Power Bi – Data Analytics & Visualization

Imagine you have thousands of records in a file and need to analyse them together – tough, right?

A pictorial representation of data is much more user-friendly and easy to comprehend. Power Bi is an advanced application developed by Microsoft to do exactly that. It feeds in a large amount of data from different sources as input and builds dynamic reports and analyses. It is easy to use with various data collecting applications like Microsoft Excel and helps publish import insights required for business. It works effortlessly with big data so that you can plug in information from all of your sources and generate required reports. Discover the benefits of our Power BI course in Delhi and gain a competitive edge in the field of data analytics.

What is Power Bi?

Power BI is a business analytics service provided by Microsoft that allows users to analyze data and create interactive visualizations, reports, and dashboards. It is a cloud-based service that can be accessed from a web browser or through mobile apps for iOS and Android. Power BI is designed to work witha wide range ofy data sources, including spreadsheets, databases, cloud services, and big data sources.

Key Features of Power Bi

Power BI offers a range of features that make it a powerful business analytics tool. Here are some of the key features of Power BI:

Data connectivity: Power BI offers seamless connectivity to various data sources, including Excel, SharePoint, Dynamics 365, SQL Server, and other cloud-based services such as Salesforce, Google Analytics, and Azure.
Data modeling: Power BI allows users to create data models that define relationships between tables and create calculated columns and measures. It also supports the creation of hierarchies, drill-through, and drill-down functionalities.
Data visualization: Power BI provides a range of visualization options, including charts, graphs, maps, and tables. Users can customize the visualizations using a drag-and-drop interface to add or remove fields, create filters, and change the formatting. Power BI also offers a range of advanced visualization options, such as treemaps, funnels, and gauges.
Data exploration: Power BI allows users to explore data and gain insights using features such as drill-down, drill-through, cross-filtering, and natural language query. Users can filter data by selecting data points on a chart or table or using slicers.
Collaboration and sharing: Power BI allows users to share their reports and dashboards with others in their organization or online. Users can collaborate on projects and share insights with stakeholders. Power BI also offers a range of collaboration tools, such as commenting, tagging, and versioning.
Artificial Intelligence and Machine Learning: Power BI provides a range of AI and machine learning features such as natural language query, quick insights, and auto clustering that enable users to explore and gain insights into their data.
Mobile access: Power BI offers iOS, Android, and Windows mobile apps. These apps allow users to access their reports and dashboards on the go and stay up-to-date with their data.

Data Connection with Various Sources

One of the main advantages of power is its ability to connect with various data sources. Some prime examples are IBM, MySQL, ORACLE, and Azure databases. It can also access data from online directories such as GitHub, and many more data sources are on the way to integrating with Power Bi soon. Steps for Data Connection with various sources in Data Analytics & Visualization are provided below:

In the Get Data window, select the source of data you want to connect. There are various options such as File, Database, Power Platform, and Online Services.
Let us select the option ‘other’ and proceed with the web. Press the connect button.
A dialogue box appears, asking for the URL of the site. Enter the details and select OK.
After the connection gets established, all the data inside the particular website are under the Navigator tab.
Load or edit the data according to your wish, and you are all set.

Live and extract mode in Power Bi

Let us get deeper into the topics one by one. Microsoft Power Bi is a business intelligence tool, and live and extract modes in Power Bi are some of the primary applications. There isn’t a second copy of the data kept in memory with this kind of connection. In the live mode, the power connects with datasets from only three types of applications from SQL Server Analysis Services (SSAS) technology. They are

SQL Server Analysis Services Multi-Dimensional
SQL Server Analysis Services Tabular
Power BI Service Dataset

Dynamic generation of reports after real-time tracking is an important aspect of live mode. However, do know that the modelling options in Power BI are severely constrained with the Live connection – just measures can be made.

Extract mode, also known as direct query, is excellent in handling large datasets that need to be processed. Instead of storing the data, it fetches the data directly from the source during the query time to save storage. It is also utilised for generating quick reports when the real-time data changes continuously.

Measures & Dimensions in Power Bi

Let us take the terms Measures & Dimensions in Power Bi individually. Measures are for analysis in Power Bi. It calculates different business metrics from the formulas that you provide for evaluation. It uses the Data Analyst Expression Language library of over two hundred different formulas and functions to create the result that you desire. Think of it as a mathematical tool for automatic calculations like MIN, AVERAGE, MAX, and SUM.

