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Describe an analytics workload on Azure →mediumMultiple ChoiceObjective-mapped

Quick Answer

The answer is that the TumblingWindow has not yet elapsed. This is correct because Azure Stream Analytics processes data in fixed, non-overlapping time intervals, and a tumbling window only emits output when the entire window duration completes—no partial results are written to the sink, such as Azure SQL Database, until that moment. On the Microsoft Azure Data Fundamentals DP-900 exam, this concept tests your understanding of how windowed aggregations work in real-time analytics, often appearing as a trap where candidates assume data flows continuously. A common memory tip is to think of a tumbling window like a countdown timer: no results appear until the timer hits zero, so if you see a job running with no output, always check if the window has fully elapsed.

DP-900 Describe an analytics workload on Azure Practice Question

This DP-900 practice question tests your understanding of describe an analytics workload on azure. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.

Exhibit

Refer to the exhibit.

```json
{
  "type": "Microsoft.StreamAnalytics/streamingjobs",
  "apiVersion": "2020-03-01",
  "properties": {
    "sku": {
      "name": "StandardV2"
    },
    "inputs": [
      {
        "name": "input",
        "properties": {
          "type": "Stream",
          "datasource": {
            "type": "Microsoft.EventHub/EventHub",
            "properties": {
              "eventHubName": "telemetry-events",
              "consumerGroupName": "$Default"
            }
          }
        }
      }
    ],
    "outputs": [
      {
        "name": "output",
        "properties": {
          "datasource": {
            "type": "Microsoft.Sql/Server/Database",
            "properties": {
              "server": "sqlserver123.database.windows.net",
              "database": "sqldb",
              "table": "SensorData"
            }
          }
        }
      }
    ],
    "transformation": {
      "name": "TransformTelemetry",
      "properties": {
        "streamingUnits": 6,
        "query": "SELECT SensorId, AVG(Temperature) AS AvgTemp INTO output FROM input GROUP BY SensorId, TumblingWindow(minute, 5)"
      }
    }
  }
}
```

Refer to the exhibit. You deploy this Azure Stream Analytics job. The job runs but no data is written to the Azure SQL Database table. What is the most likely cause?

Clue words in this question

Noticing these words before you look at the options changes how you read each choice.

  • Clue: "most likely"

    Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.

Question 1mediummultiple choice
Full question →

Exhibit

Refer to the exhibit.

```json
{
  "type": "Microsoft.StreamAnalytics/streamingjobs",
  "apiVersion": "2020-03-01",
  "properties": {
    "sku": {
      "name": "StandardV2"
    },
    "inputs": [
      {
        "name": "input",
        "properties": {
          "type": "Stream",
          "datasource": {
            "type": "Microsoft.EventHub/EventHub",
            "properties": {
              "eventHubName": "telemetry-events",
              "consumerGroupName": "$Default"
            }
          }
        }
      }
    ],
    "outputs": [
      {
        "name": "output",
        "properties": {
          "datasource": {
            "type": "Microsoft.Sql/Server/Database",
            "properties": {
              "server": "sqlserver123.database.windows.net",
              "database": "sqldb",
              "table": "SensorData"
            }
          }
        }
      }
    ],
    "transformation": {
      "name": "TransformTelemetry",
      "properties": {
        "streamingUnits": 6,
        "query": "SELECT SensorId, AVG(Temperature) AS AvgTemp INTO output FROM input GROUP BY SensorId, TumblingWindow(minute, 5)"
      }
    }
  }
}
```

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

✓

The TumblingWindow has not yet elapsed

The TumblingWindow function in Azure Stream Analytics processes data in fixed, non-overlapping time intervals. Since the job runs but no data is written, the most likely cause is that the first window has not yet elapsed, meaning no aggregation has been triggered to output results. Stream Analytics only emits results when a tumbling window completes, so data will not appear in the SQL Database until the window duration passes.

Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • ✗

    The query syntax is invalid

    Why it's wrong here

    The query syntax is valid for Stream Analytics.

  • ✓

    The TumblingWindow has not yet elapsed

    Why this is correct

    Aggregate results are emitted only after each window ends; if runtime < 5 minutes, no output.

    Clue confirmation

    The clue word "most likely" in the question point toward this answer.

    Related concept

    Read the scenario before looking for a memorised answer.

  • ✗

    The Event Hub name is incorrect

    Why it's wrong here

    The Event Hub name is specified; if it were wrong, the job would fail to start.

  • ✗

    The SKU does not support SQL output

    Why it's wrong here

    StandardV2 supports SQL output.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The trap here is that candidates assume a running job with no errors means data should flow immediately, but they overlook that tumbling windows require the full window duration to elapse before any output is produced.

Trap categories for this question

  • Command / output trap

    StandardV2 supports SQL output.

Detailed technical explanation

How to think about this question

TumblingWindow is a built-in temporal operator that groups events into discrete time buckets (e.g., every 5 minutes). The job's query engine buffers events until the window boundary is reached, then performs the aggregation and emits a single row per window. In real-world scenarios, if the window duration is set to 1 hour and the job starts at 10:00, no output will appear until 11:00, which often surprises developers expecting near-real-time results.

KKey Concepts to Remember

  • Read the scenario before looking for a memorised answer.
  • Find the constraint that changes the correct option.
  • Eliminate answers that are true in general but not in this case.

TExam Day Tips

  • Watch for words such as best, first, most likely and least administrative effort.
  • Review why wrong options are wrong, not only why the correct option is correct.

Key takeaway

Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.

Real-world example

How this comes up in practice

A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.

What to study next

Got this wrong? Here's your next step.

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

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FAQ

Questions learners often ask

What does this DP-900 question test?

Describe an analytics workload on Azure — This question tests Describe an analytics workload on Azure — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: The TumblingWindow has not yet elapsed — The TumblingWindow function in Azure Stream Analytics processes data in fixed, non-overlapping time intervals. Since the job runs but no data is written, the most likely cause is that the first window has not yet elapsed, meaning no aggregation has been triggered to output results. Stream Analytics only emits results when a tumbling window completes, so data will not appear in the SQL Database until the window duration passes.

What should I do if I get this DP-900 question wrong?

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

Are there clue words in this question I should notice?

Yes — watch for: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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Last reviewed: Jun 24, 2026

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