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Qlik Cloud Analytics

Data quality and profiling built into Qlik's integration platform

Overview

Qlik Talend Cloud combines Talend’s data integration and quality tooling, which Qlik acquired, with Qlik’s own change-data-capture replication technology. Qlik describes it as one platform for ELT, ETL and streaming ingest, with real-time movement from databases, SAP, mainframe and SaaS sources, no-code pipelines, automatically generated star-schema data marts, data products and a marketplace, and lineage, quality and a metadata catalogue[8]. Recent releases add agentic data engineering, in which AI agents propose and monitor pipelines subject to human approval[8].

The product is sold in four packages, Starter, Standard, Premium and Enterprise, and is also available as client-managed software for organisations that cannot use a cloud service[9]. Pricing is not published; Qlik’s FAQ says usage is measured on a combination of data volume moved, number of job executions and execution duration[9]. The CDC heritage makes it strong for operational databases and SAP, while the Talend side brings data quality and governance. The trade-off is that buyers must request quotes for every tier and may find overlapping legacy Talend and Qlik product names during evaluation.

What Qlik Cloud Analytics does

  • Change data capture from databases, SAP and mainframe
  • ELT, ETL and streaming in one product
  • Data quality and lineage
  • Auto-generated star-schema data marts
  • Client-managed option available
  • Agentic pipeline building with human approval
  • Log-based change data capture
  • ELT and ETL transformations

Qlik Cloud Analytics pricing

Quote-based. Four packages (Starter, Standard, Premium, Enterprise); usage measured on data volume moved, job executions and execution duration. Free trial available.

Qlik Cloud Analytics strengths and limitations

Strengths

  • No per-user charge from the Standard tier upward
  • Built-in AI features for natural-language questions and anomaly detection
  • Mature CDC for SAP and mainframe
  • Integrated data quality
  • Cloud and client-managed deployment
  • Four tiers allow staged adoption

Limitations

  • High entry price compared with per-user tools
  • Costs scale with data volume, which can be hard to predict
  • No published prices
  • Usage metric combines three variables
  • Legacy Talend product naming can confuse buyers
  • Heavier than SaaS-only ELT tools

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