For example, it can create a graph of your projected sales for next year – if you provide this year’s sales and year-on-year growth. Not only that, it can create a visual representation of different analyses of your data — for example, profit percentages and net revenue, without user intervention.

The pieces of information that are not related to mathematical calculations are kept in dimension tables; they are business entities. While a fact table stores information about sales, a dimension table can contain information about the buyer, like their name, age, and address. The types of dimensions available are static dimensions, slowly changing dimensions, and rapidly changing dimensions.

Measures & Dimensions in Power Bi give great results together!

Minor Data Wrangling in Power Bi

Minor Data wrangling in Power Bi is one of the earliest stages in analysis. Firstly, it acts as a central repository and collects data from different sources. Then, it merges different complex data sets after removing errors and redundancies. With the increasing popularity of big data, it has become a prerequisite to storing and organising various data sets efficiently. Minor data wrangling helps to eradicate and fill blank cells according to client needs, therefore making efficient use of space. It reorganises data groups and converts raw datasets into a more useful format for analysis. Minor data wrangling in Power Bi helps in workflow automation and helps in recognising the valuation of your business.

Microsoft power query is a very powerful tool built in MS excel that is an excellent data wrangling tool. One of the prime advantages is that it integrates with other Microsoft applications like Power Bi to take data wrangling experience to the next level.

Data Blending in Power Bi

The ability to combine different datasets is known as data blending. Data Blending in power Bi gives a powerful feature of linking two or more related tables to provide a compact view, which also removes redundancy. To strengthen its data Blending in Power BI tools, Microsoft partnered with data blending and analytics company Alteryx Inc.

Data blending in Power Bi requires at least two primary and secondary data sources. The first dataset becomes the main view to which different fields of the second dataset get joined.

Think of it as a join in SQL. For example, suppose there are two datasets for sales data, and we need a comparison between the actual sale and targeted sales for this year. Data blending is the merging done by keeping an entity as a pivot, for example, the unique id of the selling material.

Data modelling in Power Bi

It is how different information links with each other. Data modelling in Power Bi connects multiple data sources and tables using relationships. For example, suppose you have a sales table with details of the item sold and the customer’s phone number.

Another table contains the customer’s details like name, address, and contact number. Data modelling in Power Bi connects these two tables based on one common information – the contact number. By modelling your data, you may record the data you have, how you utilise it, and the usage, security, and management needs. You can speed up data extraction and analytics by making plans for security, scalability, and development. Data modelling in Power Bi helps you meet business deadlines and tracks performance reports. According to your business needs, the types of data modelling offered are Conceptual data modelling, Logical data modelling, and Physical data modelling. Maintainance and updation of the models are very easy as the user does not need to do anything on their own.

DAX in Power Bi

The full form of DAX is Data Analysis Expressions. It has a vast library of functions, operands, and operators to make mathematical calculations easy. You can develop new insight from data already present in your model by using DAX to tackle a variety of computations and financial analyses. It can take your business to new levels by generating profit reports or by giving an insight into your project’s business growth in the future. By looking into the reports, you can alter some of your business metrics to take them to the next level. If you need to consider only specific values for analysis, DAX in Power Bi provides that too. DAX has functions that enable you to utilise the present row data as a parameter. It also has specific time intelligence functions. You can select a starting and ending date, and get a dynamic report based on that, for example, a population chart of a nation. Example of a DAX in Power Bi; Total population = SUM(Population[Male,Female]). Here, the table name is population, and column names are male and female. This formula sums up the total count.

Charts in Power Bi

Charts in Power Bi provide an interactive approach to analysing different reports. Some of the most used charts in Power Bi are as follows :

Bar and column charts: Rectangular bars are used in bar and column charts to depict data, which gets plotted against a vertical and horizontal axis.
Area charts: Area charts consist of two types: Basic and stacked. It focuses on change over time and fills the area between the axis and line. We can observe population growth percentage across years with this.
Combo charts: It gets the best of both worlds – combo charts in Power Bi are a combination of bar and line charts with multiple values for the Y axis. It is an important chart because one can easily combine multiple things over a wide range and analyse them.
Doughnut charts: As the name suggests, this chart is shaped like a doughnut and closely resembles a pie chart. You can add different colours and labels to each part to make it stand out.
Gauge charts: This chart looks like a speedometer. If your business needs to achieve any specific target within a range of time, this is the best chart you can use to analyse the difference between your current position and end goal.

