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Understanding functional and technical aspects of Exam DA-100: Analyzing Data with Microsoft Power BI Deploy and maintain deliverables

The following will be discussed in MICROSOFT DA-100 exam dumps:

• Create and configure a workspace
• Recommend a development lifecycle strategy
• Create and manage workspaces
• Configure incremental refresh settings
• Configure row-level security group membership
• Configure a dataset scheduled refresh
• Apply sensitivity labels to workspace content
• Manage datasets
• Use deployment pipelines
• Providing access to datasets
• Assign workspace roles
• Publish, import, or update assets in a workspace
• Configure and update a workspace app
• Promote or certify Power BI content
• Identify downstream dataset dependencies

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

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Microsoft DA-100 Deutsch Exam Syllabus Topics:

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

Exam Topics

Microsoft expects that the successful candidates get the passing score of 720 points on a scale of 100-1000. This mark is achievable if you put your mind to it. To succeed, you must understand the Microsoft DA-100 exam topics that are as follows:

1. Data Preparation (20-25%):

This part includes the following areas:

• Cleaning, loading, & transforming data: This subject area requires that the students understand how to combine queries, utilize user-friendly value substitutions, solve data import errors, transform and measure column data types, and configure the data loading. It also covers their skills in applying data shape transformations for table structures and user-friendly conventional naming for queries and columns. The individuals should also have the expertise in leveraging Advanced Editor or modifying Power Query M-code.
• Collecting data from various data sources: The candidates must be able to connect and identify data sources, alternate data source settings, and choose storage mode and shared datasets, or build local datasets. They also need the capacity to select the relevant query type, utilize parameters, Microsoft Dataverse, create or use PBIDS files, and data flow.
• Data profile: The test takers should have competence in interrogating data statistics and column properties as well as identifying data anomalies and evaluating data structures.

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