Business Intelligence Tools and Features Questions

Covers expert proficiency with major business intelligence tools such as Tableau, Power BI, and Looker, and the advanced capabilities these platforms provide. Topics include creating calculated fields and parameters, conditional formatting, complex filtering, dashboard interactivity and responsive layout design, and best practices for visualization and user experience. Includes performance optimization techniques such as extract versus live connection trade offs, query optimization, incremental refresh strategies, and general performance tuning. Also covers governance and security features including access controls and sharing models, considerations for tool selection and recommending the right tool for a specific use case, and high level migration strategies between BI platforms.

HardTechnical

0 practiced

Compare two approaches to embedding dashboards for multiple tenants: (a) provisioning single-tenant BI instances per customer, and (b) running a single instance with Row-Level Security and tenant theming. Evaluate cost, operational complexity, security/isolation risk, and which you would recommend for 100 small-to-midsize tenants.

EasyTechnical

0 practiced

Explain row-level security (RLS) in BI tools and outline a simple implementation where sales reps can see only their region's data. Provide one approach for Power BI (dynamic RLS with USERPRINCIPALNAME) and one for Tableau (data source filter or user filter). Mention common pitfalls in maintenance and testing.

MediumTechnical

0 practiced

Explain how to use Tableau Performance Recording and Power BI Performance Analyzer to diagnose a slow workbook. List the key metrics you would inspect (query time, viz rendering, data engine time), and outline a workflow to isolate the slowest element and recommend fixes.

EasyTechnical

0 practiced

Define parameters in BI platforms (Tableau/Power BI/Looker). Describe three practical use-cases (dynamic thresholds, switching metrics, what-if analysis). Explain, at a high level, how you would implement a parameter-driven filter in Power BI (What-If parameter or slicer + measure) and in Tableau (parameter + calculated field).

HardTechnical

0 practiced

Design an approach for measuring and improving dashboard adoption across the company. Define adoption metrics (daily/weekly active users, time spent, tasks completed), instrumentation strategies, experiments (A/B tests to improve onboarding or default views), a feedback loop, and incentives to move users from emailed static reports to interactive dashboards.

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