PL-300 Ep 5 Data Quality, Profiling & Errors | 13 Exam Questions Verified on Microsoft Learn (Prep)

Episode 5 of the MSExamLab PL-300 series: Data Quality, Profiling and Errors. Thirteen real exam-style questions on the profiling panes, error handling, data cleaning, and model-size decisions - each answer worked through and verified against Microsoft Learn before recording. Every answer in this video was checked, question by question, against Microsoft's official documentation. No dump-site guesswork: where the question bank ships a wrong answer, the correction is shown on screen and explained. In this episode Q1 is one of those - the bank keys the Formula Bar for reviewing a column's maximum value, but the Formula Bar only shows M code. Column statistics, including min and max, live in the Column profile pane. That correction is on screen and in the pinned comment. The habit that unlocks this topic: match the pane to the job. Column quality gives valid, error and empty percentages; Column profile gives the statistics and value distribution; Column distribution gives distinct and unique counts. Pick the one that answers the question and half of these items fall out immediately. What you'll practise in this episode: Choosing the right profiling pane for percentages, statistics, or distribution Reading a string-length distribution without growing the model Telling step-level errors from cell-level errors by the message prefix Replacing error values so every row is kept Filling blanks that sit under a merged heading Reducing a source to a clean country dimension, then removing duplicates Normalising dirty casing before you deduplicate Replacing nulls with zero so an average counts them Flagging duplicate emails with CALCULATE, COUNTROWS and ALL Staging queries with Reference and disabling load Fixing a referenced query that re-evaluates for every consumer, using a dataflow Resolving a refresh that hits the memory ceiling with a composite model Reading the error when a column has vanished from the source How each question works: a blank exam-style question appears with a ten-second timer, then the worked solution follows with a clear explanation of why each distractor fails. Pause whenever you need longer, and replay the answer to lock it in. Who this is for: anyone preparing for Exam PL-300: Microsoft Power BI Data Analyst, first sitting or retake. The questions mirror the real exam's style and difficulty without reproducing live items. A note on method: each answer is reconciled with the current Microsoft Learn documentation for Power BI and Microsoft Fabric at the time of recording. If Microsoft changes a behaviour later, comment with the question number and it will be re-verified and pinned. CHAPTERS 0:00 Intro & what you'll learn 0:57 Q1 - Picking the profiling tool 2:44 Q2 - Distribution of string lengths 4:35 Q3 - Two errors, two levels 6:21 Q4 - Keeping every row 7:45 Q5 - Blanks under a heading 9:16 Q6 - Building a country dimension 10:55 Q7 - Dirty country names 12:39 Q8 - Nulls in an average 14:12 Q9 - Counting duplicate emails 15:47 Q10 - Splitting one query into two 17:34 Q11 - One query, three consumers 19:09 Q12 - Hitting the memory ceiling 21:01 Q13 - A column that vanished 22:38 Episode recap 23:26 Next episode & subscribe New episodes work through the whole PL-300 objective domain - Prepare, Model, Visualize, and Deploy - one focused set at a time. Subscribe so you catch every episode, and drop the number of any question that caught you out in the comments. Channel:    / @msexamlab   Full PL-300 playlist: open the channel Playlists tab and choose PL-300. Answers verified vs Microsoft Learn. This is exam preparation and revision practice; it is not a brain dump and does not reproduce live exam items. Tags: #PL300 #PL300Exam #PL300Prep #PL300Questions #PowerBI #PowerBIExam #MicrosoftPL300 #DataAnalystAssociate #PowerBICertification #DataQuality #DataProfiling #ColumnProfile #ColumnQuality #ColumnDistribution #ErrorHandling #ReplaceErrors #StepLevelError #CellLevelError #FillDown #RemoveDuplicates #DataCleaning #PowerQuery #MQuery #CompositeModel #DirectQuery #ImportMode #Dataflows #ReferenceQuery #DisableLoad #CALCULATE #COUNTROWS #DAX #MicrosoftFabric #PowerBIDesktop #DataAnalytics #BusinessIntelligence #MSExamLab #ExamPrep #PowerBITutorial #MicrosoftCertification #DA100 #MicrosoftLearn #MemoryCeiling #VertiPaq #Cardinality #DataReduction #SemanticModel #PowerBIReports #DataSources #MSFabric #AnalystExam #CertPrep #DataModeling #ProfilingPane #DuplicateEmails #PL300Practice #PowerBIPrep #DataAnalyst #MicrosoftExam #PowerBILearning #FabricAnalytics #PowerBIExamPrep #PL300Revision #DataTransformation #MQueryLanguage #PowerBIModeling #ExamQuestions #PracticeTest #PowerBISkills #DataWrangling #CleanData #NullHandling #ErrorRows #QueryFolding #PerformanceTuning #LoadOptimization #RefreshErrors #VertiPaqEngine #DataPrep #PowerBICourse #LearnPowerBI #MicrosoftDataAnalyst #PL300Study #BItutorial #AnalyticsExam #PowerBIcert #FabricExam #PassPL300