QLIK DATA MODERNIZATION RESOURCES
Explore Artha case studies, research, articles and event content related to Qlik, Talend, data integration, governance, migration, open lakehouse and enterprise AI.
Resources are surfaced from the existing content collections rather than duplicated inside the microsite.
AI OVERVIEW
The Artha Qlik resource center brings together existing case studies, whitepapers, blogs, webinars and events related to Qlik, Talend, data integration, data governance, migration, Apache Iceberg and enterprise AI.
Most people arrive here mid-evaluation with a specific question rather than a general interest in a platform. It is faster to start from the decision you are trying to make:
The case studies, research and articles below come from the same content library used across the site rather than being written for this microsite, so what you read here is what was published elsewhere.
How managed integration, transformation, quality and governance fit together in one platform, what a business-owned data product actually requires, and where the design work does not disappear just because the runtime is managed.
Explore servicesProfiling that establishes the honest baseline, rules with thresholds and owners, Talend Data Catalog for lineage and meaning, and what to do about a Talend MDM estate now that the product is end of life.
Explore servicesWhy AI initiatives stall on ungoverned inputs, and how Qlik data products fix it: contracts, named owners, quality gates and freshness commitments that let a model team build without re-verifying everything by hand.
Explore servicesQlik Cloud Analytics implemented around decisions: governed self-service, QlikView and Qlik Sense modernization, Qlik Predict for what happens next and Qlik Automate for what happens automatically.
Explore servicesThe published lifecycle dates, what actually breaks crossing a Talend version boundary, and how an upgrade factory keeps regression effort flat across waves. Talend 7.3 extended support ends December 2026.
Explore servicesTalend Data Fabric implementation, production support with defined service levels, managed operations and platform administration, including takeover from an incumbent provider.
Explore servicesWhat open table formats change about cost and engine choice, what snapshots give you for reproducible training data, and the table maintenance Iceberg genuinely needs once volume arrives.
Explore servicesKnowledge architecture, source governance, the indexing-identity question that decides whether an assistant is safe to deploy, and how to evaluate answer quality with a scored question set rather than a demo.
Explore servicesArtha, Qlik and your platform, Databricks, Snowflake, AWS or Azure, delivered as one team with one accountable party. What the third seat changes about escalation, architecture and blame.
Explore the modelAssessment-led modernization across Informatica, DataStage, SSIS, Pentaho and custom frameworks, where automation helps and where it does not, and how business logic buried in a transformation gets found before it is lost.
Visit Migration CenterCUSTOMER EVIDENCE
Selected from Artha’s existing published case-study system. Customer anonymization is preserved.
Challenge: Inventory and logistics events took more than 24 hours to reach executive reporting, limiting hot-order visibility and increasing operational intervention.
Artha solution: Artha implemented Qlik Replicate change data capture, Qlik Compose modeling and a governed cloud analytics pipeline.
Qlik Cloud, Qlik Replicate, Qlik Compose, Snowflake, Microsoft Azure, Azure, Qlik
Challenge: A healthcare analytics provider needed to ingest and govern more than 100 TB of diverse data while improving access and processing performance.
Artha solution: Artha deployed Talend with its Dynamic Ingestion Framework across AWS and Snowflake, adding automated validation and scalable processing.
Talend, AWS, Snowflake, Tableau
Challenge: A manufacturing and construction enterprise needed to integrate SAP S/4HANA with decades of ERP history and a wider operational application landscape.
Artha solution: Artha used Talend, AWS and Snowflake to create a scalable integration and historical-data foundation for the modernization program.
Talend, AWS, Snowflake, Salesforce, SAP, MuleSoft
RELATED RESOURCES
ANALYST CONNECTION Sponsored by: Qlik and Artha Solutions AI and Data Modernization: Enterprise Readiness and Value Realization December 2025 Questions posed by: Qlik and Artha Solutions Answers by: Stewart Bond.
Explore whitepaperSuccess with AI starts with data. Improving data quality and accessibility for AI is today’s top organizational priority; nine months ago, it was improving AI infrastructure. However, laying a solid data foundation for.
Explore whitepaperIn today’s data-driven world, staying future proof often means leaving behind legacy ETL platforms like Informatica PowerCenter, especially as they approach end-of-support. While such migrations are often perceived as...
Explore articleWe’re excited to share that Artha has been recognized by Qlik as a Healthcare Specialist Partner! 🌟 This recognition reflects our proven track record of delivering impactful data and analytics solutions across the hea...
Explore articleWhy Enterprises Are Moving from Informatica to Talend Modernizing Data Integration with Flexibility, Cost Efficiency, and Artha’s B’ETL ETL Migrator In a fast-evolving digital economy, enterprises are reassessing thei...
Explore articleCONNECTED QLIK MICROSITE
FREQUENTLY ASKED QUESTIONS
Concise answers based on current Qlik product information and Artha’s consulting approach.
The collection can include published Artha case studies, whitepapers, blogs, webinars and events. The page reads from existing content collections so detail pages, gating and analytics remain consistent.
Resources are selected by relevant product, technology, solution and industry terms such as Qlik, Talend, data integration, governance, migration, Apache Iceberg and AI. Results are limited to published records.
Artha follows the anonymization settings in the existing case-study system. This microsite does not introduce new customer names or override those settings.
Yes. Use the Qlik architecture contact option to describe the platform, workload and decision you are evaluating. Artha can recommend relevant material or scope an assessment.
Case studies, articles and event recaps are open. Whitepapers and some research are gated, which is a straightforward exchange: Artha gets to know who is evaluating, and you get the paper. If a form stands between you and something you need urgently, ask an architect directly instead and it will be sent.
The case studies for the industry closest to yours, because they show which constraints shaped the design, and the service page matching your decision, because it states what an assessment produces. Arriving with a rough source inventory and a stated freshness requirement makes the first conversation substantially more useful than arriving with a product shortlist.
It is written by the team that delivers the work, and it says where platforms fall short as well as where they help: Iceberg needs real table maintenance, no AI assistant eliminates hallucinations, and ETL migration cannot be fully automated. If a resource reads as though a product solves a problem outright, treat that as a reason to ask harder questions, here or anywhere else.
It reflects the site's published content, so new case studies, articles, whitepapers and events appear here as they are published rather than on a fixed schedule. Because the microsite reads from the same collections, nothing is duplicated and detail pages stay consistent wherever you reach them from.
NEXT STEP
Discuss the platform, workload and operating constraints behind your data modernization priority.
