Power BI Interview Guid : Most asked Interview Questions for Freshers

Power BI Interview Guid : Microsoft created Power BI, a potent business intelligence (BI) application. It enables users to gather, examine, and present data from multiple sources in order to derive insightful knowledge. Power BI can convert unprocessed data into interactive dashboards, reports, and visualizations by establishing connections with various data sources. You can track performance, spot patterns, and make educated decisions with the help of these graphics.

A specialist in developing and modifying Power BI solutions is known as a Power BI Developer. They are in charge of creating, constructing, and maintaining reports, dashboards, and other data visualizations. The majority of Power BI developers possess a solid grasp of data modeling, data analysis, and visualization methods. They must also be adept at using Power BI’s tools, including Power Query for data transformation and DAX (Data Analysis Expressions) for data manipulation. In order to give businesses a competitive edge and enable them to make data-driven decisions, Power BI developers are essential.

Here is your Power BI Interview Guid : Most asked Interview Questions for Freshers

1.What is Power BI Desktop

The free standalone program Power BI Desktop enables users to design and develop Power BI dashboards and reports. It includes a full collection of tools and capabilities for data modeling, analysis, and visualization. With Power BI Desktop, you can connect to numerous data sources, clean and manipulate data using Power Query, develop complex data models using DAX, and design interactive visualizations.  

After creating your reports and dashboards in Power BI Desktop, you can share and view them with others by publishing them to the Power BI service. With Power BI Desktop, you can create bespoke BI solutions that are suited to your company’s unique requirements in a flexible and configurable environment.

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2.What is Power Query?

Excel and Power BI Desktop come with Power Query, a potent tool for acquiring and transforming data. Users can establish connections with a variety of data sources, such as files, databases, and internet services. You can import, shape, and clean data using Power Query once it’s connected before importing it into an Excel spreadsheet or Power BI model.

You can change data in Power Query in a number of ways, including filtering, sorting, grouping, merging, and adding. To clean and get your data ready for analysis, you can also use advanced transformations. When working with complicated and varied datasets, data professionals and analysts find Power Query to be an invaluable tool due to its user-friendly interface and robust features.

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3.What is DAX?

To generate calculated columns and measures in Power BI and Excel, using the formula language known as DAX (Data Analysis Expressions). It offers a strong and adaptable method for carrying out intricate computations and extracting information from your data. Aggregates, bespoke computations, and temporal intelligence operations can all be carried out with DAX formulae.

You may use DAX to build calculated columns that expand your dataset by adding new data depending on pre-existing values. Additionally, you may design measures to instantly perform calculations and aggregate data across many dimensions. You may do calculations using DAX’s extensive set of operators and functions, including SUM, AVERAGE, COUNT, IF, and many more. You can fully utilize your data and produce insightful Power BI representations by becoming proficient with DAX.

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4.What is a dashboard in Power BI?

A Power BI dashboard is an interactive one-page display that highlights important metrics and insights in an eye-catching way. It is intended to give a quick, high-level summary of crucial business data. Dashboards can include a variety of visualizations, including tables, charts, graphs, and maps, and can be tailored to match individual requirements.

Consider a dashboard as an electronic scorecard that provides an overview of the success of particular projects or your company. Through the skilful integration of several visualizations, you can use your data to create an engaging narrative. Dashboards are useful instruments for decision-makers because they make it easier to see possible problems, track performance, and identify patterns.

5.Explain how relationships are defined in Power BI Desktop? 

Relationships are built in Power BI Desktop to create links between tables based on shared fields. This lets you do more sophisticated analysis and build more intricate data models. The primary key in one table and the foreign key in the other are specified when you define a relationship. In order to guarantee reliable data joins, these keys need to have matching values.

Power BI Desktop’s Relationships view can be used to establish relationships. You may see a diagram of your data model here, with tables shown as boxes. You just need to drag and drop a field from one table onto another to establish a relationship. After automatically analyzing the variables, Power BI will recommend a relationship type. The relationship type and cardinality (one-to-one, one-to-many, or many-to-many) can also be manually specified.

6. What are filters in Power BI?  

Power BI filters are tools that let you focus and adjust your data analysis. They give you the ability to choose particular data subsets according to a variety of standards, including conditions, values, and ranges. You may separate out pertinent data and produce more focused visualizations by using filters.

With Power BI, you can apply filters at the page, report, and visual levels, among other levels of organization. Report-level filters impact every visualization in the whole report, whereas page-level filters are applicable to every visualization on a particular page. Visual-level filters are applied to specific visualizations so you can personalize the information shown in every table and chart.

7.What are some common data shaping techniques?

The process of converting unprocessed data into a format appropriate for analysis is known as data shaping. To handle inconsistencies, inaccuracies, and missing values, this frequently entails cleaning, organizing, and rearranging the data. Typical methods of data shaping include the following:

• Data cleaning: This entails locating and fixing data abnormalities, inconsistencies, and inaccuracies. Among the methods are those for dealing with missing values, eliminating duplication, and fixing data types.
• Data normalization: Creating distinct tables for similar data is a common step in this process of arranging data into a structured format. This enhances data integrity and lessens redundancy.
• Data aggregation: This entails merging information from several sources or condensing information into a more manageable style. Among the methods include generating summary tables, averaging, and classifying data according to predetermined standards.
• Data transformation: This entails changing the format or structure of the data to satisfy particular analysis needs. Methods include pivoting data, dividing columns, and altering the type of data.
• Data enrichment: This is supplementing the data with new information in order to increase its worth. Methods include constructing calculated fields or combining data from other sources.

