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DP-900 Describe core data concepts Practice Question

A company collects temperature readings from IoT sensors every second. Each reading includes a timestamp, sensor ID, and temperature value. The data is used for real-time monitoring and historical trend analysis. Which type of data is this most likely classified as?

⚠ Common exam trap

Many exam-takers confuse the data's structure (structured vs. semi-structured) with its velocity (streaming vs. batch), leading candidates to incorrectly select 'Streaming data' because the data arrives in real time, even though the question explicitly asks about classification by type, not ingestion method.

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

Structured data

The data consists of timestamp, sensor ID, and temperature value, each with a defined data type and relationship, fitting a tabular schema (rows and columns) typical of relational databases. This structured format enables efficient querying for real-time monitoring and historical trend analysis using SQL-based systems like Azure SQL Database or Azure Synapse Analytics.

Answer analysis

Option-by-option breakdown

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

  • Structured data

    Why this is correct

    Structured data is organized into a rigid, predefined schema, such as a relational table, where each row represents a sensor reading with fixed columns like timestamp, sensor ID, and temperature. All records follow the identical format, with specific data types (e.g., DATETIME, INT, FLOAT), enabling efficient querying and aggregation. The IoT readings perfectly match this definition, as there is no variability in fields or nested properties. This makes the data directly storable in a SQL database for analysis.

  • Semi-structured data

    Why it's wrong here

    Semi-structured data has a flexible internal format, like JSON or XML, that permits optional, nested, or unordered fields, so records can differ in the attributes they contain. Although the IoT sensor readings might be transmitted as a JSON payload in transit, the logical data model itself is uniform and does not exhibit such variability. Since every reading has the same fixed set of attributes with no hierarchy, the data cannot be classified as semi-structured. The term applies only when the structure is self-describing yet inconsistent across records.

  • Unstructured data

    Why it's wrong here

    Unstructured data lacks a predefined data model or schema, consisting of content like free-text documents, images, audio, and video that cannot be directly stored in rows and columns. The IoT temperature readings are inherently orderly, with each value assigned to a clearly defined attribute, making them trivial to parse and store in a structured format. Unstructured data requires special techniques like OCR, NLP, or computer vision to extract meaning, none of which apply to simple numeric readings. Therefore, this classification is clearly incorrect for the given dataset.

  • Streaming data

    Why it's wrong here

    Incorrect. Streaming data describes a continuous flow of data that is processed in real-time. While the IoT data may be ingested as a stream, the question asks about data classification based on structure, not processing mode.

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