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.

MediumTechnical

0 practiced

Describe how to implement incremental refresh for a Power BI dataset that receives late-arriving fact records. Include partitioning strategy, policy to detect late inserts/updates, and a process to backfill or refresh affected partitions without reprocessing the entire dataset.

MediumTechnical

0 practiced

Write a SQL query that flags outlier transactions per user where an outlier is defined as amount > mean + 3 * stddev over that user's last 365 days. Table: transactions(id, user_id, amount, occurred_at). Include handling for users with fewer than 5 historical transactions (do not flag them) and show expected columns: user_id, id, amount, occurred_at, is_outlier.

HardTechnical

0 practiced

Explain how to implement column-level and row-level security in Looker. Describe using access_filters, user_attributes, and access_grants, and outline an audit and testing plan to ensure policies are correctly enforced across explores and dashboards.

MediumTechnical

0 practiced

Compare LookML's model layer and Tableau's data source layer from the perspective of metric standardization and reuse. What are the pros and cons of each approach when trying to enforce consistent metrics across teams and self-serve environments?

MediumTechnical

0 practiced

Write a LookML example that creates a derived table (PDT) computing 365-day customer LTV aggregated by customer_id. Include the view with a measure and a dimension, and explain how you'd schedule the PDT refresh to balance freshness and compute cost.

Unlock Full Question Bank

Get access to hundreds of Business Intelligence Tools and Features interview questions and detailed answers.

Join thousands of developers preparing for their dream job.