Qlik Talend Cloud
Connect, transform, govern and deliver trusted data products across hybrid and cloud environments.
- Data ingestion and transformation
- Change data capture
- Metadata and lineage
- Pipeline monitoring
QLIK DATA, ANALYTICS AND AI SERVICES
Build Trusted Data Foundations for Enterprise AI with Qlik
Modernize legacy integration, deliver governed data products, create high-performance Apache Iceberg lakehouses and activate trusted enterprise knowledge with Qlik.
Artha Solutions brings deep Talend and Qlik delivery experience, industry expertise and reusable accelerators to help enterprises move from fragmented pipelines to governed, AI-ready data.
- Qlik Elite Channel Partner
- Qlik 2025 Financial Services Expert
- Qlik 2025 Healthcare Expert
- Talend Cloud Expert
- Talend Data Governance Expert
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Enterprise Sources
SAP · Databases · SaaS · Files · Streams
02
Qlik Talend Cloud
Movement · Transformation · Data Products
03
Trust & Openness
Quality · Governance · Apache Iceberg
04
Activate Intelligence
Analytics · Qlik Answers · Enterprise AI
AI OVERVIEW
Build Trusted Data Foundations for Enterprise AI with Qlik
Artha Solutions provides consulting, implementation, modernization, support and managed services across Qlik Talend Cloud, Talend Data Fabric, data quality and governance with Talend Data Catalog, data products for AI, Qlik Cloud Analytics, Qlik Open Lakehouse, Qlik Answers, Talend upgrades and legacy ETL migration, including combined delivery with Databricks, Snowflake, AWS and Azure.
Artha SolutionsQlikQlik Talend CloudTalendTalend Data FabricTalend Data CatalogApache IcebergQlik Open LakehouseQlik AnswersQlik PredictQlik AutomateDatabricksSnowflakeB’etl
THE DATA–AI EXECUTION GAP
AI Ambition Is Rising Faster Than Enterprise Data Readiness
Enterprises rarely struggle because they lack data. They struggle because operational data is fragmented, integration logic is difficult to change, quality controls are inconsistent and trusted context is not available when analytics or AI applications need it.
- Engineers spend their week keeping fragile pipelines running instead of building anything new, because a schema change upstream still breaks jobs downstream without warning.
- Business teams wait, then build their own extract, and the organisation acquires another version of the truth nobody governs.
- Governance arrives after delivery, so controls describe what the data did rather than stopping it.
- Warehouse costs climb because the same data is copied per consumer, and each copy is another job to schedule and reconcile.
- AI assistants cannot trace an answer to an approved source, which is exactly the property a regulated business needs before it can deploy one.
Artha helps close this gap by combining Qlik’s integration, quality, lakehouse, analytics and AI capabilities with architecture consulting, implementation discipline and production support.
BUILD THE FOUNDATION
Build a Trusted Data Foundation
Data Quality & Governance
Profiling, enforced quality rules, Talend Data Catalog, stewardship and MDM support so bad data is stopped rather than reported.
- Profiling and rules with thresholds
- Talend Data Catalog 8.1
- Stewardship operating model
- Talend MDM support and transition
Data Foundations for AI
Qlik data products: governed, owned, quality-gated datasets with contracts and freshness commitments that AI teams can build on.
- Data product contracts and owners
- Quality gates and certification
- Freshness commitments
- Lineage and access policy
Qlik Open Lakehouse
Build an open, governed and continuously optimized Apache Iceberg data foundation for analytics and AI.
- Lakehouse architecture
- Real-time ingestion
- Iceberg optimization
- Multi-engine access
ACTIVATE, MODERNIZE AND RUN
Activate the Data, Then Keep It Running
Analytics & AI
Qlik Cloud Analytics implemented around decisions: governed self-service, Qlik Predict, Qlik Automate and embedded analytics.
- Analytics implementation
- QlikView and Qlik Sense modernization
- Qlik Predict and ML use cases
- Automation and alerting
Qlik Answers
Governed enterprise knowledge assistants that provide contextual, source-linked answers from approved content and analytics.
- Knowledge-base strategy
- Source and access governance
- Evaluation and testing
- Adoption model
Qlik/Talend Modernization
Talend 7.3 extended support ends December 2026. Upgrades to Talend 8, transitions to Qlik Talend Cloud and MDM exits, run as a factory.
