#1. |
Connect Power BI Desktop to an external data source such as a SQL database or an online API.
Outline the
process of establishing the connection, including providing the necessary credentials and selecting
the relevant
tables or endpoints. Discuss the benefits of connecting to external data sources using Power BI
Desktop
compared to using Power BI Service. |
#2. |
Compare and contrast the concepts of DirectQuery and importing data in Power BI Desktop. Create a
scenario
where DirectQuery would be the preferred approach, and another scenario where importing data would
be
more suitable. Discuss the implications of each approach on data freshness, performance, and the
ability to
leverage Power BI Desktop's transformation capabilities. |
Section 3 - Modelling with Power BI
- Introduction to Modeling
- Setup and Manage Relationships
- Cardinality and Cross Filtering
- Default Summarization & Sort by
- Creating Calculated Columns
- Creating Measures & Quick Measures
- Recap and What's Next
S.No |
Question |
*1. |
Create a Power BI model using multiple tables and demonstrate how to set up and manage
relationships
between them. Explain the concept of cardinality and its significance in determining how
tables are related.
Provide an example where one-to-one, one-to-many, and many-to-many relationships are
utilized. |
*2. |
Explore the default summarization and sorting options in Power BI. Choose a specific
scenario and modify the
default summarization and sorting behavior for a given measure or column. Justify your
modifications based
on the specific analysis requirements and discuss the potential impact on data visualization
and analysis. |
*3. |
Design a Power BI report that includes custom measures for performing calculations on
aggregated data. Create
measures for calculating metrics such as total sales, average revenue per customer, or
year-over-year growth.
Additionally, explore the Quick Measures feature in Power BI and demonstrate how to leverage
it to quickly
generate commonly used calculations. |
S.No |
Question |
#1. |
Develop a Power BI report that showcases the cross-filtering feature. Include
visualizations that demonstrate
how applying filters on one table affects the data displayed in related tables. Discuss the
impact of cardinality
on cross-filtering behavior and provide guidelines on handling scenarios where unexpected
filtering results
occur. |
#2. |
Create a calculated column in Power BI based on a given dataset. Explain the purpose of
calculated columns
and provide step-by-step instructions on how to define and implement the calculation using
DAX expressions.
Discuss the considerations for choosing between calculated columns and measures in different
analytical
scenarios. |
#3. |
Summarize the key concepts and techniques covered in the "Modeling with Power BI" module.
Provide a
summary of the best practices for designing an efficient and effective data model in Power
BI. Discuss
advanced modeling features, such as calculated tables, bidirectional relationships, and
role-playing dimensions,
and suggest further resources for users to explore these advanced topics. |
Section 4 - Power BI Desktop Vusualisations
- Creating Visualisations
- Color & Conditional Formatting
- Setting Sort Order
- Scatter & Bubble Charts & Play Axis
- Slicers
- Tooltips
- Cross Filtering and Highlighting
- Visual, Page and Report Level Filters
- Drill Down/Up
- Hierarchies
- Constant Lines
- Tables, Matrices & Table Conditional Formatting
- KPI's, Cards & Gauges
- Map Visualisations
- Custom Visuals
- Managing and Arranging
- Drillthrough
- Custom Report Themes
- Grouping and Binning
- Bookmarks & Buttons
- Decomposition Tree
S.No |
Question |
*1. |
Develop an interactive sales dashboard using Power BI Desktop. Include visualizations such
as bar charts, line
charts, and scatter plots to display sales performance over time, by product category, and
by region. Apply
conditional formatting to highlight top-performing products and regions. Add slicers for
users to filter data by
time period, product category, or region. |
*2. |
Visualize employee performance metrics using Power BI Desktop. Create KPI visualizations
to track metrics
such as sales targets, customer retention rates, or call resolution time. Utilize custom
visuals or gauges to
display performance against targets. Apply tooltips to provide additional context or
explanations for each
metric. |
*3. |
Build a custom visual dashboard using Power BI Desktop. Explore the Power BI marketplace
for custom
visuals and select a custom visual that aligns with your project requirements. Incorporate
the custom visual
into your dashboard and integrate it with other native visualizations. Apply advanced
functionalities such as
cross-filtering and hierarchical drill-down to enhance the interactivity of the custom
visual dashboard. |
S.No |
Question |
#1. |
Analyze customer satisfaction ratings using Power BI Desktop. Create a gauge or card
visualization to display
the overall satisfaction score. Utilize conditional formatting to visually indicate
different satisfaction levels.
