Describe an analytics workload on Azure

A data science team needs an Apache Spark-based analytics platform on Azure where engineers can prepare large datasets and data scientists can collaboratively train machine learning models in shared workspaces. Which Azure service best fits this requirement?

A data science team needs a cloud analytics platform where they can write collaborative Apache Spark notebooks in Python and Scala, run large-scale data transformations on distributed clusters, and train machine learning models. The team specifically wants an optimized, managed Spark environment. Which Azure service best meets these requirements?

A retail company wants a single Azure service that lets data engineers ingest data, run large-scale distributed queries using both provisioned SQL pools and Apache Spark, and query data directly in the data lake — all within one integrated workspace. Which Azure service best fits this requirement?

A retail company collects sales transactions from all its stores throughout the day. Every night at 2 AM, a job runs to consolidate the entire day's transactions, calculate daily totals, and load the results into a data warehouse for reporting. Which characteristic best identifies this as a batch processing workload?

A retail company collects sales transactions throughout the day and processes all of them together once every night to produce a summary report for the previous day. There is no requirement to react to individual transactions as they occur. How should this workload be classified?

A retail company needs to orchestrate a workflow that copies sales files from an on-premises file server into Azure Data Lake Storage on a nightly schedule, then triggers transformation steps before loading the data into an analytical store. The team wants a cloud-based data integration service with a visual, low-code pipeline designer to build and schedule these ingestion activities. Which Azure service should they use?

A retail operations team wants to monitor their real-time sales telemetry inside Microsoft Fabric. Whenever a store's hourly transaction failure rate exceeds a defined threshold, they need an alert automatically sent to the on-call engineer without anyone manually watching a dashboard. Which Microsoft Fabric capability should they use?

A logistics company uses Microsoft Fabric. Delivery trucks continuously send GPS and sensor readings that must be analyzed as events arrive so operations staff can react to delays within seconds. Which Fabric workload experience is designed to capture and analyze this continuously flowing event data?

A retail company uses Microsoft Fabric for large-scale analytics. The data engineering team needs to orchestrate a repeatable workflow that copies sales files from an external source, applies transformation activities, and loads the results into a lakehouse on a scheduled basis. Which Microsoft Fabric capability should they use to build and schedule this orchestration workflow?

A retail analytics team using Microsoft Fabric wants a fully managed, SQL-based analytical store that data analysts can query using T-SQL and that supports transactional (multi-table) consistency for their reporting layer. Which Fabric workload experience should they choose?

A data team is building a large-scale analytics solution in Microsoft Fabric. They need a single item that stores both structured tables and raw files (CSV, JSON, Parquet) in one location and lets data engineers query the data with Apache Spark notebooks. Which Fabric item should they use?

A company is adopting Microsoft Fabric for its analytics platform. Data engineers, data scientists, and business analysts all need to work with the same datasets without copying data between different services or maintaining multiple storage systems. Which Fabric capability provides a single, unified storage foundation that all Fabric workloads can access?

A retail analytics team uses Microsoft Fabric to store curated sales data in a lakehouse. They now want business users to build interactive reports and dashboards directly on top of that data without exporting it to a separate tool. Which Microsoft Fabric experience should they use to create these reports?

A retail analytics team wants a single software-as-a-service platform that unifies data ingestion, data engineering, a data warehouse, real-time analytics, and Power BI reporting under one integrated experience with shared OneLake storage. Which Microsoft service should they choose?

A retail company stores operational order data in Azure Cosmos DB. Analysts want to run large-scale analytical queries over this operational data without writing custom ETL pipelines and without adding read load or affecting the performance of the transactional application. Which capability should they use?

A retail company is building a large-scale analytics solution. They want to load raw sales data directly into a cloud data lake first, then use the compute power of the analytical platform to transform the data into curated tables afterward. Which data processing approach does this describe?

A retail operations manager wants a Power BI report page to prominently display a single headline number — the current total sales for the day — with no chart, axis, or breakdown. Which Power BI visualization best fits this requirement?

A sales analyst is building a Power BI report and needs a visual that compares total revenue across several product categories for a single time period, making it easy to see which category earned the most. Which visualization type is most appropriate?

A retail company has a business intelligence team that builds Power BI reports. The sales managers only need to open and interact with these published reports on their mobile phones and browsers — they do not create or edit any content. Which Power BI experience is designed for these sales managers?

A retail operations manager wants a single, always-on screen that pins together key visuals from several different Power BI reports — total sales, inventory levels, and customer satisfaction — so executives can monitor the business at a glance. Which Power BI artifact should be created to combine these pinned visuals from multiple reports onto one canvas?