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PL-300 Practice Test - Microsoft Power BI Data Analyst | [HOSTED-SITE]
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Microsoft PL-300 : Microsoft Power BI Data Analyst Exam Dumps

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Latest 2024 Updated Microsoft Microsoft Power BI Data Analyst Syllabus
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PL-300 Test Center Questions : Download 100% Free PL-300 exam Dumps (PDF and VCE)

Exam Number : PL-300
Exam Name : Microsoft Power BI Data Analyst
Vendor Name : Microsoft
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Question Bank : Check Questions

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PL-300 Exam Format | PL-300 Course Contents | PL-300 Course Outline | PL-300 Exam Syllabus | PL-300 Exam Objectives


EXAM CODE: PL-300

EXAM NAME: Microsoft Power BI Data Analyst

PASSING SCORE: 700



The Power BI data analyst delivers actionable insights by leveraging available data and applying domain expertise. The Power BI data analyst collaborates with key stakeholders across verticals to identify business requirements, cleans and transforms the data, and then designs and builds data models by using Power BI. The Power BI data analyst provides meaningful business value through easy-to-comprehend data visualizations, enables others to perform self-service analytics, and deploys and configures solutions for consumption. Candidates for this exam should be proficient using Power Query and writing expressions by using DAX.



• Prepare the data

• Model the data

• Visualize and analyze the data

• Deploy and maintain assets



Prepare the data (15–20%)

Get data from different data sources

• Identify and connect to a data source

• Change data source settings

• Select a shared dataset or create a local dataset

• Select a storage mode

• Use Microsoft Dataverse

• Change the value in a parameterv
• Connect to a data flow

Clean, transform, and load the data

• Profile the data

• Resolve inconsistencies, unexpected or null values, and data quality issue

• Identify and create appropriate keys for joins

• Evaluate and transform column data types

• Shape and transform tables

• Combine queries

• Apply user-friendly naming conventions to columns and queries

• Configure data loading

• Resolve data import errors

Model the data (30–35%)

Design a data model

• Define the tables

• Configure table and column properties

• Design and implement role-playing dimensions

• Define a relationship's cardinality and cross-filter direction

• Design a data model that uses a star schema

• Create a common date table

Develop a data model

• Create calculated tables

• Create hierarchies

• Create calculated columns

• Implement row-level security roles

• Use the Q&A feature

Create model calculations by using DAX

• Create basic measures by using DAX

• Use CALCULATE to manipulate filters

• Implement Time Intelligence using DAX

• Replace implicit measures with explicit measures

• Use basic statistical functions

• Create semi-additive measures

• Use quick measures

Optimize model performance

• Remove unnecessary rows and columns

• Identify poorly performing measures, relationships, and visuals

• Reduce cardinality levels to improve performance

Visualize and analyze the data (30–35%)

Create reports

• Add visualization items to reports

• Choose an appropriate visualization type

• Format and configure visualizations

• Use a custom visual

• Apply and customize a theme

• Configure conditional formatting

• Apply slicing and filtering

• Configure the report page

• Use the Analyze in Excel feature

• Choose when to use a paginated report

Create dashboards

• Manage tiles on a dashboard

• Configure mobile view

• Use the Q&A feature

• Add a Quick Insights result to a dashboard

• Apply a dashboard theme

• Pin a live report page to a dashboard

Enhance reports for usability and storytelling

• Configure bookmarks

• Create custom tooltips

• Edit and configure interactions between visuals

• Configure navigation for a report

• Apply sorting

• Configure Sync Slicers

• Group and layer visuals by using the selection pane

• Drilldown into data using interactive visuals

• Export report data

• Design reports for mobile devices

Identify patterns and trends

• Use the Analyze feature in Power BI

• Identify outliers

• Choose between continuous and categorical axes

• Use groupings, binnings, and clustering

• Use AI visuals

• Use the Forecast feature

• Create reference lines by using the Analytics pane

Deploy and maintain assets (10–15%)

Manage files and datasets

• Identify when a gateway is required

• Configure a dataset scheduled refresh

• Configure row-level security group membership

• Provide access to datasets

• Manage global options for files

Manage workspaces

• Create and configure a workspace

• Assign workspace roles

• Configure and update a workspace app

• Publish, import, or update assets in a workspace

• Apply sensitivity labels to workspace content

• Configure subscriptions and data alerts

• Promote or certify Power BI content




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Microsoft Analyst Exam Questions

 

Boom in A.I. Prompts a Test of Copyright Law

The boom in artificial intelligence tools that draw on troves of content from across the internet has begun to test the bounds of copyright law.

Authors and a leading photo agency have brought suit over the past year, contending that their intellectual property was illegally used to train A.I. systems, which can produce humanlike prose and power applications like chatbots.

Now they have been joined in the spotlight by the news industry. The New York Times filed a lawsuit on Wednesday accusing OpenAI and Microsoft of copyright infringement, the first such challenge by a major American news organization over the use of artificial intelligence.

The lawsuit contends that OpenAI’s ChatGPT and Microsoft’s Bing Chat can produce content nearly identical to Times articles, allowing the companies to “free-ride on The Times’s massive investment in its journalism by using it to build substitutive products without permission or payment.”

