We will examine some of the most significant interview questions related to the Power BI Certification in this blog post, which will help you stand out in your interview. Microsoft made the decision to merge several add-ons for Excel in order to produce Power BI, which was launched in late 2013. The key driver of Microsoft's expansion in the fields of business intelligence and data visualisation in 2016–17 has been Power BI. According to Gartner, the following firms have moved up or down in the Data Visualization domain:
We've included the top queries that interviewers frequently ask about Power BI in this article. After talking with leading industry professionals in the fields of data analytics and visualisation, these inquiries were compiled.
Microsoft created Power BI to unify the many data visualisation
functionalities. The data-driven sector has a new name, Power BI, which means it has a lot of prospects ahead of it. It comes as a set of three significant parts:
Power BI services
Power BI Desktop
Power BI mobile app
With these three elements, Power BI enables you to develop a data-driven understanding of your company. You may use Power BI to your advantage in a variety of positions by creating reports, keeping track of progress, integrating APIs, and more.
Considering that Power BI offers a simple method for everyone, even non-technical employees, to connect, modify, and visualise their raw business data from several sources into valuable data that makes it simple to make wise company judgments.
Technology is the driving force behind business intelligence. It assists you in data analysis and in providing information that can be put to use, enabling corporate leaders, company managers, and other users to make informed business decisions.
VPN and cloud computing are two technologies that could link two offices spread across different regions.
Unprocessed data that can be received from a variety of data sources can be analysed and visualised by users of PowerBI, a cloud-based business intelligence tool. Any company can use it to help them make data-driven business decisions because it blends business analytics with data visualisation. The data has been processed in a way that makes it dependable and easy to understand, and it is simple to utilise. It is available from several platforms and can be shared with on-cloud users. This makes it a workable solution.
It is a language for formula expression known as (DAX), which can be utilised with a variety of visualisation tools like Power BI. Because the entire code is contained within a function, it is also known as a functional language.
The following are PowerBI's main components:
One of the most crucial parts of PowerBI for data transformation is Power Query. Data extraction from multiple data sources, such as Oracle, SQL, Text/CSV files, Excel, and others, is made simpler by Power Query. It also makes it easier to delete data from various sources.
Data modelling that uses DAX (Data Analysis Expression) routines for the calculations is done using Power Pivot. Here, we may also construct relationships between several tables and obtain values for Pivot Tables.
Power View: The Power View is used to obtain metadata for data analysis and to present data in an easily understandable way. Slicers and filters can be used to slice and dice the data, and the views are interactive in nature.
Power Query, Power View, and Power Pivot may all be integrated with Power BI Desktop. It aids in the development of your BI skills for data analysis and makes it easier to design complex queries, data models, reports, and dashboards.
Mobile Power BI Application: It is compatible with Android, iOS, and even Windows operating systems. The app offers an interactive dashboard display that may also be shared.
Power Map: It provides a three-dimensional geospatial display of the data. The geographic location of the data, which can be a continent, state, city, or even a street address, can be highlighted.
Power Q&A: It is used to respond to queries submitted by users. Power Q&A can respond to it with illustrations and works with Power View.
There are presently three versions of PowerBI:
Use Microsoft PowerBI Free/Desktop if you want to see your business insights from the data.
The full version of PowerBI, Microsoft PowerBI Pro, allows for unlimited report reading, reporting, and sharing—features that PowerBI Desktop does not provide.
Microsoft PowerBI Premium - The Power BI Premium licence gives each user in the organisation access to a single dedicated unit of capacity; it is not a per-user licence.
Data View: Curating, investigating, and visualising the data set's data tables. With data view, as opposed to Power Query editor, you can see the data after it has been fed to the model.
Model View: This view displays all of the tables as well as the intricate relationships between them. With this, you may deconstruct these intricate models into easier-to-understand diagrams or give them all the same features.
Report View: To make data analysis simpler, the report view presents the tables in an interactive fashion. Create as many reports as you like, add visuals, combine them, or use any other functionality.
The dashboard resembles a single-page canvas on which you may draw and visualise reports produced by data analysis using a variety of elements. To build a tale, it uses only the most crucial
information from the reports.
The dashboard's visual components are referred to as Tiles. These tiles from the reports can be pinned to the dashboard. Any element on the dashboard can be clicked to see the report for a specific data collection.
Content packs are collections of several Power BI objects, including datasets, reports, and dashboards. There are two categories of content packs:
Service providers offer pre-built content packages, like Google Analytics, Salesforce, and others.
User-generated content packs: Users can create and distribute their own content packs within the company.
