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

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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.

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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.

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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.
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