Apply drill-down functionality to allow users to explore satisfaction scores by different
dimensions such as
product, region, or customer segment. |
#2. |
Create a geographic sales map using Power BI Desktop. Import a dataset with location
information and sales
data. Utilize the map visualization to display sales figures by region or city. Apply color
coding to represent
sales intensity or growth rates. Implement tooltips to display detailed sales information
when hovering over
specific locations. |
Section 5 - Power BI Service Visualisation Tools
- Introduction to the Power BI Service
- Standalone Tiles
- Data Driven Alerts (Power BI Pro/Premium)
- Quick and Related Insights
- Custom Q&A
S.No |
Question |
*1. |
Create a standalone tile dashboard in Power BI Service using relevant datasets. Choose key
metrics, such as
sales revenue, customer satisfaction, or website traffic, and create visually appealing
tiles to display these
metrics. Configure the tiles to refresh automatically and provide drill-through capabilities
for detailed analysis. |
*2. |
Explore the Quick Insights and Related Insights features in Power BI Service. Choose a
dataset containing
various dimensions and measures, such as sales data by region and product category. Use
Quick Insights to
automatically generate visualizations and identify patterns or trends in the data. Then,
utilize Related Insights
to discover additional relevant information or correlations within the dataset. |
*3. |
Develop an interactive insights dashboard in Power BI Service using a combination of
visualizations and the
features mentioned in the topic. Choose a dataset with rich dimensions and measures, such as
customer
behavior data or financial metrics. Design a comprehensive dashboard that incorporates
standalone tiles, datadriven alerts, quick and related insights, and a custom Q&A experience
to provide a holistic and interactive
analytics solution. |
S.No |
Question |
#1. |
Configure data-driven alerts in Power BI Service based on specific metrics or thresholds.
Choose a dataset with
real-time or regularly updated data, such as stock prices or website performance metrics.
Set up alerts to notify
users when certain conditions are met, such as stock prices exceeding a certain threshold or
website downtime
exceeding a specified duration. |
#2. |
Create a custom Q&A experience in Power BI Service for a specific dataset. Design a set of
natural language
questions and provide appropriate answers using Power BI's Q&A capabilities. Incorporate
synonyms and
alternative phrasing to ensure accurate and intuitive responses. Test and refine the custom
Q&A experience
based on user feedback and improvement opportunities. |
Section 6 - Publishing and Sharing
- Sharing Options Overview
- Publish from Power BI Desktop
- Publish Reports to Web
- Sharing Reports & Dashboards (Power BI Pro/Premium)
- Workspaces (Power BI Pro/Premium)
- Apps (Power BI Pro/Premium)
- Printing, PDFs and Exporting to PowerPoint
- Row Level Security (Power BI Pro)
- Export Data from a Visualisation
- Publishing for Mobile Apps
- Sharing Options Summary
S.No |
Question |
*1. |
Publish a sales report created in Power BI Desktop to the Power BI Service. Walk through
the steps involved
in publishing, including signing in to Power BI, selecting the appropriate workspace, and
configuring the
necessary settings. Discuss the benefits of publishing from Power BI Desktop compared to
creating reports
directly in the Power BI Service. |
*2. |
Share a report and dashboard with specific collaborators in Power BI Service. Demonstrate
the process of
granting access to selected individuals, controlling their level of permissions, and
managing their access rights.
Discuss the collaborative features available in Power BI Pro and Power BI Premium, such as
real-time
collaboration and commenting. |
*3. |
Apply row-level security in a Power BI report to restrict data access based on user roles
and permissions.