Dashboards in Power Bi

Dashboards in Power Bi allow you to have all the insights clubbed together on a single screen. It is referred to as canvas because it tells a story — a story about the business! If you want to gain insight that highlights the business features, you need dashboards in Power Bi. Do note that the dashboard only comes in Power Bi service and not on Power Bi desktops. The feature works like a dashboard in real life – we can create or edit the dashboards by pinning the business metrics on the screen that we think are necessary. It can combine several datasets to give a beautiful representation of different metrics. It is dynamic – the tiles keep changing with changes in the data sets.

Types of Dashboards in Power Bi

Sales Analytics Report: covers important sections like sales over the years and their profit or loss margin, year-on-year growth, etc
Inventory stock analysis report: This Dashboard in Power Bi updates the important day-to-day things needed for different industries, for example – how much milk is needed for a dairy products manufacturing unit.

Stories in Power Bi

Data storytelling is the way we tell stories about data to the user. Stories in Power Bi are a strong and effective way of storytelling in the visual form. Complex information is made understandable through data storytelling. Stories in Power Bi allow clients to interact efficiently and extract their key ideas. Your data should add value to your organisation and inspire others to make a change for the better. It should be easy to understand, therefore increasing client engagement.

Most importantly, keep an unbiased approach while telling a story and being open to contradictions. Utilise unbiased data sets to influence your stories in Power Bi and how your ideas will bring a revolution.

You can utilise Power Bi’s web feature that allows insights and reports from your Power Bi account to be uploaded anywhere across the web so that your story reaches many people and moves them.

Advantages of Power BI

User-friendly interface: Power BI’s user-friendly interface makes it easy for users to work with data, create visualizations, and gain insights.
Data integration: Power BI can seamlessly connect to a wide range of data sources, including Excel, SharePoint, Dynamics 365, SQL Server, and other cloud-based services such as Salesforce, Google Analytics, and Azure.
Powerful data modeling: Power BI provides robust data modeling capabilities, allowing users to create relationships between tables, define calculated columns and measures, and create hierarchies.
Rich visualization options: Power BI offers a wide range of visualization options, including charts, graphs, maps, and tables, that can be customized to meet users’ needs.
Collaborative: Power BI allows users to share their reports and dashboards with others in their organization or online. Users can collaborate on projects and share insights with stakeholders.
Artificial Intelligence and Machine Learning: Power BI provides a range of AI and machine learning features such as natural language query, quick insights, and auto clustering that enable users to explore and gain insights into their data.

Disadvantages of Power BI:

Learning curve: Power BI can have a steep learning curve for beginners, especially those unfamiliar with data modeling and visualization.
Cost: While Power BI offers a free version, the full-featured version requires a subscription, which can be expensive for some users.
Limited data capacity: Power BI has a data capacity limit, which can limit its use for large organizations or data sets.
Limited customization: While Power BI offers a range of customization options, it can be limited compared to other BI tools.
Limited support for complex data structures: Power BI may need help with complex data structures and may require significant data transformation before using them effectively.

Difference between Tableau & Power Bi

Even though Tableau is a similar application that works by visualising data, there are some key differences between Tableau & Power Bi.

Price: Power Bi is cheaper than Tableau. There are different versions available for both applications. Power Bi’s professional version comes at 10 dollars per month, and Tableau’s pro version pricing is 35 dollars per month.
Performance: Power Bi is not suitable for handling a lot of data. It works the best when the data load is relatively less. On the other hand, Tableau supports large data volumes effortlessly.
Ease of access: Power Bi is a product of Microsoft, and therefore it is very user-friendly and easy to understand, but the Tableau interface is a bit tricky.
Organisations associated: Power Bi offers excellent service to medium data loads and is easy to understand; small-range organisations would benefit from Power Bi, whereas large-scale organisations should prefer Tableau.
Updation: Tableau has static functionalities, which means the user has to change the reports manually, unlike Power Bi, which supports dynamic reports and insights.

Power Bi – Data Analytics & Visualization​