power bi portfolio -aniekan okono

BI Analyst

Power BI Portfolio by Aniekan Okono

Last Updated: June 2016 Page 1

BI Analyst

Contents

Contents 1. Power BI

1.1. About Power BI 1.2. About PorĔolio

2. Data Analysis & Business Intelligence Analysis 2.1. Overview

2.1.1. Aggregated Visualizaĕon 2.2. Business Intelligence

2.2.1. Revenue by Country 2.2.2. Aggregated Data Visualizaĕon 2.2.2. Revenue by month

3. Time Series, Correlaĕon Analysis and KPIs 3.1. Overview

3.1.1. About this data 3.1.2. Transformaĕon of data 3.1.3. Time Series Analysis 3.1.4. Correlaĕon Analysis 3.1.4. Revenue by Country 3.1.5. Dashboards


BI Analyst

1. Power BI

1.1. About Power BI

Power BI is a suite of business analytics tools used to analyze data and share insights. Monitor business performance and get answers quickly with rich dashboards available on every device.

1.2. About Portfolio

This portfolio uses open data sources to showcase the use of Power BI. The data sets used contain business metrics from an unspecified company and population data from the World Bank. Power BI is used to analyse and visualise the data. Since the free version of Power BI is used, it has certain limitations and restrictions compared to pro accounts.


BI Analyst

2. Data Analysis & Business Intelligence Analysis

2.1. Overview

The first data visualization is carried out with the World Bank’s Country Population data. The data is a subset of a dataset called "World Data Bank's Population, total". This is the link to the data file .

2.1.1. Aggregated Visualization

Diagram 1.0 below is a visualization of the populations of USA, Mexico, France, Canada and Germany from 1999 to 2014. I have compared the population of these countries over the said period. The graph represents the comparisons over time.


https://github.com/MicrosoftLearning/Analyzing-Visualizing-Data-PowerBI/raw/master/Lab1/CountryPopulationByYear.zip

BI Analyst

Diagram 1.0


BI Analyst

2.2. Business Intelligence

VanArsdel is a company that manufactures and sells sporting goods. The company has offices in the United States and several other countries. Its sales comprise of US and International sales. VanArsdel’s sales come from its owned manufactured products, as well as other manufacturers’ products. Here is the link to the dataset in excel format. For business intelligence purposes, date, product identification number, revenue, country and units have been extracted. The dataset has 841 150 rows and therefore fits the big data description. The following columns have been analysed:

● ProductID ● Date ● Units ● Revenue ● Country

As part of the data management process, I have created a new column and calculated the price from the revenue and units data.


https://github.com/MicrosoftLearning/Analyzing-Visualizing-Data-PowerBI/raw/master/Lab1/InternationalSales.zip

BI Analyst

2.2.1. Revenue by Country

Diagram 1.1 below showcases revenue by country. France has the highest revenue at $314.075, Germany the second highest at $234.007, Mexico the 3rd highest at $217.001,and Canada the lowest revenue at $75.032.

Diagram 1.1


BI Analyst

2.2.2. Aggregated Data Visualization

Diagram 1.2 aggregated various graphs to be used in visualizing different aspects of the data like location, revenue by countries, units sold and prices.

Diagram 1.2


BI Analyst

2.2.2. Revenue by month

Diagram 1.3 below indicates the revenue generated throughout the year. It can be seen that May was the most profitable month with $115.008 while January was the least profitable with $30.016.

Diagram 1.3


BI Analyst

3. Time Series, Correlation Analysis and KPIs

3.1. Overview

The below analyses are from an Odata source, created for visualization purposes only. The data can be found at http://services.odata.org/V3/Northwind/Northwind.svc/

3.1.1. About this data

The company details of the data are not revealed. The data contains information on the international orders of a company. The dataset is a typical example of what product or service companies require. At typical order database contains the following information: Orders (Customer, Date, ShipAddress), Order_Details (OrderID, Product, Quantity, UnitPrice, Discount) 3.1.2. Transformation of data

Excess columns are stripped away from the data to enable the analysis of the most important business related insights. The date of the order, location, employee (sales owner), quantity, year and month of order are all key details extracted from the data to use in providing key insights.


http://services.odata.org/V3/Northwind/Northwind.svc/

BI Analyst

3.1.3. Time Series Analysis

Power BI provides a powerful time series analysis. Diagram 1.4 is used to visualize an analysis of the orders over time.

Diagram 1.4


BI Analyst

3.1.4. Correlation Analysis

Diagram 1.5 below shows a correlation between the revenue generated (price multiplied by quantity) and price per unit. Higher prices brought more revenue whereas items with lower prices had more orders.

Diagram 1.5


BI Analyst

3.1.4. Revenue by Country

Diagram 1.6 below shows that the USA brought in more sales revenue compared to other countries. Germany also crossed the $200.000 revenue mark. The revenues are labeled on the x‐axis while the countries on the y‐axis.

Diagram 1.6


BI Analyst

3.1.5. Dashboards

Diagram 1.7 below shows that an employee by the name of Margaret brought in the highest sales revenue. The dashboard can be used to visualize various aspects of the data. Reports can be generated and shared via the Power BI platform.

Diagram 1.7


power bi portfolio -aniekan okono

Documents