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4. Data Analysis (10-15%):
This section requires your skills in:
- Enhancing reports to expose insights: The candidates should have the expertise in personalizing visuals, applying filters & slicers and conditional formatting. They also need to demonstrate their skills in exploring statistical summary, creating reference lines with Analytics pane, and using Q&A visuals, among others.
- Caring out advanced analysis: This subject area covers your skills in identifying outliers, using binnings & groupings, conducting Time Series Analysis, and applying AI Insights. The students should also have competence in using decomposition tree visuals to dissect a measure and use Key Influencers for the exploration of dimensional variances.
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Understanding functional and technical aspects of Exam DA-100: Analyzing Data with Microsoft Power BI Visualize the data
The following will be discussed in MICROSOFT DA-100 exam dumps:
- Add an R or Python visual
- Enrich reports for usability
- Configure the report page
- Choose an appropriate visualization type
- Pin a live report page to a dashboard
- Configure conditional formatting
- Use the Q&A feature
- Edit and configure interactions between visuals
- Configure Sync Slicers
- Configure automatic page refresh
- Add a dashboard theme
- Add visualization items to reports
- Create dashboards
- Apply sorting
- Manage tiles on a dashboard
- Configure data alerts
- Drilldown into data using interactive visuals
- Configure bookmarks
- Configure data classification
- Set mobile view
- Design reports for mobile devices
- Format and configure visualizations
- Design and configure for accessibility
- Import a custom visual
- Apply slicing and filtering
- Export report data
- Use drillthrough and cross filter
- Create custom tooltips
- Configure navigation for a report
- Create reports
- Use the selection pane
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/da-100
Microsoft DA-100 Exam Syllabus Topics:
| Topic | Details |
|---|---|
Prepare the Data (20-25%) | |
| Get data from different data sources | - identify and connect to a data source - change data source settings - select a shared dataset or create a local dataset - select a storage mode - choose an appropriate query type - identify query performance issues - use Microsoft Dataverse - use parameters - use or create a PBIDS file - use or create a data flow - connect to a dataset using the XMLA endpoint |
| Profile the data | - identify data anomalies - examine data structures - interrogate column properties - interrogate data statistics |
| Clean, transform, and load the data | - resolve inconsistencies, unexpected or null values, and data quality issues - apply user-friendly value replacements - identify and create appropriate keys for joins - evaluate and transform column data types - apply data shape transformations to table structures - combine queries - apply user-friendly naming conventions to columns and queries - leverage Advanced Editor to modify Power Query M code - configure data loading - resolve data import errors |
Model the Data (25-30%) | |
| Design a data model | - define the tables - configure table and column properties - define quick measures - flatten out a parent-child hierarchy - define role-playing dimensions - define a relationship's cardinality and cross-filter direction - design the data model to meet performance requirements - resolve many-to-many relationships - create a common date table - define the appropriate level of data granularity |
| Develop a data model | - apply cross-filter direction and security filtering - create calculated tables - create hierarchies - create calculated columns - implement row-level security roles - implement object-level security - set up the Q&A feature |
| Create measures by using DAX | - use DAX to build complex measures - use CALCULATE to manipulate filters - implement Time Intelligence using DAX - replace numeric columns with measures - use basic statistical functions to enhance data - create semi-additive measures |
| Optimize model performance | - remove unnecessary rows and columns - identify poorly performing measures, relationships, and visuals - improve cardinality levels by changing data types - improve cardinality levels through summarization - create and manage aggregations - use Query Diagnostics |
Visualize the Data (20-25%) | |
| Create reports | - add visualization items to reports - choose an appropriate visualization type - format and configure visualizations - import a custom visual - configure conditional formatting - apply slicing and filtering - add an R or Python visual - configure the report page - design and configure for accessibility - configure automatic page refresh - create a paginated report |
| Create dashboards | - set mobile view - manage tiles on a dashboard - configure data alerts - use the Q&A feature - add a dashboard theme - pin a live report page to a dashboard |
| Enrich reports for usability | - configure bookmarks - create custom tooltips - edit and configure interactions between visuals - configure navigation for a report - apply sorting - configure Sync Slicers - use the selection pane - use drillthrough and cross filter - drilldown into data using interactive visuals - export report data - design reports for mobile devices |
Analyze the Data (10-15%) | |
| Enhance reports to expose insights | - apply conditional formatting - apply slicers and filters - perform top N analysis - explore statistical summary - use the Q&A visual - add a Quick Insights result to a report - create reference lines by using Analytics pane - use the Play Axis feature of a visualization - personalize visuals |
| Perform advanced analysis | - identify outliers - conduct Time Series analysis - use groupings and binnings - use the Key Influencers to explore dimensional variances - use the decomposition tree visual to break down a measure - apply AI Insights |
Deploy and Maintain Deliverables (10-15%) | |
| Manage datasets | - configure a dataset scheduled refresh - configure row-level security group membership - provide access to datasets - configure incremental refresh settings - promote or certify Power BI datasets - identify downstream dataset dependencies - configure large dataset format |
| Create and manage workspaces | - create and configure a workspace - recommend a development lifecycle strategy - assign workspace roles - configure and update a workspace app - publish, import, or update assets in a workspace - apply sensitivity labels to workspace content - use deployment pipelines - configure subscriptions - promote or certify Power BI content |
The benefit in Obtaining the Exam DA-100: Analyzing Data with Microsoft Power BI
Microsoft Power BI is a suite of business intelligence (BI), reporting, and data visualization products and services for individuals and teams. Power BI stands out with streamlined publication and distribution capabilities, as well as integration with other Microsoft products and services.
Through Power BI, users can:
- Embed Power BI visuals into Power BI apps
- Enable peer-to-peer sharing - a way to share published dashboards or reports with people outside the organization who have a Power BI Pro license
- Integrate with other Microsoft solutions, such as Azure data services
- Transform and model the data
- Create reports and dashboards that are collections of visuals
- Create charts and graphs
- Share reports with others using the Power BI service
- Connect to data
- Share data, dashboards, and reports with other Power BI users
- Create workspaces - places to collaborate with colleagues to create collections of dashboards and reports
Some other benefits are as follows:
- After completion of the exam, candidates receive official confirmation from Microsoft that they are now fully certified in their chosen field.
- Organization owners invest a lot in their employees when it comes to their training with the goal of making them quicker, more efficient, and more knowledgeable about their role. Certified Professional will reduce the time he spends on tasks, meaning he can get more done this could help reduce company downtime when repairing faults on a system or fixing hardware problems.
- Candidates will get in-depth knowledge by completing the courses along with the access to revision materials for 6 months upon completion means they will have a wider skill set when it comes to the various technologies and systems than an uncertified professional.
- Candidates will be able to apply that knowledge by experiencing hands-on use of a supported Microsoft product (e.g., Excel or PowerPoint). The exam will also help prepare individuals for the advanced data analysis skills required for more sophisticated reports and presentations.
- After completion of exam, candidates receive official confirmation from Microsoft that you are now fully certified in their chosen field. This can be now added to their CV, cover letters and job applications.
- When Candidates applying for a job or looking to promotion in their current position, a Microsoft certification in the field in which Candidates are applying will put you at the top of the list and make them a desirable candidate for employers.
- It will not only help those looking to become data analysts gain practical experience but also boost their chances of finding and securing employment.
- When candidates applying for a job or looking to promotion in their current position, a Microsoft certification in the field in which candidates are applying will put them at the top of the list and make them desirable candidates for employers.
