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What career bonuses will you get after passing the Microsoft DA-100 exam?

The certifications from a renowned vendor such as Microsoft enhance the chances of the professionals to land a decent job. The individuals with the Microsoft Certified: Data Analyst Associate certificate are also at an advantage because this option validates their skills and competence in a specific technical domain. Some of the job titles that the certified specialists can pursue include a Data Analyst, a Business Analyst, a Mobile Test Analyst, a Revenue Analyst, and a Quantity Assurance Analyst. The average salary for these experts is $105,000 per annum.

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

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:

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

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Difficulty in Attempting Exam DA-100: Analyzing Data with Microsoft Power BI

However, if you would like to use different source data/tables in the same project, link them together and perform transformations on the data in Power BI as well, then the level of difficulty increases. Learning this will take of course more time. What we believe will also help is to get a general understanding of how data cleansing works and data integration in general. We offer MICROSOFT DA-100 practice exams and MICROSOFT DA-100 practice test for this purpose.

Analyzing Data with Microsoft Power BI Certification helps candidates in developing their professionals and academic career and it is a very tough task to pass Microsoft DA-100 exam for those candidates who have not done hard work and get some relevant Microsoft DA-100 exam preparation material. There are many peoples have passed Microsoft DA-100 exam by following these three things such as look for the latest Microsoft DA-100 exam dumps, get relevant MICROSOFT DA-100 exam dumps and develop their knowledge about Microsoft DA-100 exam new questions. At the same time, it can also stress out some people as they found passing Microsoft DA-100 exam a tough task. It is just a wrong assumption as many of the peoples have passed Microsoft DA-100 exam questions. All you have to do is to work hard, get some relevant Microsoft DA-100 exam preparation material and go thoroughly from them.

Compared to other visualization tools we would recommend that Power BI is quite user friendly and is relatively easy to learn. What also contributes to this is that the Power BI desktop version is available for free, resulting in a pretty large user base on the internet, which is beneficial to your learning curve, as in our experience answers to particular questions can be found easily most of the times.

More about DA-100 Exam

This test focuses on technical domains such as structuring data, using DAX to create measures, making a data model, acquiring data from numerous sources, and preparing and analyzing data. Also, it checks one’s skills in interpreting reports, revealing data insights, forming dashboards, visualizing data, handling datasets, and lastly, incorporating and maintaining deliverables. The registration fee for DA-100 is $165. The test is available in numerous languages including Japanese, Chinese, Korean, and English. DA-100 can be taken at local physical centers or online under proctored conditions.

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Microsoft DA-100日本語 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Deploy and maintain deliverables10%- Create and manage workspaces
  • 1. Create and configure a workspace
  • 2. Configure and update a workspace app
  • 3. Assign workspace roles
- Manage datasets
  • 1. Configure cross-workspace sharing
  • 2. Configure row-level security group membership
  • 3. Provide access to datasets
  • 4. Configure a dataset scheduled refresh
Topic 2: Model the data30%- Design a data model
  • 1. Define quick measures
  • 2. Define a relationship's cross-filter direction and security filtering
  • 3. Define the tables
  • 4. Configure table and column properties
  • 5. Design and implement role-playing dimensions
- Create measures by using DAX
  • 1. Use DAX aggregation functions
  • 2. Create semi-additive measures
  • 3. Create calculated measures
  • 4. Use DAX logical functions
  • 5. Implement Time Intelligence using DAX
- Optimize model performance
  • 1. Improve performance by identifying and removing unnecessary rows and columns
  • 2. Optimize Power Query transformations
  • 3. Improve performance by choosing optimal data types
- Develop a data model
  • 1. Implement row-level security roles
  • 2. Create calculated columns
  • 3. Create calculated tables
  • 4. Create hierarchies
Topic 3: Analyze the data15%- Perform advanced analysis
  • 1. Use the Analyze feature
  • 2. Use advanced analytical custom visuals
  • 3. Identify outliers
  • 4. Perform What-if analysis
- Enhance reports for usability and storytelling
  • 1. Configure bookmarks
  • 2. Group and layer visuals
  • 3. Configure sync slicers
  • 4. Configure navigation for a report
  • 5. Create custom tooltips
  • 6. Apply sorting
  • 7. Edit and configure interactions between visuals
Topic 4: Visualize the data25%- Enforce accessibility
  • 1. Configure tab order
  • 2. Design accessible reports
  • 3. Use accessibility features
- Create reports
  • 1. Apply slicing and filtering
  • 2. Configure conditional formatting
  • 3. Format and configure visualizations
  • 4. Choose an appropriate visualization type
  • 5. Create and manage bookmarks
  • 6. Add visualization items to reports
  • 7. Import a custom visual
- Create dashboards
  • 1. Configure data alerts
  • 2. Manage tiles on a dashboard
  • 3. Set mobile view
  • 4. Use the Q&A feature
Topic 5: Prepare the data20%- Profile the data
  • 1. Interpret data distribution and variance
  • 2. Examine data structures
  • 3. Identify data anomalies
- Get data from different data sources
  • 1. Change data source settings
  • 2. Identify and connect to a data source
  • 3. Select a shared dataset or create a local dataset
  • 4. Choose an appropriate Power BI data source
  • 5. Select a storage mode
- Clean the data
  • 1. Resolve data import errors
  • 2. Resolve inconsistencies, unexpected or null values, and data quality issues
  • 3. Evaluate data, including data statistics and column properties
- Transform and load the data
  • 1. Define relationship cardinality and cross-filter direction
  • 2. Design a star schema
  • 3. Create and transform tables
  • 4. Create and transform columns
  • 5. Select appropriate column data types

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