Power BI; Data Visualization Tool.

What is Data Visualization?

10 min readApr 25, 2021

Data Visualization is defined as the pictorial representation of the data to communicate data or information to decision-makers as text data might not be able to reveal the pattern or trends needed to communicate the message.

There are two different types of data visualization:

1. Exploration Analysis

This analysis focuses on finding relationships between variables as well as identifying patterns and outliers with the aid of a data and also connecting to questions about data. Here visualization don’t need to be perfect but whatever analysis done must satisfy the audience’s expectations.

2. Explanation Analysis

This tells a story to an audience after the data has been explored, here you focus on what has happened (information) and why it happened (knowledge) also taking into account the audience’s expectations. Visualization has to be detailed and insighful.

Note: Do not include informations that are not needed.

Why?

According to the writers of A Tour Through the Visualization Zoo, “The goal of visualization is to aid our understanding of data by leveraging the human visual system’s highly-tuned ability to see patterns, spot trends, and identify outliers”, in summary Data visualization makes the data more natural for the human mind to comprehend.

5 Steps of Data Analysis

Extract
Clean
Explore
Analyze
Share

Data Visualization Tool

Data Visualization tool is a software which provides the accessible way to see and understand trends, outliers and patterns in data. Examples of visualization tools are matplotlib, Tableau, and Microsoft power BI etc. Tableau seemed easier to use compared to power BI;which will be our main focus in this article.

Power BI(Business Intelligence).

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

It is the leading data visualization tools. It supports the collection of software services, apps and connectors that works together to turn unrelated sources of data into insights through easy to use customizable visualizations.

Power BI is used by over 97% of Fortune 500 companies ( i.e the largest 500 companies in the united states compiled by the Fortune magazine) and has over 6 millions customers.

In this article we will be using power BI to analyze a

Versions of of Power BI.

Power BI desktop: It is a free application you install on your computer that serves as the complete report authoring tool to create reports. It includes powerful features, like the Query Editor.
Power BI service:It is an Internet-run program with components stored online with some (or all) processes executed in the cloud, that enables anyone to visualize and analyze data with greater speed, efficiency, and understanding. It is mainly for sharing and distributing reports.
Power BI Pro: Paid per-user license, needed to get access to advanced features and the ability to share reports
Power BI Premium: Licenses by scale, intended for large businesses and enterprises
Power BI Mobile: It is a device-based app for phones and tables
Power BI Embedded: A white-label version of Power BI which Independent Software Vendors can embed in their own apps, rather than build their own analytical features
Power BI Report Server: An on-premise version of the Power BI Desktop app for businesses that need to keep their data and reports on their own

Components of Power BI.

Power Query: It’s a data connection tool that lets you transform, combine, and enhance data from several sources.
Power Pivot: It’s a data modeling tool for creating data models.
Power View:It’s a data visualization tool that generates interactive charts, graphs, maps, and other visuals.
Power Map: It’s a visualization tool for creating immersive 3D visuals
Power Q&A:It’s a question and answer engine that lets you ask questions about your data in plain language.

Check this article for more information about the version and components of power BI.

Power BI interface

There are three data interface accessible to power BI users, these views can be selected by clicking one of the three icons on the left side of the power BI:

Report view : This is where you build reports and visuals from queries you create. They can be arranged to your taste and you can create a lot of pages. The image below shows that the report view icon has been selected, this is indicated by the yellow band.

In the report view we have the Filter pane ,Visualization pane and Fields pane.

Image showing the Filter, Visualization and Field Pane.

Filter pane

This automatically appears once a visual is included on the report canvas. Here you can configure which filter to include and then update existing filter to aid your visualization by dragging other fields of interest into the filter pane. One can also rename,sort, format, hide etc .

There are 3 types of filter :

Visual-level filters: Its applied directly on individual data filter.
Page-level filters: Its applied on selected page.
Report-level filters: Its applied on the entire plot.

Visualization pane

From the image above we can see the visualization pane next to the filter pane.This pane exhibits the different ways one can give insights to their readers or viewers. Visualizations can be edited with the aid of a paint roller.

Types of visualization

1.Column and Barchart: This type of visualization helps you look at a specific value across different categories. The difference between them is that the rectangle in a Column chart is vertically placed and the rectangle in a barchart is horizontally placed.

There are different types of barchart and column:-

Stacked bar and column chart: Here there are multiple element in one bar.
Clustered bar and Column chart: It includes a multiple bar representing values located next to each other. Below is an image of a column clustered chart.

This insight was gotten from the dataset presented to us to work with; This is a visual representation of the number of suicides in different countries, from the visual we can draw an insight that the Russian Federation has the highest number of suicides.

100% stacked bar and column chart : Here the total of each stacked bar always equal 100. It shows the relative % of stacked bars.

This image is a visual representation of the number of suicides by age and sex; if we look closely we will see that there is a legend above immediately after the title which indicates pink represents female and blue represents male. We get the insights that male have more tendency to commit suicides compared to female, also there is a high rate of suicide for male between age 25–34 years.

