Analyzing Data with Microsoft Power BI (DA-100日本語版): DA-100 Exam
"Analyzing Data with Microsoft Power BI (DA-100日本語版)", also known as DA-100 exam, is a Microsoft Certification. With the complete collection of questions and answers, Pass4sureCert has assembled to take you through 150 Q&As to your DA-100 Exam preparation. In the DA-100 exam resources, you will cover every field and category in Microsoft Certified: Data Analyst Associate Certification helping to ready you for your successful Microsoft Certification.
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Exam DA-100 Topics Covered
Test DA-100 measures the entrant's skills in 5 different domains:
- Modeling the data (25-30%)
This part of the final exam includes designing a data model. Here, the candidate should be able to define and configure tables along with having an idea about various dimensions and relationships. They are also required to be familiar with the concept of cardinality and cross-filter direction. After designing a data model, the applicant should be aware of how to develop it. Therefore, understanding of security filtering, calculated tables, hierarchies, and the implementation of row-level security roles will be beneficial. Furthermore, the entrants' expertise in working with DAX will be tested in this sector. They are required to be capable of using DAX for building complex measures, taking advantage of CALCULATE for manipulating filters using DAX with Time Intelligence, and more. In addition, this portion of DA-100 also involves the optimization of model performance by removing rows and columns, changing data types, managing aggregations, etc. Finally, the entrant should also know how to create semi-additive measures.
- Deployment and maintenance deliverables (10-15%)
The fifth and final section of DA-100 exam includes managing datasets. The candidate must be able to configure dataset scheduled refresh and row-level security. They are also expected to have an idea about giving access to data sets, incremental refresh settings, and certifying datasets. Moreover, the entrant is required to be well-informed about creating and managing workspaces. They should be able to create and configure workspaces, assign roles in the workspace, and manage the workspace app. Knowing how to import, export, update, and publish workspace assets will be essential. Finally, the candidate needs to know about applying sensitivity labels in workspace contents. The entrant also needs to be capable of identifying downstream data set dependencies and using deployment pipelines.
- Visualizing the data (20-25%)
The third domain will test the applicant's know-how of creating reports, dashboards, and enriching reports for usability. This will require the candidate's expertise in adding visualization to reports, choosing a proper visualization style, formatting visualizations, slicing and filtering applications, configuring a report page, building automatic page refresh, etc. The knowledge of R and Python visuals will also be beneficial. Furthermore, it is also essential for the entrant to know how to set dashboard to mobile view, manage tiles, configure data alerts, arrange aspects of the dashboard, and pin live reports. Finally, the applicant needs to enrich the reports by configuring bookmarks, creating custom tooltips, sorting & configuring various Sync Slicers, designing reports for mobile devices, etc.
- Preparation of data (20-25%)
The first domain for DA-100 exam consists of questions that will test the candidate's understanding of data retrieval from various sources. Thus, applicants should be able to identify the data source and connect to it, modify the source settings, select and create various data sets, pick a storage mode, etc. In addition, the examinee should be familiar with the concept of data profiling and have to be able to identify anomalies, study data structures, and examine column properties as well as data statistics. This section also includes cleaning, transforming, and loading data. This means that the entrant must know how to resolve inconsistencies, transform column data types, combine queries, solve data import errors, and more. This topic will also include Microsoft Dataverse, the usage & creation of a PBIDS file, and data flow after the changes are incorporated.
- Analyzing the data (10-15%)
In the fourth tested area, the candidate will be asked to enhance reports for exposing insights. This means complying with the need to be well-informed about conditional formatting, slicers, filters, Analytics pane along with a few other concepts. Besides, candidates must be able to add Quick Insights results to reports and use Q&A visuals. Likewise, the exam-taker should be able to know how to execute the advanced analysis. This involves the understanding of outliers, Timer Series analysis, groupings, binning, dimensional variances, decompositions tree visuals, and AI Insights. The exam also requires an understanding of the Play Axis feature and the personalization of visuals.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/da-100
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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 |
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