8.What is the use of the INDEX function?

Excel’s INDEX function is a strong tool that lets you get a value out of a particular cell or range by using its row and column numbers. When you don’t have a specific reference to the cell but know the position of the value you want to find, it’s especially helpful.

For instance, you can use the INDEX function to discover the column containing the April sales figure if you have a table of sales data and you want to find the total sales for the month of April. With the use of functions like MATCH, you may combine the INDEX function to make dynamic formulas that adjust to variations in your data.

9.What are custom visualizations?

In Power BI, custom visualizations are those that you design in addition to the pre-built choices the platform offers. They enable you to create one-of-a-kind, customized visualizations that more accurately depict your data and satisfy particular requirements. You may visualize your data in more logical, interesting, and educational ways by creating bespoke visualizations.

You’ll usually need to use a development environment like Visual Studio and have some familiarity with web development tools like HTML, CSS, and JavaScript in order to design a bespoke visual. React and D3.js are two examples of frameworks and libraries that can be used to create custom visuals. Once developed, you can share and allow others to use your custom visual by publishing it to the Power BI marketplace.

10.  What is Power View?

Using Power View, a feature of Power BI, you can generate visually beautiful, interactive reports that are simple to share and comprehend. It offers an easy-to-use drag-and-drop interface for creating dashboards and data displays. In order to assist you in meaningfully visualizing your data, Power View provides a range of chart formats, such as pie charts, bar charts, line charts, and maps.

A single Power View report can have many views created in it, giving you the ability to examine your data from various angles. Additionally supported by Power View are filters and slicers, which let you delve further into your data analysis and focus on particular elements. All things considered, Power View is an effective tool for producing interesting and educational reports that can assist you in making decisions based on facts.

11.Explain the filled map in Power BI.

A sort of visualization known as a “filled map” in Power BI shows geographic data on a map, with various colors or patterns denoting changing values of a certain metric. This makes it simple to spot abnormalities, trends, and patterns in many areas or places.

When displaying geographically spread data, such as sales numbers by nation, population density by state, or crime statistics by city, filled maps are especially helpful. You may convey the geographic distribution of your data quickly and effectively by utilizing different colors or patterns to represent distinct data values. Custom base maps, satellite imagery, road maps, and other map formats can all be added to filled maps.

12.How do you create a group in Power BI?

In Power BI, grouping is an effective method for arranging and classifying data into meaningful categories. This can facilitate the understanding of complex datasets, enhance visualization, and simplify analysis.

• Identify the column: Choose which column you wish to group. This could be a numerical column (like age, sales) or a categorical column (like product category, region).
• Right-click and select “New group”: Select “New group” from the context menu by performing a right-click on the column header.
• Create groups: Decide which values you would want to see in each group. Groups based on numerical criteria can be created by using ranges or by manually selecting individual numbers.
• Name your groups: Assign relevant names to each group that appropriately convey the essence of the group.

13.What is the Time Intelligence function?

You can do calculations across predetermined time periods with the help of temporal intelligence functions, which are an effective tool in data analysis. They are especially helpful in business analytics, where it’s critical to comprehend trends, compare performance across time, and spot abnormalities. With the help of these date-based functions, you can compute measures like growth from quarter to quarter, moving averages, and year-to-date totals.

You can generate dynamic reports that automatically change according to the current date by utilizing time intelligence functions. This will give you real-time insights into your data. You may use this to find opportunities, make well-informed decisions, and quickly resolve any possible problems. The functions DATEADD, DATESBETWEEN, DATESINPERIOD, and TOTALYTD are examples of common time intelligence functions. You may work with dates, make date ranges, and compute values across predetermined intervals of time with these tools.

14.Name the different connectivity modes available in Power BI?

SQL Server Import: In Power BI, it’s the most popular and default connectivity option. The user can fully utilize Power BI Desktop with SQL Server Import. Running queries on SQL Server data may be accomplished with ease by connecting it to Power BI.

Direct Query: Direct searches can be run on datasets larger than what is advised. In this scenario, Power BI will just keep the source’s metadata and run direct queries against it. It does, however, restrict the actions you may take to get your data ready for reporting.

Live Connections: Live data sources including SQL Server Analysis Services, Power BI Datasets provided by Power BI Service, and Azure Analysis Service can all be connected to using Power BI Service. Direct inquiries will be used for all interactions during a live connection.

15.Describe the role of data warehouses and data marts.

Data warehouses function as centralized storage facilities for the historical information gathered from multiple sources by an organization. They provide data access for analysis and reporting by combining data from several systems into a single, standardized format. A data warehouse can be compared to an extensive library of an organization’s data, offering decision-makers a single source of truth.

Smaller, more specialized portions of a data warehouse, data marts are created to specifically address the analytical requirements of a given department or business unit. They take pertinent information out of the warehouse and format it for that department—sales, marketing, or finance, for example—so that it meets their needs. With its more granular perspective of the data, data marts make it possible to analyze the data more quickly and precisely for particular business purposes.

16.What is row-level security?

A database security feature called row-level security (RLS) limits access to particular rows of data in a table according to the role or permissions of the user. Greater control over data visibility is possible with RLS as opposed to conventional database- or table-level security.

Organizations can guarantee that only authorized individuals can access sensitive information by putting RLS into place. A manager may have access to client data for all areas, whilst a sales representative may only be able to examine data for their own region. RLS aids in protecting against illegal access, upholding regulatory obligations, and preserving data privacy.

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