A data analyst is creating a dashboard to monitor the performance of a new, time-sensitive social media campaign. The marketing team needs to track key engagement metrics, such as likes and shares, to make rapid adjustments to the campaign's budget and targeting throughout the day.
When configuring the data connection for this dashboard, which of the following is the MOST critical factor for the analyst to consider when setting the data refresh interval?
The business need for near-real-time data to enable timely decision-making.
The long-term storage capacity required for historical data snapshots.
The complexity of documenting the data lineage for each refresh cycle.
The potential performance impact and query load on the source database.
The correct answer is that the business need for near-real-time data is the most critical factor. In this scenario, the marketing team needs to make 'rapid adjustments' based on campaign performance. This requirement for timely decision-making dictates that the data must be as current as possible, necessitating a short refresh interval (e.g., every few minutes). The refresh interval directly controls the timeliness, or 'freshness', of the data presented in the dashboard.
The potential performance impact on the source system is an important technical constraint to manage, but it is secondary to fulfilling the primary business requirement. The need for storage is more critical for long-term historical analysis rather than an operational dashboard. The complexity of documenting data lineage is a data governance task that is separate from determining the operational need for data timeliness.
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CompTIA Data+ DA0-002 (V2)
Data Governance
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