Data visualization is correct because it helps you quickly detect patterns anomalies and operational problems and it lets you focus on the meaning of information rather than inspecting raw records.

Data visualization uses charts graphs and dashboards to reveal trends clusters outliers and relationships in data so that teams can understand issues at a glance and act faster. Visualizations abstract raw records into visual forms which makes it easier to spot anomalies and operational problems without reading individual rows.

BigQuery is a scalable data warehouse for storing and querying large datasets and it is not itself a visualization tool even though it can feed data to visualization systems.

Data reconciliation is the process of comparing and correcting data between sources and it focuses on data quality rather than on presenting patterns visually.

Data forecasting creates models to predict future values and trends and it is about generating predictions rather than helping users visually inspect current records for patterns or operational issues.

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