This certification exam covers a range of skills that the applicants need to develop competency in before sitting for it. These skills are broken into topics and subtopics. Here are the highlights of the subject areas covered in Microsoft DA-100:
- Visualize Data: 20-25%
Within this domain, the examinees should possess the ability to create reports because the certification test will measure their capability to perform the technical tasks in this area. They will also need to demonstrate their skills in creating dashboards, including setting mobile view, using Q&A features, managing tiles on dashboards, and configuring data classification. The individuals should also be able to improve reports for usability. They will be required to demonstrate their skills in configuring bookmarks, applying to sort, creating custom tooltips, exporting report data, and configuring Sync Slicers.
- Maintain & Deploy Deliverables: 10-15%
The applicants for the Microsoft DA-100 exam should also have competence in managing datasets. This involves configuring datasets scheduled refresh, certifying or promoting Power BI content, and providing access to the datasets. The learners also need to have the skills in creating and managing workspaces, creating and configuring workspaces, assigning workspace roles, and using deployment pipelines.
- Prepare Data: 20-25%
This section of the certification exam will evaluate the ability of the candidates to acquire data from various data sources. They also must be able to profile data, which includes identifying data anomalies and examining data structure. It also requires interrogating data statistics and column properties. In addition, the test takers should have competence in cleaning, transforming, and loading the data. This involves resolving inconsistencies, identifying the relevant keys for joins, combining queries, and resolving data import errors.
- Analyze Data: 10-15%
This part will measure the competence of the students in improving reports to reveal insights. These include competence in applying conditional formatting, personalizing visuals, exploring statistical summary, and using Q&A visuals. It will also evaluate their skills in performing advanced analysis.
- Model Data: 25-30%
This topic equips the candidates with the skills and knowledge on how to design the data model. The questions from this subject area will measure their expertise in defining tables, quick measures, role-playing dimensions, cross-filter direction and relationship’s cardinality, and precise level of data granularity. It will also measure competence in the development of data models, creation of measures with the use of DAX, and optimization of model performance.
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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 |
Certification Path
After acquiring the Microsoft Certified: Data Analyst Associate certification, you are competent to go further and broaden your expertise in the Microsoft BI platform. Although this certificate is not a direct requirement for other BI-related validations, it will sure help you get started with the higher-level certifications like the Microsoft Certified: Dynamics 365 + Power Platform Solution Architect Expert.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/da-100
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