# Data visualization and analysis


After you complete your data quality checks, then you can move to the data analysis or visualization stage, as shown in the following diagram.

![\[Data visualization diagram\]](http://docs.aws.amazon.com/prescriptive-guidance/latest/modern-data-centric-use-cases/images/data_visualization_analysis.png)


In this stage, you can use [Quick Sight](https://aws.amazon.com/quicksight/) for creating graphs or charts, [Neptune](https://aws.amazon.com/neptune/) for graph database operations and visualization, or [OpenSearch](https://aws.amazon.com/what-is/opensearch/) for open-source search and analytics. Typically, you can also feed clean data into data science or machine learning (ML) workflows by using Amazon SageMaker pipelines or simple reads from Amazon S3. The data visualization and analysis stage concludes the sequential portion of the data engineering pipeline.