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DAC Business Intelligence & Analytics Strategy Flashcards

6 cards from real DAC practice questions. Tap to flip, then mark Knew It or Still Learning โ€” missed cards come back until you master them.

Read the first 6 DAC Business Intelligence & Analytics Strategy flashcards as text
  1. What is a slowly changing dimension (SCD) in data warehousing?

    Answer: A technique for managing and tracking changes to dimension data over time

    Slowly Changing Dimensions (SCDs) are methods (Type 1, 2, 3, etc.) for managing how changes to dimension attributes are tracked and stored in a data warehouse over time.

  2. Which BI concept refers to the ability to drill down into data for more granular detail?

    Answer: OLAP drill-down

    Drill-down is an OLAP operation that allows users to navigate from summary-level data to increasingly detailed levels, such as from annual to quarterly to monthly sales.

  3. What is the primary goal of data storytelling in business analytics?

    Answer: To communicate analytical insights through a narrative that combines data, visuals, and context to drive action

    Data storytelling combines data insights, visualizations, and narrative context to communicate findings in a compelling, understandable way that motivates informed decision-making.

  4. What does ROI stand for, and how is it used in analytics strategy?

    Answer: Return on Investment, used to measure the profitability of analytics initiatives relative to their cost

    ROI (Return on Investment) measures the net benefit of an analytics investment relative to its cost, helping justify data projects and prioritize resources.

  5. In BI reporting, what is an ad-hoc report?

    Answer: A report created on-demand by a user to answer a specific, unplanned business question

    An ad-hoc report is created dynamically by a user to answer a specific question not covered by pre-built standard reports, enabling flexible data exploration.

  6. What is the primary function of a data lakehouse architecture?

    Answer: To combine the flexibility of a data lake with the management and performance features of a data warehouse

    A data lakehouse merges data lake storage flexibility with data warehouse management features (schema enforcement, ACID transactions, BI query performance) in a single architecture.