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Career Opportunities and Pay

After getting through with DA-100 exam and earning the Microsoft Certified: Data Analyst Associate certification, you will be able to offer more for big business companies that need more analytical power that Excel cannot provide. This opens up multiple job opportunities with decent average annual salaries. Below are some of them as covered by Payscale:

• Data Analyst: $61k;
• Web Data Analyst: $67k.
• IT Operation Analyst: $56k;

5. Deliverables Deployment and Maintenance (10-15%):

The topics for this part are the following:

• Workspaces creation and management: The test takers must have competence in assigning workspace roles, using deployment pipeline, updating and configuring workspace apps, and applying sensitivity labels for workspace content. It also requires their skills in importing, updating, and publishing assets in workspaces, as well as recommending the development lifecycle strategy.
• Datasets management: In the framework of this subtopic, the applicants will be evaluated based on their skills in configuring incremental refresh settings, dataset scheduled refresh, and group membership for row-level security. It will also measure their skills in providing access to the datasets and certifying or promoting Power BI content.

Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/da-100

How to Prepare for Exam DA-100: Analyzing Data with Microsoft Power BI

Preparation Guide for Exam DA-100: Analyzing Data with Microsoft Power BI

Introduction for Exam DA-100: Analyzing Data with Microsoft Power BI

Analyzing Data with Microsoft Power BI certification demonstrates your expertise in analyzing data with both Power BI. This certification is for data analysts who are responsible for designing and building scalable data models, cleaning, transforming, and analyzing data. The exam includes questions about Data preparation, tools, queries and tables, visualization types and support, dashboards creation. Data Analysts also collaborate with IT and business teams to ensure that data analysis is providing business value.

PracticeMaterial offers detailed exam dumps and MICROSOFT DA-100 practice exams and MICROSOFT DA-100 practice test to prepare candidates, who are going to be data analysts in the future, to prepare and pass this exam in the first go.

Exam DA-100: Analyzing Data with Microsoft Power BI will allow you to learn:

• Perform Quick Data Analysis with Power BI

With the help of Power BI, you can collect your company's data, whether it's located in the cloud or locally, and provides quick and easy access to this data - all without having to ask any human being for help.

• Generate Accurate Interactive reporting

Your customers can see all data on one screen and the Power BI Mobile apps are automatically updated with changes to your data so you can access updated data and reports, no matter where you are.

• Financial overview

Companies of a certain size can benefit from Power BI's analytical reporting features and the ability to access their data across multiple devices.

• How Power BI is user friendly

With the help of Power BI innovative tools, you can easily find out what data you want to see and how the results will look like. The tool allows you to switch between different formats in order to give you a more visual representation of your data. Power BI can also connect to a wide variety of databases and information sources, including cloud-based sources such as Azure SQL Database, Oracle, Salesforce.com, Amazon Redshift, Dropbox Business, Google Analytics Premium, and Tableau Online.

• Power BI Data Visualization

Power BI makes productive and creative. You no longer need to go through complex processes without leaving the Power BI interface. The benefit of this process is that you can, as a company, focus on the data and actions of your customers rather than creating lengthy reports and documents to satisfy them. It combines data from multiple sources into a single, standardized, format.

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Exam DA-100 Topics Covered

Test DA-100 measures the entrant's skills in 5 different domains:

• 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.

• 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.

• 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.

• 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.

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