Data Science: Practical 7

AIM: Consume data with Power BI and How to build a simple dashboard.

Theory:

PowerBI - Power BI is an analytics tool developed by Microsoft that turns your bits of unstructured data into a visually compelling story. It consists of the Power BI Desktop, the SaaS Power BI Service, and a range of mobile apps (iOS and Android compatible). These tools take big data and help your business or organization ask the right questions and receive actionable insights. Power BI takes information from disparate data sources and turns them into custom visuals designed to help an organization not only read the info but get a clear idea of what to do. The right data visualization can be the difference between having unstructured data that disappears and using that data to make critical (and more importantly, correct) decisions.

Types of visulaisation:

Area Charts, Bar Charts
Clustered Column Charts
Doughnut charts
Line Charts
Scatter charts
Candle Stick
Map
Pie Chart
KPI
Other Charts can be imported from Market place

Visualization in PowerBi can be dynamic based on the feature selected. It has dynamic flow for all the diagrams or charts that are created in a Dashboard. It has ability to change the values and display based on page, reports etc.
PowerBi has various ways to import data for analysis. It has sources like:

CSV
Excel Sheet
MySQL Database
API
Web Scrap URL
Azure Data sources
Others
PowerBi is robust tool comparing it with its counterparts like Tableau, Quicksight etc. PowerBI give you the power to maintain dashboards with other Microsoft's other application like Word, Powerpoint Presentation, Excel etc. This is the best feature which also allows access to Azure cloud. PowerBi also has Mobile app which makes it easier to share the report created.

Dataset Description:

Data columns (total 16 columns):
 #   Column                 Non-Null Count  Dtype 
---  ------                 --------------  ----- 
 0   Segment                700 non-null    object
 1   Country                700 non-null    object
 2    Product               700 non-null    object
 3    Discount Band         700 non-null    object
 4    Units Sold            700 non-null    object
 5    Manufacturing Price   700 non-null    object
 6    Sale Price            700 non-null    object
 7    Gross Sales           700 non-null    object
 8    Discounts             700 non-null    object
 9     Sales                700 non-null    object
 10   COGS                  700 non-null    object
 11   Profit                700 non-null    object
 12  Date                   700 non-null    object
 13  Month Number           700 non-null    int64 
 14   Month Name            700 non-null    object
 15  Year                   700 non-null    int64 
dtypes: int64(2), object(14)

(700, 16)

Dashboard Report
Country representation in data

Sales by segment

Totals sales and unit sold

Sales price by month

Sales by product

Profit by segment

Profit Units sold and Discount by month