DA-100: Analysing Data with Microsoft Power BI Exam:

For the generation of business, the usage of Power BI is important. So to test the ability and understanding grip of using Power BI, the DA-100 is essential, which is associated with the role of a data analyst. Power BI is easy to learn and qualify, not very difficult as such, but hype automatically creates when the evaluation context stage takes place in the course. As you understand and get the knowledge of the evaluation context, you become the king of DAX.

With Power BI, we have all data and stats of our organization; if there is no Power BI, managers don’t even know what’s going wrong and from where it is the need to improve and can face the unhappy events within the organization. As we see in the near past, the machine’s efficiency has been evaluated and converted the raw material into the product’s nut. The data analyst will carry on these strategic tasks by using Power BI in the future.

This certification is, as we know, based on the Data Analyst role. Hence, knowing report making is enough, but maintaining security protocols, resolving security issues, and maintaining administrative rights is the main task within the workspace and Power BI.

For this, you have to get solid foundational concepts that can be easily done if you can mentally picture and continuously rehearse what could happen and the outcome. It will be very tough for you if you are unsure about the working of relationships in a data structure from where the Power BI starts. 

Objectives of DA-100 Analyzing Data With Microsoft Power BI:

There are five domains and key objectives of DA 100, so here I am describing them briefly:

Prepare the Data: (20 – 25%):

First, we have to identify the data source and connect it to it. Then the data source setting should be changed and create a local data set. Then for the data, we have to select storage mode. Query mode choosing process and identifying the issues in the queries take place next. Then the use of parameters, Microsoft Data verse, and data flow occurs, or the creation of Data flow is needed.

Then we will profile data by examining the data structure and interrogating the column properties and data stats. At last, the cleaning, transforming, and loading data take place by analysing and resolving issues with friendly replacements.

Model the Data: (25 – 30%):

Then we have to design a model using various techniques like first defining the table and then configuring the rows and columns with the properties. Measures should be taken quickly, and the hierarchy should be defined as per the set required. After this defining the dimensions and resolving issues of the data and table-use the tools like DAX. Replace the columns as needed with the numerics and at last but not least, create the semi-additive measures.

After this optimization takes place, the removal of unnecessary things takes place as the removal of extra rows and columns. The measured relationships or visuals that are not performing well should be identified then and after that by changing data types or summarization methods to improve levels co-ordinately. At last, the aggregation should be created and managed to complete the optimization.

Visualize the Data: (20 – 25 %):

In this task, first, we have to create a report by adding some visualization items into it. For this, we have to choose appropriate visuals and customize the report, then import it, and then the conditional formatting process. Then apply some filters to make it eye-catching and add python visuals. After this, the report page has to be configured and its accessibilities. At last, automatic page refresh should be configured.

Dashboard creation takes place by setting mobile views and applying tiles for a dashboard. Data alerts are then configured, Q&A features are used, a dashboard theme is applied, and pinning of the report page takes place, and at last, data classification is done.

At last, enrich your report for usability.

Deploy and Maintain Deliverables: (10 – 15%):

For this task, we have to Manage Data sets by configuring the scheduled refresh. After we provide access to data sets, incremental refresh settings are configured. Then certify the content of Power BI and identify the data set dependencies downstream.

Then create and manage the workspaces and recommend a developed lifecycle. Roles of workspace should be assigned, and the workspace app should be updated. Assets should be published and imported into the workspaces also to get, to obtain sensitive content on the workspaces. Deployment pipelines should be used at the last subscription should be configured.

DA-100 Exam Guide:

After knowing about DA-100 exam dumps guide objectives and course outlines, let’s discuss some important things related to exams so that you may know about them before applying.

• Exam duration = 180 minutes
• Multiple choice and multi-response questions both.
• It includes 40 – 60 questions.
• Scores to pass is 70%.
• Exam Cost 165$.
• Exam Domains: 5.

These are important things related to DA 100; DA 100 is considered a somewhat difficult exam to pass, so you should properly prepare yourself to pass this exam and qualify for exam certifications.

How Do I Clear the DA 100 Exam Certification?

DA 100 is an online exam to prepare it online, the learning path is available for DA 100 at the Microsoft site.

Also, you can follow these steps to clear your DA 100 exam:

1. Find a study partner, or you can join study groups.
2. Review the exam content first.
3. Run through Dashboard within a day.
4. Complete the DA 100 learning path.
5. You should gain real-world experience.
6. After studying for the DA 100 exam, purchase and schedule the DA 100 Exam.
7. You can prepare for your exam with the help of Exam dumps, pdf files, online lectures, and different courses.
8. You can also visit the DumpsOut website in this regard. You will indeed find helpful data to prepare for your DA 100 exam.

Conclusion:

DA 100 is an up-to-date Microsoft certification and can lead to a successful career. So you can apply for this exam if you are interested in this field.