When integrating heterogeneous data sources, organizations often encounter three common challenges:

$1.$ Data Mapping and Transformation:

Integrating data from different sources often involves dealing with various data formats and structures. This requires mapping data from each source to a unified format, which can be complex due to differences in data schemas and naming conventions.

$2.$ Data Quality and Consistency:

Data from different sources may vary in accuracy, completeness, and format. Ensuring that the data is consistent and of high quality is crucial, as poor data quality can lead to misleading analysis and business decisions.

$3.$ Performance and Scalability:

Handling large volumes of data from multiple sources requires efficient data processing capabilities to maintain performance. It's important to manage the balance between real$-$time data processing and the ability to scale the systems as data volume grows.

Is this correct statements?