Free Certification Practice Questions

Validates the ability to implement data pipelines and to monitor, troubleshoot, and optimize cost and performance issues in accordance with best practices.

Validates the ability to secure and manage data on Google Cloud by using data services for ingestion, transformation, pipeline management, analysis, machine learning, and visualization, with foundational understanding of core cloud concepts.

Validates the ability to design, build, deploy, monitor, maintain, optimize, and secure data processing systems on Google Cloud for collection, transformation, storage, delivery, and analysis of data to support business and regulatory requirements.

Validates foundational knowledge of core data concepts and related Microsoft Azure data services, including relational and non-relational data, analytics workloads, and data visualization with Power BI.

Validates the skills needed to design, create, and manage analytical assets in Microsoft Fabric, including preparing data, securing and maintaining analytics assets, and implementing and optimizing semantic models for enterprise-scale analytics solutions.

Validates the skills needed to implement data engineering solutions in Microsoft Fabric, including ingesting and transforming data, securing and managing analytics solutions, and monitoring and optimizing data engineering workloads for enterprise-scale analytics.

Validates foundational knowledge of Microsoft Power Platform, including its business value, environment management, Dataverse, Power Apps, Power Automate, and Power Pages capabilities used to build low-code business solutions.

Validates the ability to design, develop, test, and troubleshoot Microsoft Power Platform solution components by creating technical designs, building solutions, improving Power Apps, extending the user experience and platform, and developing integrations using Dataverse, Power Automate, developer tools, and Azure services.

Validates the ability to deliver actionable insights by preparing, modeling, visualizing, and analyzing data in Power BI and by managing and securing Power BI assets to enable business value and self-service analytics.

Validates the ability to integrate and model data, build and deploy optimized pipelines, and troubleshoot and maintain workloads in Azure Databricks by setting up Azure Databricks environments, securing and governing Unity Catalog objects, preparing and processing data, and deploying and maintaining data pipelines and workloads with SQL, Python, Git, Azure Data Factory, Microsoft Entra, and Azure Monitor.

Validates proficiency with the Databricks Data Intelligence Platform for introductory data engineering tasks, including understanding the platform architecture and multi-cloud workspace, performing ETL using Apache Spark SQL and PySpark, handling complex data transformations and user-defined functions, deploying and orchestrating workloads with Databricks Workflows, and applying data governance and quality practices with Unity Catalog.

Validates advanced skills in building, optimising, and maintaining production-grade data engineering solutions on the Databricks Data Intelligence Platform. Covers Delta Lake, Unity Catalog, Auto Loader, Lakeflow Spark Declarative Pipelines, Databricks Compute (including serverless), Lakeflow Jobs, and the Medallion Architecture. Assesses the ability to design secure, reliable, and cost-effective ETL pipelines, process complex data using Python and SQL, and apply best practices in schema management, observability, governance, and performance optimization. Also covers streaming workloads, workflow orchestration, DevOps and CI/CD, and deploying with the Databricks CLI, REST API, and Asset Bundles.