After cleaning and transformation, it is prepared to load into the target system or data warehouse. This may include:
Batch Processing: One batch of big data in one go, which will be used for scheduled uploads
Real-Time Integration: Real-time applications will always have some method of integration in stream form, like Apache Kafka or Apache Flink.
This would largely depend on the nature and frequency of updates in your data sources.
Tools of Data Integration
There are many tools that can be used in support of the task of data integration, though well-suited to a certain type of integration task:
ETL Tools: Powerful ETL tools for the integration of structured data include Informatica, Talend, Apache NiFi, and Microsoft SSIS.
For storing and querying large datasets, the three ideal options are Google BigQuery, Snowflake, and Amazon Redshift.
All the data visualization and reporting are done using Tableau, Power BI, and Looker.
All the above tools have multiple connectors with various sources of data that may make integration a bit easier.