Talend Data Fabric Data Platform

Database-to-database synchronisation

• Real-time data delivery for reporting and analysis: Replicating data to a separate database or warehouse can enable faster and more efficient querying and analysis of data without affecting the performance of the primary database. 
• Real-time data integration: replicating data between databases can facilitate data integration between different systems or applications within the organisation to ensure that data is consistent and up-to-date. 
• Legacy modernisation: Moving legacy data to new data stores to reduce OLAP costs and improve query performance. Moving data to the cloud: replicate data between on-premises data sources and cloud databases for new ML initiatives.

Data warehouse modernisation

• Data warehouse automation enables faster time-to-market for new data warehouses, improves data quality and reduces costs associated with manual management. Intelligent data pipelines help scale data warehousing activities more efficiently by automatically generating the required transformation SQL and passing it to the warehouse for execution.

Data Lake / Lakehouse automation

• Data Lake Automation solutions based on Qlik and Talend enable enterprise data to be moved, transformed and data governance policies to be enforced so that organisations can build a data lake for data analytics, machine learning and AI initiatives - whether the lake is based on Hadoop, cloud object stores or Databricks.

Database-to-Streams/Streams-to-Database (or other targets)

• Integrating databases with streaming infrastructures such as Apache Kafka or Amazon Kinesis can help companies gain insights from their dynamic data and respond more quickly to changing business conditions. For example, a company could use a database to store customer data such as name, address and purchase history. It would be possible to use a streaming infrastructure such as Kafka to process purchase data generated in real time to detect abusive behaviour such as fraudulent credit card transactions. The Qlik and Talend-based data integration and quality solutions can synchronise database transactions with streams and also pull data from streams to route it to any destination in virtually any format.

API services and workflow

With the Qlik and Talend portfolio, companies can create and use their own APIs for scenarios like these:

• Enterprise APIs as part of a cloud-first strategy.
• Creating new applications that leverage existing data and functionality via APIs.
• Publishing APIs that control the exchange of data between multiple parties.
• Creating "data contracts" as part of a data fabric.
• Automating business processes such as order processing, inventory management and customer support
• Integrating different systems such as CRM, ERP and e-commerce platforms to improve efficiency
• Write KPIs from the data warehouse back into operational systems
• Operational data transformation

Operational data transformation

• Raw data can be converted into formats that can be used by downstream processes such as electronic data interchange, data science or analytics. Usually, operational data conversion takes place outside the data warehouse or data lake, with the final files stored in an object store. Examples include converting transactional records to HL7 files, converting CSV files to Parquet, and converting aggregated data sources to EDI-compatible formats. The Qlik and Talend data integration and quality solutions include specialised functions for many common transformations and help to quickly solve the data exchange problem for specific industry formats.