Create multiple user roles and demonstrate how to define security rules that filter data
based on the logged-in
user's role. Discuss the considerations for implementing row-level security and the
limitations based on the
Power BI license type. |
S.No |
Question |
#1. |
Publish a report to the web in Power BI Service, making it publicly accessible without
requiring user
authentication. Explain the considerations and limitations of sharing reports publicly, such
as data privacy and
security concerns. Discuss how to embed the published report on a website or share the link
for wider
dissemination. |
#2. |
Create an app in Power BI Service to bundle and distribute reports and dashboards to a
specific audience. Walk
through the steps of creating an app workspace, adding reports and dashboards to it, and
configuring access
and navigation settings. Discuss the benefits of using apps for targeted content
distribution and the differences
between Power BI Pro and Power BI Premium for app creation and consumption. |
Section 7 - Refreshing Datasets
- Understanding Data Refresh
- Personal Gateway (Power BI Pro and 64-bit Windows)
- Replacing a Dataset
- Troubleshooting Refreshing
S.No |
Question |
*1. |
Configure data refresh settings for a dataset in Power BI Service. Walk through the steps
involved in setting up
scheduled refreshes and selecting the appropriate refresh frequency. Discuss the factors to
consider when
determining the refresh frequency based on the data source's update frequency and the
business requirements. |
*2. |
Implement incremental refresh for large datasets in Power BI Premium. Choose a dataset
with a significant
volume of data and demonstrate how to configure incremental refresh settings to load only
the delta or updated
data. Discuss the benefits of using incremental refresh, such as improved performance and
reduced data
storage requirements, and any limitations or considerations associated with its
implementation. |
*3. |
Replace an existing dataset with an updated version while maintaining the existing reports
and dashboards.
Demonstrate the steps involved in replacing the dataset, ensuring that the reports and
dashboards continue to
function correctly after the replacement. Discuss the considerations for managing refresh
dependencies and
minimizing disruption during the dataset replacement process. |
S.No |
Question |
#1. |
Install and configure the Personal Gateway in Power BI Service for refreshing datasets
hosted on an onpremises data source. Discuss the prerequisites, installation process, and
configuration steps involved.
Highlight any potential challenges or troubleshooting tips that may arise during the setup.
|
#2. |
Encounter and troubleshoot common dataset refresh issues in Power BI Service. Choose
specific scenarios,
such as connection failures, data source authentication errors, or data transformation
issues, and provide stepby-step guidance on identifying and resolving the problems. Discuss
best practices for troubleshooting refresh
issues and provide tips for proactive monitoring and maintenance. |
Section 8 - Power BI and Excel Together
- Options for Publishing from Excel
- Import Excel Power Query & Power Pivot Models
- Analyze in Excel (Power BI Pro or Premium)
- Excel Publish: Upload and Export to Power BI
- Sharing Published Excel Dashboards (Power BI Pro or Premium
S.No |
Question |
*1. |
Explore the options for publishing data from Excel to Power BI Service. Compare and contrast the methods
available, such as uploading Excel files directly to Power BI, using Power Query and Power Pivot models, or
utilizing the "Analyze in Excel" feature. Discuss the advantages and limitations of each method in terms of
data connectivity, data modeling capabilities, and visualization options. |
*2. |
Utilize the "Analyze in Excel" feature in Power BI Service to connect and analyze Excel data. Select a dataset
from Excel and analyze it using Excel's familiar interface and advanced features. Discuss the advantages of
using "Analyze in Excel" for users who are more comfortable with Excel's functionalities and explore the
possibilities of creating interactive reports and dashboards within Excel. |
*3. |
Share an Excel-based dashboard published in Power BI Service with other users. Walk through the steps of
granting access, managing permissions, and defining collaboration settings for the shared Excel dashboard.
Discuss the collaboration and sharing capabilities available in Power BI Pro and Power BI Premium when
working with published Excel dashboards. |
S.No |
Question |
#1. |
Import an Excel file containing Power Query and Power Pivot models into Power BI Desktop. Walk through
the process of connecting to the Excel file, selecting the relevant tables or queries, and importing them into
Power BI Desktop. Discuss the benefits of leveraging Power Query transformations and Power Pivot data
modeling capabilities when working with Excel data in Power BI. |
#2. |
Upload an Excel dashboard to Power BI Service and explore the process of exporting Excel dashboards to
Power BI. Discuss the steps involved in uploading the Excel file, configuring the data refresh settings, and
publishing the dashboard. Explore the benefits and limitations of using Excel as a dashboard creation tool in
conjunction with Power BI Service. |