OpenAI and Microsoft have not had an opportunity to respond in court. But after the lawsuit was filed, those companies noted that they were in discussions with a number of news organizations on using their content — and, in the case of OpenAI, had begun to sign deals.

Without such agreements, the limits may be worked out in the courts, with significant repercussions. Data is crucial to developing generative A.I. technologies — which can generate text, images and other media on their own — and to the business models of companies doing that work.

“Copyright will be one of the key points that shapes the generative A.I. industry,” said Fred Havemeyer, an analyst at the financial research firm Macquarie.

A central consideration is the “fair use” doctrine in intellectual property law, which allows creators to build upon copyrighted work. Among other factors, defendants in copyright cases need to prove that they transformed the content substantially and are not competing in the same market as a substitute for the work of the original creator.

A review quoting passages from a book, for example, could be considered fair use because it builds on that content to create new, unique work. Selling extended excerpts from the book, on the other hand, may violate the doctrine.

Courts have not weighed in on how those standards apply to A.I. tools.

“There isn’t a clear answer to whether or not in the United States that is copyright infringement or whether it’s fair use,” said Ryan Abbott, a lawyer at Brown Neri Smith & Khan who handles intellectual property cases. “In the meantime, we have lots of lawsuits moving forward with potentially billions of dollars at stake.”

It could be a while before the industry gets definitive answers.

The lawsuits posing these questions are in early stages of litigation. If they don’t produce settlements (as most litigation does), it could be years until a Federal District Court rules on the matter. Those rulings would probably be appealed, and appellate decisions could vary by circuit, which could potentially elevate the question to the U.S. Supreme Court.

Getting there could take about a decade, Mr. Abbott said. “A decade is an eternity in the market that we’re currently living through,” he said.

The Times said in its suit that it had been in talks with Microsoft and OpenAI about terms for resolving the dispute, possibly including a license. The Associated Press and Axel Springer, the German owner of outlets like Politico and Business Insider, have recently reached data licensing agreements with OpenAI.

Taking cases to trial could answer vital questions about what copyrighted data A.I. developers are able to use and how. But it could also simply serve as leverage for a plaintiff to secure a more favorable licensing deal through a settlement.

“Ultimately, whether or not this lawsuit ends up shaping copyright law will be determined by whether the suit is really about the future of fair use and copyright, or whether it’s a salvo in a negotiation,” Jane Ginsburg, a professor at Columbia Law School, said of the lawsuit by The Times.

How the legal landscape unfolds could shape the nascent yet heavily capitalized A.I. industry.

Some A.I. companies have been flooded with venture capital in the past year after the public rollout of ChatGPT went viral. A stock plan under consideration could value OpenAI at over $80 billion; Microsoft has invested $13 billion in the company and has incorporated its technology into its own products. But questions about the use of intellectual property to train models have been top of mind for investors, Mr. Havemeyer said.

Competition in the A.I. field may boil down to data haves and have-nots.

Companies with the rights to large quantities of data, such as Adobe and Bloomberg — or that have amassed their own data, such as Meta and Google — have started developing their own A.I. tools. Mr. Havemeyer noted that an established company like Microsoft was well equipped to secure data licensing agreements and tackle legal challenges. But start-ups with less capital may have a harder time obtaining the data they need to compete.

“Generative A.I. begins and ends with data,” Mr. Havemeyer said.

Benjamin Mullin contributed reporting.


Analyst: Microsoft Anti-Piracy Efforts To Backfire

While the Windows Genuine Advantage program is voluntary, Microsoft is forcing users to opt-in by refusing to provide some updates, unless it can verify their OS is not pirated. This heavy-handed approach is sure to drive users of illegitimate versions of Windows to the competing open-source operating system, IDC said in its top 10 infrastructure software predictions for 2007.

While it's true that losing people who aren't paying for the software is arguably a good thing for Microsoft, it's certain to cause an uptick over time in Linux's market share. "We don't think this is a pure win for Microsoft," IDC analyst Al Gillen said. "This is going to accelerate the Linux market as well."

While the increase isn't expected to be sudden or dramatic, IDC predicts that over the next 12 months there would be "some incremental growth" because of the WGA program, Gillen said. "This creates a larger, more robust ecosystem for Linux, which could add just a little bit of acceleration to growth."

The WGA program requires Windows XP users to agree to download software that Microsoft uses to verify that the OS is legitimate before sending updates. The WGA program also includes Vista, which shipped to businesses in November, and is set for release to consumers next month.

Internet Explorer 7 is an example of an important update that wouldn't be available to non-participants of the anti-piracy effort. Critical patches and security updates are still available to everyone, but that could easily change, Gillen said.

Microsoft has been criticized for its handling of the WGA program. The first version of the notification component "phoned home" to Microsoft's servers on a daily basis, angering privacy advocates and others. The software was later updated to remove the feature.

In other IDC predictions, the analyst firm reaffirmed its earlier expectation that Vista is unlikely to cause much of an increase in spending in the PC market. People and companies who do buy Vista, however, will favor the premium version.

IDC also expects to see a next wave of virtualization technology appear next year, focusing on continuity, disaster recovery, and high availability.


Top analyst says this CEO is the most impactful tech exec since Steve Jobs

No result found, try new keyword!Microsoft and Google reported strong earnings beats after the bell Tuesday. The results have investors and analysts largely feeling pretty good. Despite Google reporting an 11% surge in group ...
 


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