is a robust tool for creating visual and interactive reports and dashboards. It plays a crucial role in exploratory data analysis, helping businesses uncover insights, make informed decisions, and optimize processes. As new graduates, harnessing the power of PowerBI and understanding the significance of analytic dashboards and EDA will not only elevate your professional skills but also enhance your career opportunities in the rapidly evolving business landscape.

Feel free to reach out for further discussion or any queries. Let’s embark on this data journey together and make the most out of the insights it offers.

Thank you, and happy analyzing!

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