DataOps for Analytics
Modern data integration that delivers real-time, analytics-ready and actionable data to any analytics environment, from Qlik to Tableau, PowerBI and beyond.
To lead in the digital age, everyone in your business needs easy access to the latest and most accurate data. Qlik enables a DataOps approach, vastly accelerating the discovery and availability of real-time, analytics-ready data to the cloud of your choice by automating data streaming (CDC), refinement, cataloging, and publishing.
Learn more about data integration with Qlik
Real-time Data Streaming (CDC)
Extend enterprise data into live streams to enable modern analytics and microservices with a simple, real-time and universal solution.
Agile Data Warehouse Automation
Quickly design, build, deploy and manage purpose-built cloud data warehouses without manual coding.
Managed Data Lake Creation
Automate complex ingestion and transformation processes to provide continuously updated and analytics-ready data lakes.
Delivering real-time Streaming Data
Extend enterprise data into live streams with a simple and universal solution.
The Qlik Data Integration platform efficiently delivers large volumes of real-time, analytics-ready data into streaming and cloud platforms, data warehouses, and data lakes. And with an agentless and log-based approach to change data capture, your data is always current without impacting source systems.
Delivering the Agile Data Warehouse
Rapid design, deployment, and management without coding
The Qlik Data Integration platform automates the entire data warehouse lifecycle to accelerate the availability of analytics-ready data. Data engineers have the agility to create a data model, add new sources, and provision new data marts. Data warehouse automation (DWA) ensures success at every step of the pipeline from data modeling and real-time ingestion to data marts and governance.
Delivering the Agile Data Lake
Rapid design, deployment, and data management without coding
The Qlik Data Integration platform for managed data lakes automates the process of providing continuously updated, accurate, and trusted data sets for business analytics. Data engineers have the agility to quickly add new sources and ensure success at every step of the data lake pipeline from real-time data ingestion, to refinement, provisioning, and governance.