You may import millions of rows from many data sources into one Excel sheet with Power Pivot. It enables us to make connections between different tables, add columns, perform calculations with formulas, and produce PivotCharts and PivotTables. There can only ever be one active relationship between the tables at a time, which is shown by a continuous line.
The following are the key distinctions between Power BI and Tableau:
Tableau utilises MDX while Power BI uses DAX to calculate a table's columns (Multidimensional Expressions).
Tableau is more effective since it can handle more data than Power BI, which can only handle a small quantity.
Using Tableau is more difficult than using Power BI.
There are two types of table relationships:
Manually - Primary and foreign keys are used to define relationships between tables.
When activated, Power BI's automated feature automatically finds and establishes associations between tables.
Data is sorted by filters according to the criteria they are given. With the aid of filters, we can pick out specific fields and extract data at the page, visualisation, and report levels.
For the Indian subcontinent, for instance, filters can reveal sales information from the year 2019. Based on the criteria, Power BI can alter the data and produce new graphs or visuals.
Various filters include:
Page-level filters: These are used to narrow down the pages that appear in a report on a certain page.
Filters at the visualisation level: These are used for certain visualisations' data and calculation criteria.
Filters that apply to the entire report are called report-level filters.
Data is graphically represented through visualisation. Reports and dashboards can be created using visualisations. Bar charts, column charts, lines, areas, stacked areas, ribbon charts, waterfall charts, scatter charts, pie charts, donut charts, treemap charts, maps, funnel charts, gauge charts, cards, KPI, slicer, tables, matrices, R script visuals, Python visuals, and other visualisation types are among the visualisation types offered by Power BI.
Services are offered by Power BI for its cloud-based business analytics. Through the Power BI website, you may view and share reports using these services. A web-based service for sharing reports is called Power BI. PowerBI.com, PowerBI workspace, PowerBI site, or PowerBI portal are the most appropriate names for the Power BI service.
In Power BI, there are three primary connectivity modes.
SQL Server Import
The default and most popular connectivity type utilised by Power BI is a SQL Server Import. It enables you to utilise all of the Power BI Desktop's features.
Only when you connect to particular data sources is the Direct Query connection type possible. Power BI will only save the metadata of the underlying data in this type of connectivity, not the actual data itself.
This sort of link prevents data from being stored in the Power BI model. Every Live Connection query made in response to a report will directly query the current Analysis Services model. Only 3 data sources—SQL Server Analysis Services (Tabular models and Multidimensional Cubes), Azure Analysis Services (Tabular Models), and Power BI Datasets housed in the Power BI Service—support the live connection approach.
Both Fact tables and Dimension tables in a data warehouse are where we store all the data that we input into Power BI from various data sources. All of the measure (quantitative data) values
are contained in the fact tables, which are the central/main table of a start schema. It has primary keys, and the fact table is connected to all of the dimension tables. Usually, the
fact table is not standardised.
A database table called a dimension table, on the other hand, houses all the attribute values (data about data) for the data recorded in a fact table. In a star schema, each dimension table is connected to a fact table.
Types of visuals are:
Custom visual files.
Yes, a SQL query can be used as the starting point for a Power Query/M function to perform additional processing or logic. By doing this, one can ensure that a useful database query is sent to the source and reduce the amount of processing and complexity that the client machine and M function must perform.
It mainly comprises three steps:
Data Integration: Extracting and integrating data from various data sources comes first. Following integration, the data is transformed into a common format and kept in a location known as the staging area.
Data processing: After the data has been put together and integrated, it needs to be cleaned up. Since raw data is not very valuable, it undergoes a few transformations and cleaning processes to get rid of unnecessary numbers, etc. Data warehouses are where the transformed data is kept after transformation.
Data Presentation: After the data has been transformed and cleansed, it is displayed visually as reports, dashboards, or scorecards on the Power BI desktop. These reports can be distributed to different corporate users online or through mobile apps.
With the help of Power BI, both technical and non-technical users may manage, examine, visualise, and share data with others. The presentation of data and insights through eye-catching images is one of its primary aspects. Maps are one of the graphics offered by power BI.
Bidirectional cross-filtering is one of Power BI's most significant capabilities. With the help of this functionality, you can apply filters to both sides of a table relationship and calculate them in both the right-to-left and left-to-right directions. This allows modellers to precisely understand how certain relationships can function in various settings.
The xVelocity in-memory analytics engine is the key driving force behind power pivot. Because it stores data in columnar databases and performs in-memory analytics, which speeds up data processing by loading all data into RAM memory, it can manage massive amounts of data.
