Login Get started

Power BI Full Course - Learn Power BI in 4 Hours | Power BI Tutorial for Beginners | Edureka

edureka!・209 minutes read

Power BI is an essential tool for data management, offering modules on data visualization, dashboards, and BI basics, catering to a wide range of users. Its components, updates, and features make it a versatile and powerful choice for organizations seeking to transform raw data into actionable insights.

Insights

Power BI is a leading data management tool for visualizing and organizing data.
Business Intelligence transforms raw data into actionable insights for decision-making.
BI has evolved through three waves: IT to end-user, analyst to end-user, and empowerment of all end-users.
Data visualization is crucial for simplifying complex data into visual formats.
Power BI enables real-time trend spotting, custom visualizations, and enterprise-grade data connections.
Power BI components include Power Query, Power Pivot, Power View, Power Map, and Data Management Gateway for data connectivity and visualization.

Get key ideas from YouTube videos. It’s free

Recent questions

What is Power BI?
Power BI is a tool for data management, visualization, and organization.
Who can benefit from Power BI?
IT professionals, developers, companies, subject matter experts, and analytics enthusiasts.
What are the components of Power BI?
Power Query, Power Pivot, Power View, Power Map, Power BI Services, Power BI Q&A, and Data Management Gateway.
How does Power BI aid in data visualization?
It allows real-time trend spotting, hidden insights search, custom visualizations, and enterprise-grade data connections.
How does Power BI compare to Tableau?
Power BI excels in custom visuals and data import capabilities, while Tableau offers curated visualizations and drill-down features.

Related videos

Summary

00:00

Power BI: Leading Tool for Data Management

Power BI is a leading tool for data management, aiding organizations and individuals in visualizing and organizing data.
The Power BI Full Course covers modules on introduction to Power BI, Power BI Desktop, Power Charts, KPI indicators, dashboards, a comparison with Tableau, and interview questions.
Business Intelligence (BI) involves transforming raw data into useful information for making business decisions.
BI has evolved through three waves: IT to end-user, analyst to end-user, and empowerment of all end-users.
Data visualization is crucial for conveying complex data in a simple, visual manner.
Power BI allows real-time trend spotting, hidden insights search, custom visualizations, and enterprise-grade data connections.
Power BI is suitable for IT professionals, developers, companies, subject matter experts, and analytics enthusiasts.
Power BI is a Microsoft business analytics service offering interactive visualization and self-service BI capabilities.
Power BI benefits include pre-built dashboards, real-time updates, secure data connections, intuitive data exploration, Microsoft product integration, and quick deployment.
Power BI components include Power Query, Power Pivot, Power View, Power Map, Power BI Services, Power BI Q&A, and Data Management Gateway for data connectivity and preparation, data modeling, data visualization, map exploration, service delivery, natural language querying, and data management.

18:10

"Power BI: Gateway, Catalog, Architecture, Visualization, Insights"

To connect on-premise servers with Power BI in the cloud, the Data Management Gateway must be configured and available to your tenant.
Power BI Data Catalog stores metadata for facilitated search functionality in Power BI, allowing shared queries with search access lists for users and security groups.
Power BI's architecture consists of three phases: data integration, data processing, and data presentation.
Data integration involves extracting data from various sources, standardizing it, and storing it in a staging area.
Data processing includes cleaning and transforming data, applying business rules, and loading it into a data warehouse.
Data presentation involves visualizing data using Power BI's various visualization types like charts, graphs, and maps.
Power BI's building blocks include visualizations, data sets, reports, dashboards, and tiles.
Visualizations represent data visually through graphs, charts, and maps, aiding in gaining insights.
Data sets are collections of data that can be filtered and combined from various sources to create visualizations.
Reports, dashboards, and tiles in Power BI help in presenting visualizations and insights in a structured and intuitive manner.