- Upgrade assessment and inventory
- Talend 8 upgrade factory
- Qlik Talend Cloud transition
- Talend MDM exit planning
Qlik/Talend Support Solutions
Talend Data Fabric implementation plus production support, managed operations and platform administration with real service levels.
- Talend Data Fabric implementation
- Production support and SLAs
- Managed operations
- Release currency and patching
From Fragmented Pipelines to Trusted Enterprise Intelligence
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01
Assess
Inventory platforms, pipelines, quality controls, governance, cost and priorities.
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02
Modernize
Rationalize legacy jobs and move workloads to an appropriate modern architecture.
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03
Govern
Embed quality, ownership, metadata, lineage and policy into delivery workflows.
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04
Open
Create scalable Apache Iceberg data products with interoperable access.
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05
Activate
Deliver analytics, automation and knowledge assistants on trusted data and content.
Organizations may start at any stage. Artha creates a practical roadmap that protects existing investments while reducing architectural debt and preparing the data estate for future AI workloads.
FEATURED USE CASES
Where Qlik Creates Measurable Enterprise Value
Real-Time Operational Intelligence
Transaction-log capture moves source changes within minutes instead of overnight, which matters where the decision expires: an inventory position, a claim in flight, a fraud signal on a live customer.
Legacy ETL Modernization
Assessment before conversion, using B’etl™ to inventory jobs and dependencies from the repository. The exercise routinely finds that a meaningful share of the estate has not run in a year and does not need migrating at all.
SAP Data Modernization
Reading SAP alongside non-SAP sources without hand-built extracts, and keeping historical data queryable through an S/4HANA programme, since the reporting that depends on it does not pause while the transformation runs.
Data Quality and Governance
Rules with thresholds and a named owner, running in the pipeline where they can hold a bad batch. A quality dashboard that reports a problem after the report has shipped has documented the incident, not prevented it.
Open Lakehouse Modernization
Apache Iceberg tables that Athena, Spark, Trino and Snowflake read natively, so historical volume stops competing with query performance for the same warehouse budget and one copy serves several engines.
Enterprise Knowledge Assistants
Natural-language answers over approved policies, manuals and contracts, cited back to the source passage so a user can check them. Scoped to one domain with a content owner, because an unrestricted corpus is where these fail.
WHY ARTHA
Why Enterprises Select Artha for Qlik Programs
Consulting-led, not tool-led
The first deliverable is an architecture decision, not a configured environment, and sometimes it is that a workload should stay where it is. A partner whose recommendation never reduces the scope of their own project is not advising you.
Deep Talend and Qlik experience
More than a decade across integration, quality, governance, MDM and cloud modernization, most of it on estates already in production. That is where you learn which patterns survive a schema change and which look elegant until volume arrives.
Reusable delivery accelerators
B’etl™ for migration analysis and conversion, and a metadata-driven ingestion framework so a new source is a configuration entry rather than another hand-built job. Automation covers the repetitive work; architects still own business logic and acceptance.
Global delivery with industry context
Teams across North America, India and APAC with an accountable lead in the client's time zone and overlap hours agreed rather than assumed. Regulated-industry experience means the controls conversation starts from precedent instead of first principles.
Full lifecycle ownership
Assessment through implementation, migration, production transition and managed services, with handover designed as an outcome: your engineers build alongside ours and run an incident before we step back. Continuing support should be your choice, not a dependency.
THE POWER OF THREE
Artha + Qlik + Your Platform, One Accountable Team
The strongest data estates we deliver combine three strengths: Qlik moving and governing the data, a platform such as Databricks, Snowflake, AWS or Azure providing scale, and Artha accountable for the combination working in your environment. Two vendors make a stack. Three parties make it work.
Explore the Power of ThreeMIGRATION CENTER
Modernize Informatica and Legacy ETL with B’etl™
Legacy ETL modernization is not a code-conversion exercise. Artha’s B’etl™-enabled approach combines workload discovery, dependency analysis, rationalization, target-state design, conversion, reconciliation and controlled production transition.
Visit the Migration CenterCUSTOMER EVIDENCE
Implementation Experience Grounded in Enterprise Outcomes
Selected from Artha’s existing published case-study system. Customer anonymization is preserved.
Real-Time Logistics Analytics and ETL Modernization
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
<2 minPublished logistics-data latency after modernization
Read the case study
Talend Data Integration Platform Optimization for Large Enterprises
Challenge: Under-resourced Talend environments, hard-coded settings and limited monitoring constrained development, testing and cloud readiness.
