Describe Core Data Concepts: Free DP-900 Practice Questions

Question 1

A company is building an application that collects customer feedback through various channels: scanned handwritten letters, audio recordings of phone calls, and photos of product defects. A junior developer asks what type of data this represents and what storage approach to use. Which statement best describes the nature of this data?

It is unstructured data because it lacks a predefined schema or organized format and varies in type and size It is structured data because each feedback channel follows a consistent collection pattern and predictable layout It is unstructured data because it is stored in rows and columns but uses flexible data types across fields It is semi-structured data because it contains metadata tags that define its organization and content relationships

Correct Answer: It is unstructured data because it lacks a predefined schema or organized format and varies in type and size

Scanned handwritten letters, audio recordings, and photos are classic examples of unstructured data because they have no predefined schema, no organized tabular format, and vary widely in type, size, and content.

Semi-structured data would include formats like JSON or XML with self-describing tags, not raw binary files like images and audio. Unstructured data is never stored in rows and columns, so describing it that way is contradictory. Structured data requires a fixed schema with predictable fields, which raw images, audio, and scanned documents do not have.

The key concept tested is the ability to distinguish between structured, semi-structured, and unstructured data types.

Question 2

What does a data analyst primarily do with cleaned and modeled data?

Stores it in databases and configures access permissions for team members Transforms it into visualizations and reports that drive business decisions Transforms it into machine learning models that predict future outcomes Transfers it into data warehouses and manages ongoing pipeline orchestration

Correct Answer: Transforms it into visualizations and reports that drive business decisions

A data analyst's primary responsibility is to take cleaned and modeled data and turn it into meaningful visualizations, dashboards, and reports that help organizations make informed business decisions.

Storing data and configuring access permissions is the role of a database administrator. Building machine learning models is the responsibility of a data scientist. Transferring data into warehouses and managing pipelines falls under the domain of a data engineer.

The key concept tested here is understanding the distinct role of a data analyst within the broader data professional ecosystem, specifically their focus on reporting and visualization to deliver actionable business insights.

Question 3

What is a key collaboration responsibility of an Azure Data Engineer in relation to data consumers such as analysts and scientists?

Defining business requirements and establishing key performance indicators for each department Ensuring reliable and accessible data is available in organized analytical stores Creating business intelligence dashboards and distributing scheduled reports to stakeholders Building machine learning models and deploying them into production environments

Correct Answer: Ensuring reliable and accessible data is available in organized analytical stores

Azure Data Engineers are responsible for building and maintaining data pipelines that deliver clean, reliable, and well-organized data into analytical stores such as data warehouses and data lakes, making it readily accessible for data consumers like analysts and data scientists.

Building machine learning models is the responsibility of a Data Scientist, not a Data Engineer. Creating dashboards and distributing reports falls under the role of a Data Analyst. Defining business requirements and KPIs is typically a business stakeholder or business analyst responsibility.

The key concept tested is understanding the distinct role boundaries of an Azure Data Engineer and how they collaborate with other data professionals by providing well-structured analytical data stores.

Describe Core Data Concepts

DP-900 - Describe Core Data Concepts Example Questions

Question 1

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Question 3

Master Data Fundamentals on Azure