34:21

"Power BI: Creating Visualizations and Dashboards"

Power BI can automatically detect and join data from different tables based on relationships.
The Modeling tab in Power BI allows for data format changes, such as sorting and converting numbers to currency.
The Canvas view in Power BI is where visualizations are created, with options for multiple canvas pages.
Visualizations in Power BI can be modified by resizing and changing colors for emphasis.
Publishing reports in Power BI is simple, with options to overwrite or rename previous publications.
Dashboards in Power BI are a compilation of visualizations from different reports, providing real-time data for decision-making.
Creating a dashboard involves pinning visualizations and sharing them with colleagues or partners.
Power BI offers predefined sizes for visualizations in dashboards, with options to modify and share them easily.
Sharing dashboards in Power BI can be done by email or by copying and pasting a URL, with the ability to allow recipients to share as well.
Power BI Desktop is essential for creating reports and dashboards, with workspaces for reports, data, and relationships.

48:57

Visualizing Game Data with Various Charts

Tick rate is the number of times a game refreshes in a second, with a good rate being 128.
Slope of the graph indicates a tick rate of 128.48.
Area graph can also represent tick rate.
Combination chart combines bar and line charts for data visualization.
Ribbon chart shows data with respect to the maximum measure.
Pie chart visually represents data breakdown, while a donut chart is similar but with a hollow center.
Donut charts are preferred for readability, while pie charts are used for percentage breakdowns.
Tree maps display data hierarchy.
Maps in Power BI can show data density and player locations.
Funnel charts show progress stages and can be color-coded for better visualization.

01:04:54

Creating and Customizing KPIs in Power BI

Green colors are good, red colors are bad, and yellow colors are neutral.
A measure called "progress" can be created in the model to return a string.
The progress column can be added to a card in the model.
A power KPI tool can be added by going to the Home tab and selecting it from the marketplace.
Actual and target values can be dropped into the values field for the KPI.
Formatting options for the KPI can be adjusted in the formatting pane.
A custom KPI indicator can be obtained from the marketplace and used like any other visualization.
Different chart types can be selected for the KPI, such as line chart, line no marker, or bar chart.
Slicers can be added to interact with different charts in Power BI.
Dashboards in Power BI are single pages with visualizations tailored to specific requirements.

01:18:41

"Visualize Profit Leaders on State Map"

To rename a movie report, double click on the title and change it to "profit leaders."
Create a visualization by combining different states and their profits on a map.
Add profit details to the visualization to show differences in size.
Filter the data by adding details with respect to the country.
Use filters to select specific countries and visualize profits by state.
Change colors to differentiate between positive and negative profit-making states.
Use the field map system to represent profit values with color intensity.
Customize color settings by adjusting minimum, middle, and maximum values.
Choose the type of visualization based on the data being represented.
Identify profitable and non-profitable regions by filtering data by category and region.

01:31:59

"Analyzing Profit Data for Strategic Improvement"

The text discusses analyzing profit data, focusing on regions with negative profit.
It highlights the importance of identifying regions with high sales but low profit.
The text introduces the concept of trendlines and x-axis constant lines for analysis.
It explains the significance of dividing regions into quadrants for prioritization.
Quadrant three is identified as the highest priority for improvement due to negative profit.
Quadrant two is the second priority for enhancing sales and profit.
The text delves into segment-wise performance analysis using subcategories in a clustered bar chart.
It suggests representing the data in different ways for a comprehensive understanding.
The text then explores revenue generated by product categories over time using a line chart.
It concludes with instructions on creating a dashboard in Power BI, including pinning visuals and sharing reports.

