Real-Time ETL

As companies struggle to consolidate real-time data streaming in from multiple sources—in the face of continuous data growth and the demand for timely, accurate business intelligence—more businesses are looking to shift from batch-oriented ETL to real-time ETL.

ETL refers to the processes of extracting, transforming, and loading data from disparate data sources into a centralized data repository for reporting and analysis. Using a conventional ETL tool however, implementing ETL is generally a complex and time-consuming process, often introducing costly delays and risk into BI projects. Forward-thinking companies are interested in real-time ETL solutions that can help them keep up with the volume and velocity of incoming data and respond quickly to changes in the marketplace.

Real-Time ETL: Why Companies Want More Efficient ETL and How They're Achieving It

The promise of real-time ETL for companies is being able to thrive in a rapidly changing world in which using up-to-date information is crucial for staying competitive. Real-time ETL should allow businesses to realize real-time data warehousing in support of timely operational reporting and business intelligence and faster data-driven decision-making.

One way companies have been able to accelerate BI ETL projects is through the use of an ETL solution　that generates ETL scripts and streamlines and improves the performance and consistency of ETL workflows. By providing users with built-in connectors for different sources and targets, integrated metadata repositories, and an intuitive graphical UI from which to monitor and manage data flows, an ETL integration solution makes executing, modifying, and troubleshooting ETL processes simpler and easier.

Another way businesses have come closer to achieving real-time ETL is through the use of data warehouse automation solutions like Qlik Compose®. DWA solutions automate repetitive and labor-intensive data warehousing tasks such as schema generation and ETL coding, enabling not just ETL automation but automation of the entire data warehousing lifecycle from DW design and creation to impact analysis and change management.

Real-Time ETL: Keeping Warehoused Data Fresh with Change Data Capture

For companies seeking real-time ETL, the easiest and most cost-effective way to achieve real-time data integration is through the use of a high-performance data replication and loading solution featuring log-based CDC (change data capture).

Qlik Replicate® is a powerful real-time event capture and data integration platform incorporating log-based CDC technology and intelligent in-memory transaction streaming to boost the performance of high-volume data delivery and enable real-time data warehousing and analytics. Qlik Replicate agentless CDC technology minimizes the need for bulk transfers of data and allows you to extract and load changed source data into your target database or data warehouse instantly or in optimized batches. Qlik Replicate supports a wide variety of data sources and targets including all major relational databases, enterprise data warehouses, mainframe systems, Hadoop distributions, and Kafka message brokers.

Qlik Replicate integrates seamlessly with Qlik Compose.