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DA-100 Exam Facts
Microsoft DA-100: Analyzing Data with Microsoft Power BI is an associate-level certification test. It is developed to measure the expertise of the professionals in preparing, modeling, visualizing, and analyzing data. Furthermore, the exam evaluates the proficiency of the individuals in deploying and maintaining deliverables. In addition, it validates the applicants’ comprehension of data processing and data repositories both on-premises and in Cloud. Those who nail the test will get the related certificate that is Microsoft Certified: Data Analyst Associate.
The most suitable applicants for the Microsoft DA-100 certification test are the specialists who are interested in evaluating their skills in the domain of data analysis. The exam does not have any formal prerequisites. At the same time, the professionals should have competence in designing and building scalable data models as well as transforming and cleaning data. Moreover, they need to have the ability to enable advanced analytic capabilities, which provide meaningful business value through easy-to-comprehend data visualizations.
The Microsoft DA-100 test has a length of 3 hours. Microsoft doesn’t tell much about the number of the entailed questions but be ready to encounter about 40 to 60. The exam is delivered in several languages, including Spanish, French, German, English, Korean, Japanese, and Chinese (Simplified). It is important to add that Microsoft DA-100 is a proctored test and requires that the applicants pay the registration fee of $165. The registration process can be done via Pearson VUE.
Before you start your preparation process, you should get familiar with the topics of the exam. Here are the highlights of them:
Within the first subject area, the test takers need to demonstrate their competence in using Microsoft Dataverse, parameters, Power BI Desktop Source file, and data flow. Furthermore, this part checks the skills of the individuals in changing data source settings and connecting to a dataset utilizing the XMLA endpoint as well as resolving inconsistencies, null or unexpected values, and data quality issues. In addition, it covers applying user-friendly value replacements, applying data shape transformations to table structures, and applying user-friendly naming conventions to columns and queries.
The focus of this section is to measure the expertise of the specialists in creating common date tables, calculated tables, hierarchies, calculated columns, and semi-additive measures. Moreover, it concentrates on implementing row-level security roles, object-level security, and Time Intelligence utilizing DAX. Besides that, the examinees should possess competence in using Data Analysis Expressions to build complex measures, using CALCULATE to manipulate filters, and using Query Diagnostics.
The questions from this topic are dedicated to assessing the skills of the students in adding visualization items to reports, setting conditional formatting, adding R or Python visual, and creating custom tooltips. Moreover, this part includes editing and setting interactions between visuals, setting Sync Slicers, drilling down into data utilizing interactive visuals, exporting report data, and designing reports for mobile devices.
The purpose of this module is to validate the proficiency of the examinees in applying conditional formatting and AI Insights as well as using the Q&A visual and Play Axis feature of visualization. In addition, this area covers performing top N analysis, exploring statistical summary, personalizing visuals, and conducting Time Series analysis.
In the framework of the last part, the learners are required to show their experience in setting dataset scheduled refresh, row-level security group membership, large dataset format, and subscriptions. Moreover, the topic checks the competence of the individuals in configuring incremental refresh settings and using deployment pipelines as well as creating and configuring a workspace and configuring and updating a workspace app.
Those students who plan to take the Microsoft DA-100 exam should think about the preparation process in advance. There are many resources that they can consider. Below you may find some examples:
If you prefer to work with an experienced mentor, you can consider utilizing the instructor-led training course that is available on the exam webpage. This course focuses on ingesting, cleaning, and transforming data as well as modeling data for performance and scalability. Furthermore, it can help the students develop their skills in designing and creating reports for data analysis. Besides that, this training option concentrates on applying and performing advanced report analytics, managing and sharing report assets, and creating paginated reports in Power BI. It should be noted that the course has some prerequisites. First of all, the applicants should possess experience in working with data in Cloud. Moreover, they need to have knowledge of core data concepts as well as data analysis and visualization concepts. In addition, the learners should have proficiency in working with relational data and non-relational data in Cloud. The course has the duration of 4 days and can be taken in Chinese (Simplified), Korean, Japanese, and English.
At the same time, if you prefer to prepare for the exam on your own, you can think about using the official learning paths. They are online self-preparation modules. There are several paths and each of them concentrates on a specific area. One of them covers Microsoft data analytics, while other online modules focus on data modeling, data visualization, data analysis in Power BI. In addition, there is a learning path that is dedicated to workspaces and datasets management in Power BI. More information about these materials can be found on the Microsoft site.
As mentioned earlier, those individuals who pass the Microsoft DA-100 exam will obtain the Microsoft Certified: Data Analyst Associate certificate. The professionals with this certification can think about various positions. Some of the job roles that these specialists can explore include a Business Analytics, an Analytics Manager, a Data Scientist, and a Data Analyst, among others. The median salary outlook for these titles is $62,000 per annum. However, the real salary will depend on various factors, including one’s experience in the field, country of living, employer, and so on.
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