01:45:48

"England Leads Sales and Profit Analysis"

The state with the highest sales is England, leading in sales among all states.
England also ranks highest in profit, although the values have changed from the sales data.
When comparing profit and sales, a scatterplot is generated, offering a different perspective.
Power BI and Tableau are discussed as two prominent tools in business intelligence and data visualization.
Power BI excels in custom visuals and data import capabilities, while Tableau offers curated visualizations and drill-down features.
In terms of cost, Power BI is initially cheaper, but Tableau may be more cost-effective in the long run considering labor and total usage costs.
Power BI integrates well with various Microsoft products, while Tableau offers a more curated approach to integration.
Power BI stands out in data shaping and modeling with its query editor and DAX power pivot, providing ease and efficiency.
Functional parameters like year of establishment, applications, support, and scalability are compared between Power BI and Tableau.
Self-service business intelligence is explained as an approach enabling business users to analyze data independently, enhancing speed and control in data analysis.

01:58:41

"Power BI: Essential Tool for Data Reporting"

Building reports in data requires basic understanding
Challenges of traditional BI and other top tools should be discussed
Power BI is a small part of the BI landscape dominated by tools like Tableau and Spotfire
Microsoft's self-service BI solution includes XLBI and Power BI toolkits
Power BI components include Power Query, Power Pivot, Power View, and Power Map
Power BI Desktop is a client tool for development, while Power BI Service is cloud-based
Power BI ecosystem consists of Power Query, Power Pivot, Power View, Power Map, Data Management Gateway, Power BI Q&A, and Power BI Service
Power BI is frequently updated, with monthly updates for Desktop and weekly updates for Service
Q&A feature is available in both Service and Desktop, recently added as a preview feature in Desktop
Power BI Desktop allows easy data connection and visualization, with features like Q&A accessible through preview settings.

02:09:15

Power BI desktop: Simplifying data analysis and visualization.

Power BI desktop allows for easy Q&A features, enabling users to ask questions and visualize data instantly.
Power Query in Power BI desktop serves as the ETL component, focusing on basic data cleansing and transformation operations.
Data from sources is typically considered dirty and requires cleaning before analysis.
Power Query involves connecting to data sources, performing basic ETL operations, and setting data types accurately.
Power Pivot in Power BI desktop functions as an in-memory columnar database for data visualization.
Power BI desktop and Excel share similarities in their components and processes, emphasizing the importance of understanding both tools.
Power Map in Excel and Power BI desktop offers powerful mapping features for data visualization.
Power BI desktop connects to various sources, including files, databases, and online services, with the ability to set up ODBC connections.
Web data connectivity in Power BI desktop simplifies the process of extracting tabular data from websites without the need for complex scripting.
Power BI desktop allows for easy sharing and publishing of reports and dashboards in a cloud environment, enabling collaboration within organizations.

02:19:47

"Effortless data extraction with Power BI"

The process involves connecting to a website to access tables, which may take time based on the connection speed.
A list of available tables is presented after establishing a connection with the site.
Initially, there may be issues with the connection, resulting in incomplete table displays.
The tool scans an entire website for HTML structures to compile the tables.
It allows for easy selection and extraction of data from the website.
Content packs, also known as apps, offer pre-built dashboards and reports for various sources.
Bing Maps is an example of a content pack that can be easily installed and utilized.
Power BI's self-service capabilities enable users to create reports and dashboards effortlessly.
The service allows for editing reports but not building models or conducting query editing.
Different types of filters in Power BI include visual, page, report, and drill-through filters, each serving specific filtering purposes.

02:30:23

"Power BI: Filtering, Drill Through, Dax"

Filtering by Central and East, not Central T's on page two is a double filter.
Implement a report level filter to apply a filter across all pages in a report.
Report level filter allows consistent filtering across all pages.
Drill through feature enables detailed filtering based on selections.
Drill through filter allows navigation to specific categories or subcategories.
Drill through filter configuration should be placed on the page being configured.
Drill through feature allows detailed exploration of data across multiple pages.
Dax is a functional language in Power BI for creating calculated columns and measures.
Power Query uses M code, while Power Pivot uses Dax for calculations.
Calculate function in Dax helps in calculating percentages and totals in reports.

