Qlik Data Integration
Qlik, originally founded in 1993 in Lund, Sweden, moved its headquarters to the United States in 2005 after raising funds from several venture capital firms. It was acquired by the current owner – private equity company Thoma Bravo – in 2016.
Qlik offers a compelling portfolio of end-to-end platform-based solutions for analytics and data management. In the area of data management, the vendor offers a number of services for data ingestion and transformation, catalog features and automation services.
Qlik has greatly expanded its data management offerings through acquisition, particularly in recent years. Key acquisitions include the Podium Data data management platform for data integration, quality and cataloging in 2018; Attunity’s enterprise data integration and real-time analytics software in 2019; Blendr.io’s IPaaS technology for data and application integration in 2020; and the purchase of NodeGraph, a graph-based data catalog focused on data lineage and data governance, in 2021. The company also acquired Big Squid in 2021 to enhance data preparation leveraging machine learning capabilities.
Qlik Data Integration encompasses these expert data management tools for connecting, preparing and delivering data for analysis. The data management tools are tightly integrated with Qlik analytics tools, but can also be used standalone. They cover usage scenarios from replication and data warehouse automation to building data lakes, streaming use cases and data cataloging. Although Qlik has a SaaS strategy, products such as Composer for creating data warehouse automation are also available in the private cloud, as an on-premises variant or can be distributed hybrid.
Qlik offers qualitative connectors for data extraction that also support efficient, near/real-time streaming scenarios via CDC support, including SAP systems and cloud services such as Amazon Redshift, Snowflake, Google BigQuery, Microsoft Azure Synapse and more. Depending on the use case, the data can be processed in one look and feel with dedicated engines optimized for various integration purposes. Qlik Compose for Data Warehouses allows rapid graphical development of data warehouse models and marts, while Compose for Data Lakes enables customers to build data lakes. The catalog provides a business-user-friendly interface to search and analyze connected data assets leveraging metadata. All pipelines can be scheduled and monitored by a dedicated tool (Qlik Enterprise Manager), which allows users to configure, execute and monitor pipelines across the enterprise.
With this toolset, the foundation is laid for Qlik’s vision to create an end-to-end analytics data pipeline delivering real-time, up-to-date information designed to trigger immediate actions.
User & Use Cases
Qlik Data Integration is primarily used for data warehousing (67 percent) and data integration (44 (percent), which is not surprising given the history of the toolset. The integration of the acquired tools into the Qlik ecosystem is starting to show results. 33 percent of users are already using data management capabilities for self-service analytics, while 22 percent are making use of data preparation capabilities for business users. Interestingly, despite having a special component for data warehouse automation, it is not used by any of our survey participants. Qlik Data Integration tools tend to be used more in larger environments, with 33 percent saying they use it company-wide, and another 33 percent in several divisions. Qlik is used in companies of all sizes. The tool scales from small to large scenarios with 143 users on average (mean). It is noticeable that Qlik respondents reported lower numbers of users and developers than most of its rivals. This indicates good potential for Qlik to scale up within customer organizations.
Extend of usage in the company
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Total number of developers per company
Company size (number of employees)
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