N.B: Each rectangle bars percentage numbers present in the chart add up to 100%.

. Combo chart : It combines a column and a line chart.

This is a line clustered chart visual representation of the number of suicides considering the age and sex and how the Human Development Index (HDI) is affected. The insight of this visual tells us that the HDI is the same no

2. Line chart: It shows multiple lines in one chart and emphasize the overall shape of an entire series of values, usually over time.

The image below represents a line chart showing the relationship between the gdp per capita ($) and suicides no by country.

3. Area charts : They are based on line charts with the area between the axis and line filled in.

4. Pie and Doughnut charts: They show the relationship between a part to a whole.

5. Tree maps: They also show the relationship of parts to a whole. They are charts of colored rectangles, with size representing the proportional values.

6. Card, multi-row card, KPI, gauge chart: These are used for showing the overall level of performance. Cards show one value, while multi-row cards can display multiple. Gauge and KPIs are designed to show actual data compared to budgeted data

7. Table and matrix: These visualizations show detailed text data in a tabular format. A table is a grid that contains related data in a logical series of rows and columns. It may also contain headers and a row at the bottom for totals. A matrix is similar to a table in that it is made up of rows and columns. However, a matrix can be collapsed and expanded by rows and/or columns.

Table, card and slicer visualization image.

With the visualization above I inended gaining insight on what sex has the highest number of suicide in each country and what year. I made use of a slicer to help in selecting the country I intend to visualize , here I selected Belarus and with the visual we’ll see that male has the maximum number of suicide of 1391 in year . The card shows the gdp_per_capital of ($) of the country Belarus.

More on visualizations

Two or more Visualizations can be used at the same time for example a card can be used to show the details of a clustered bar .
Details of a visualization can be seen when we hover our mouse above the current visuals.
The formatting tool that looks like a paint roller can be used to change the size of the font of a visualization title.
To change the theme of the report ,click the visual currently on the canvas > click view in the ribbon above your desktop.
In situations where we have an hierachy in our visuals like, year> quarterhalf >month> date, we drill down with the aid of an arrow like icon around the visual canvas.

In the image below from the dataset given I made an hierachy with the age field and generation field. Above the visuals, a clustered column chart, there are four arrow-like icons.

The first arrow pointing up: drills up the fields one at a time after drilling down to the last hierachy.
The second arrow pointing down: drills down one field at a time.
The third one with a twin arrow pointing down; drills down on all field at ones.
The fourth one which looks like a fork teeth: expands all field at a time.

Fields pane

This is that pane that contains the list of all the available tables in the data model. When a table is expanded you see the fields on that table. Hierachy is formed in the field pane, by dragging a field on top another.

2. Data view

This view shows the data in your report in data model format, where you can add measures, create new tables ,create new columns, and manage relationships. In the image below we can see the yellow band on the second icon along the left side of the power BI desktop.

The ability to create programmatically generated new measures, tables and columns in the data view is called Data Analysis Expressions (DAX).It is a calculation language used in power BI.

It consists of many functions, that is predefined formulas that perform calculations on specific values, called arguments, in a particular order. Do not fret , you don’t need to cram all the functions , a tool called Power BI provides code completion i.e it provides the syntax and a description of the function when typing.

Each function has a specific syntax indicating the order of arguments expected. Examples of DAX function are the SUM function, LEFT function etc.

More on DAX function

Creating calculation columns is based on other columns from any table. Any column created is calculated at Data load or when the data is refreshed. A calculated column adds a new column to a table and and evaluates a row
Creating calculation tables is the same as columns.
Creating calculation measures helps define complex measure to be used on your data. measures are calculated during query time therefore making it efficient because the measure isn’t run everytime the table is accessed unless when it’s used. A measure aggregates multiple rows and result in another field which can be added to a visualization.
When defining a calculation column, table or measure, you need to give it a name, followed by an equal sign.
When using DAX formula first put the name of the column|table|measures of the new calculation and equal sign then proceed with your preferred function.
There is a function called Nested function , it is a function within a function i.e FUNCTION 1(FUNCTION 2(column name)). For example if i want to convert a text of a particular funtion to lowercase, I’ll be making use of the LOWER() function, which converts text to all lowercase. e.g LOWER(FUNCTION 2(column name)).
Quick measure tool is that tool one can use to create measure without using DAX functions .They work by providing a menu commonly used divided into 6 categories which are:

-Aggregate per categor

-Filters

-Time intelligence

-Total

-Text

-Mathematical Operations

One of the most commonly used DAX functions is the Calculate function, which lets you combine aggregating and filtering. It takes one or more filter. It can use functions like SUM or COUNT or it can be another calculated measure.

3. Model / Relationship view: Here is where you can see and manage the relationships among tables in your data model. The third icon with the yellow band indication in the image below represents the model view. The lines connecting the square like boxes are called a relationship line.