02:40:57

"Dynamic Star Ratings and Efficient Calculations"

New features and updates are regularly added to the system, such as time intelligence calculations and star ratings.
Star ratings allow users to assign a value, like 250,000, and rate it with stars, creating a dynamic star rating column.
Behind the scenes, complex Dax formulas are generated by Power BI for quick measures and default options.
The star rating column adjusts dynamically based on the underlying data's granularity, showing varying star values.
Calculations like percentage of individual sales can be done using Dax formulas, such as dividing sum of sales by total sales.
The "calculate" function in Dax helps in evaluating expressions in a filter context, allowing for precise calculations.
Measures in Power BI are dynamic and adjust based on changes in data, providing flexibility in calculations.
Variables in Dax can be used to avoid redundancy and repetition in code, enhancing efficiency.
Time intelligence functions like "calculate all" and "filter" can be utilized in various scenarios to create different calculations.
Calculated columns and measures serve different purposes, with calculated columns aggregating data at the row level and measures aggregating data at a higher level, ensuring accurate results.

02:51:47

"Measures Over Averages: Power BI Essentials"

Building a model using averages leads to incorrect outputs; measures are the correct method.
Measures are dynamically calculated on-the-fly and not stored in the model.
Measures recalculate when filters are applied or changed in visuals.
Measures are responsive to filters and recalculated based on defined aggregations.
Measures are essential for percentage calculations and divisions.
Calculated columns consume more memory as they are stored in the model, unlike measures.
Measures may strain resources due to dynamic calculation but offer faster evaluation.
Measures can reduce processing and refresh performance on large fact tables.
Power Pivot's modeling layer utilizes DAX for calculated columns and measures.
Data models in Power BI consist of tables, columns, rows, and relationships, crucial for visualizing data across multiple tables.

03:02:40

"ETL Tools Enhance Data Transformation Efficiency"

ETL tools are crucial for shaping, cleansing, and transforming data.
Queries in M code are a combination of steps that can be built into multiple queries.
Query folding enhances performance by transferring operations to the data source.
Native queries and view native queries are visible when connecting to a SQL server.
Query folding transfers operations from Power BI to the data source, improving efficiency.
Parameters in Power BI act as dynamic filters, allowing for customized data views.
Parameters can be set up in the query editor and applied to filter data dynamically.
Parameters help load only necessary data, improving performance and efficiency.
Power Query is an ETL tool that imports data from various sources for analysis.
Power Pivot is distinct from Power Query, focusing on analytics rather than data cleansing.

03:13:18

Setting Geographical Data Types in Power BI

When working with map data, set the geographical data type to see a small globe sign.
The small globe sign indicates that the data is categorized as geographical.
Ensure to set the data type for city, country, and postal code to avoid unwanted summarization.
Postal codes should not be summarized as they are unique identifiers.
Set postal code as a geographical type to display the globe sign.
Set the data type for state to accurately represent geographical information.
Use the maps feature in Power BI to visualize geographical data.
Power BI offers custom visual maps for advanced visualization options.
Replicate the process of setting data types for city, state, postal code, country to ensure accurate geographical representation.
Utilize gateways for data refresh in Power BI, especially when connecting to on-premise sources.

03:24:21

"Seamless Power BI and Excel Integration Tips"

Seamless integration between Power BI and Excel allows for easy data transfer in both directions.
To move data from Excel to Power BI, use Power BI Publisher for Excel.
Sign in to your service, hit publish, and pin the data to your dashboard.
Implement data security in Power BI using roles, creating separate roles for different regions.
Set up filter expressions for each role based on region, ensuring data confidentiality.
Preview roles to see how data will be displayed for different users.
Implement many-to-many relationships in Power BI by creating a bridge table.
Use edit interactions to specify how visuals on the same page interact with each other.
SSRS integrates seamlessly with Power BI, allowing for easy dashboard creation and pinning.

Try it yourself — It’s free.