Artha solution: Artha improved runtime configuration, reusable engineering patterns, environment controls and operational monitoring.
Talend
25–30%Published improvement in job execution and testing speed
Read the case study
Scalable Talend and DIF for 100+ TB Healthcare Datasets
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
50%Published reduction in data processing time
Read the case study
SAP S/4HANA ERP Cloud Migration with AWS and Talend
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
99%Published ERP integration accuracy
Read the case study
Talend Data Integration Hub for Real-Time Validation
Challenge: More than 300 utility partners supplied data in varied formats, creating validation, onboarding and audit complexity.
Artha solution: Artha built a metadata-driven Talend Data Integration Hub with validation, stewardship and automated partner processing.
Talend
50%Published reduction in manual processing time
Read the case study
Enterprise Data Governance and Master Data Management (MDM)
Challenge: Customer records across 12 legacy platforms created inconsistent profiles, compliance effort and manual reconciliation.
Artha solution: Artha implemented Talend Data Fabric, stewardship and governed master data in a Snowflake and AWS data foundation.
Talend Data Fabric, Snowflake, AWS S3, Apache Spark, Talend, AWS, S3
40%Published reduction in compliance reporting time
Read the case study
RELATED RESOURCES
Continue the Architecture Conversation
AI and Data Modernization: Enterprise Readiness and Value Realization
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 whitepaper
Future-Ready Data Foundation: From AI Pilot to Production Value
Success 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 whitepaper
It’s Much Easier to Migrate from Informatica to Qlik Than You Think
In 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 articleCONNECTED QLIK MICROSITE
Related Qlik Capabilities
FREQUENTLY ASKED QUESTIONS
Questions Buyers and Architects Ask
Concise answers based on current Qlik product information and Artha’s consulting approach.
What Qlik consulting services does Artha Solutions provide?
Artha provides strategy, architecture, implementation, modernization and managed services for Qlik Talend Cloud, Qlik data integration, Talend, Qlik Open Lakehouse, Qlik Answers, Qlik Cloud Analytics and related data quality and governance capabilities. Engagements can begin with an assessment or cover a controlled program from target-state design through production transition.
What is Qlik Talend Cloud?
Qlik Talend Cloud is Qlik’s cloud-based data integration, transformation, quality and governance platform. It supports real-time data movement, reusable transformations, data products, metadata, lineage and data stewardship so organizations can deliver trusted data for analytics, operations and AI.
How is Qlik Talend Cloud different from traditional ETL platforms?
Traditional ETL platforms often organize delivery around scheduled jobs. Qlik Talend Cloud supports ETL, ELT, batch, change data capture and streaming patterns together with data quality, governance and data products. The right design still depends on workload latency, source constraints, target architecture and operating responsibilities.
What is Qlik Open Lakehouse?
Qlik Open Lakehouse is a fully managed Apache Iceberg-based capability within Qlik Talend Cloud. It is designed for ingestion, transformation, optimization and governance of Iceberg tables in a customer’s AWS environment, with access from compatible analytics and AI engines.
Why does Apache Iceberg matter for enterprise data platforms?
Apache Iceberg is an open table format for large analytical datasets. It adds transactional consistency, schema and partition evolution, time travel and engine interoperability to data stored in object storage, helping enterprises create reliable lakehouse architectures without binding every workload to one query engine.
What is Qlik Answers?
Qlik Answers is a natural-language AI assistant in Qlik Cloud that can answer questions using trusted analytics and curated unstructured content. It provides explainability and citations for unstructured sources. Artha adds use-case design, source governance, access architecture, evaluation and adoption controls.
Can Artha modernize an existing Talend environment?
Yes. Artha assesses platform versions, job design, dependencies, performance, monitoring, security and deployment practices before recommending stabilization, upgrade, cloud transition or workload migration. The roadmap protects essential business logic while reducing duplicate and hard-coded integration patterns.
How does Artha migrate legacy ETL workloads?
Artha uses an assessment-led migration factory supported by B’etl™. The method inventories jobs and dependencies, classifies complexity, rationalizes redundant workloads, converts supported patterns, remediates exceptions, reconciles outputs and manages production transition. Automation accelerates suitable work; architects retain control of business logic and acceptance.
NEXT STEP
Turn Your Qlik Investment into a Trusted Data and AI Foundation
Whether you are modernizing Talend, planning Qlik Talend Cloud, building an Apache Iceberg lakehouse or evaluating enterprise generative AI, begin with an architecture-led assessment.