Some of the variations are as follows:
Security, computed tables, bidirectional cross-filtering connections, and Direct Query options are all supported by Power BI Desktop.
Power Pivot for Excel only supports calculated columns, relationships with a single direction (one to many), and import mode. Power Pivot for Excel does not support the definition of security roles.
You can connect to several data sources using "Get Data" in PowerBI to import data for analysis and visualisation. In order to import the needed data, you can choose from a variety of different data sources. Text/CSV, Excel, PDF, JSON, Amazon Redshift, SQL Server, Access, SAP HANA, IBM, MySQL, Oracle, Impala, Google BigQuery, etc. are a few examples.
When steps from a Power Query or Query Editor are converted to SQL and run by the source database rather than the client system, this is known as query folding. Given the client machine's restricted resources, it's crucial for processing performance and scalability.
Excel may already have the data or it may be available elsewhere. Make sure that all of your data is organised in an Excel table structure, with each row denoting a distinct item. Instead of actual data, your column or row headings should have text so that Power Map can properly comprehend them when plotting the coordinates. When you construct your tour in the Power Map Tour Editor pane, value and category fields become available to you when you use relevant labels.
A bridge or junction table that reflects the combinations of two dimensions is involved in many-to-many connections (e.g. doctors and patients). Either all potential pairings or those that have already happened.
In Power BI, there are four different sorts of refreshes. model or data refresh, tile refresh, visual container refresh, and package refresh.
By doing this, your Power BI Desktop or Excel file is synced with OneDrive or SharePoint Online and the Power BI service. This, however, does not obtain information from the original data source. Only the information contained in the file stored in OneDrive or SharePoint Online will be updated for the dataset in Power BI.
In the context of the Power BI service, it alludes to updating the dataset with information from the original data source. Either scheduled refresh or refresh now can be used for this. A gateway for on-premises data sources is necessary for this.
When data changes, tile refresh updates the cache for tile visuals on the dashboard. About every fifteen minutes, this occurs. Selecting the ellipsis (...) in the top right of a dashboard and choosing Refresh dashboard tiles will also cause a tile refresh.
Visual container refresh
Once the data changes, refreshing the visual container updates the cached report graphics, within a report.
Calculated Columns are DAX expressions that are generated for each row of the specified column during the model's processing/refresh process and may be utilised just like any other column.
Calculated columns don't use compression, therefore they use more memory and have a negative impact on query performance. They can also hinder processing/refresh performance when used on big fact tables and can make maintaining and supporting a model more challenging because the calculated column is absent from the source system.
Select the fields you wish to group in Power Bi, then right-click on them to reveal the context menu. Choose the Group option from the menu, please.
Power BI will automatically group those things after you select the group option, as illustrated below. We completed the grouping; that's all. If you look attentively, you will see that group has taken the position of the legend part, and colour has been moved to the details section.
Visuals are arranged over forms using the design technique known as Z-order. It can also be described as a technique used to implement multiple-element reports. Additionally, this can be used to update the display if something in a report changes.
Data preparation before loading into the Power BI model is done using the query formula language M in the Power BI Query Editor.
Excel, Analysis Services, and Power BI workbooks are compatible with Power Query. Its primary capabilities are data filtering and combining, or data mashups, using one or more supported data sources with extensive collections. A Power Query M Formula Language expression is used to describe any such data mashup.
The methods for integrating SSRS with Power BI are as follows:
Charts from SSRS report items can be pinned to Power BI dashboards.
Users will be directed to SSRS reports by choosing the tile option in Power BI dashboards.
A subscription is made to keep the dashboard tile updated.
Reports from Power BI will be posted to the SSRS site.
Some drawbacks of PowerBI include:
The complexity of PowerBI's design is one of its biggest flaws. PowerBI must be completely understood before one can begin using it.
PowerBI is unable to process big amounts of data and may crash while doing so.
Data larger than 1 GB cannot be processed by PowerBI.
Only users who share the same domain or have their emails listed in Office 365 are able to see reports.
Although there are very few data sources that permit real-time connectivity to the PowerBI dashboards, PowerBI can connect to real-time data sets.
The only functions that let you change the filter context of measures or tables are these.
Context of current filters for queries is added.
override the query context filter.
Query context for existing filters should be removed.
Only one column can be used by filter parameters at once.
A metric cannot be referenced by a filter parameter.
Syntax: These are the parts of the formula that make it up. Functions like SUM are included in the syntax (used when you want to add figures). You'll see an error message
if the syntax is incorrect.