Qlik

What Qlik does

Qlik provides modern data integration, AI, and analytics solutions to help organizations make their data work for AI with trust, context, and adaptability. The company delivers trusted data products, a powerful analytics engine, and AI agents to reduce risk, manage operating costs, and scale AI responsibly. Qlik's platform is used by 75% of the Fortune 500 and supports customers worldwide, integrating with existing systems and partners to offer flexibility without vendor lock-in. Qlik is recognized as a Gartner Magic Quadrant Leader in data integration and augmented data quality solutions. The company is committed to responsible AI development and deployment, guided by principles of reliability, customer control, transparency, explainability, and inclusivity.

Products

• Qlik Talend CloudA comprehensive data integration, quality, and governance solution built on Qlik Cloud infrastructure. It offers rapid data movement, real-time synchronization with change data capture, automated data transformation (ELT/ETL), data warehouse/lake/lakehouse automation, end-to-end column-level lineage, impact analysis, Spark batch processing, application/API integration, data product creation, data marketplace, data quality/profiling, data stewardship, and the Qlik Talend Trust Score® for AI/analytics data readiness. It also supports creating data pipelines for AI/Generative AI use cases and enriching data with integrated LLM extensibility.
• Qlik Cloud AnalyticsA powerful analytics engine that provides AI-powered analytics, access to Answers Agents and MCP Server, connectivity to hundreds of data sources, interactive data visualizations and dashboards, and automation workflows. It supports leveraging unstructured data and GenAI for deeper insights, augmented advanced analytics, predictive analytics with automated machine learning, and seamless data extraction from SAP systems.
• Qlik Data IntegrationA client-managed solution offering automated, governed, real-time data pipelines that deliver reliable, analytics-ready data. It automates continuous delivery of real-time data into data warehouses or data lakes and makes it accessible through a governed catalog.
• Talend Data FabricA client-managed unified environment that brings together data integration, data integrity, and data quality.
• Qlik AnswersAn agentic AI assistant that provides personalized contextual answers from customers' own structured and unstructured content, as well as Qlik Help documentation. It is also described as a GenAI-driven knowledge assistant capable of generating insights from unstructured data.
• Qlik PredictA no-code, automated machine learning offering for analytics teams to create, deploy, and manage predictive models.
• Discovery AgentAutomated anomaly detection directly within Qlik Cloud that monitors metrics, identifies meaningful changes, and delivers contextual insights.
• Qlik Insight AdvisorAn AI-powered assistant that uses natural language to generate analyses and visualizations and summarizes insights from structured data. Available in Qlik Cloud and Qlik Sense Client-Managed.
• Generative SQL AssistantA data loading feature that uses generative AI to convert natural language into SQL queries.
• Qlik Sense Client-ManagedA client-managed analytics platform that offers a single digital platform for data customization and agile content/product offerings.
• Qlik Cloud GovernmentA cloud platform for data and analytics built specifically for the U.S. Public Sector, ensuring security and compliance with FedRAMP Moderate Impact Level (IL) and Department of Defense (DOD) IL2 authorization.
• Qlik GeoAnalyticsA tool used to visualize thousands of crime-related data points on a city map.
• Talend StitchA fully managed pipeline solution that helps migrate orphaned product metrics and integrates product data with revenue metrics for go-to-market planning.
• Qlik AutoMLA solution for deploying AI solutions.

Key capabilities

• Modern data integration
• AI-powered analytics
• Agentic AI framework
• Trusted data products
• Powerful analytics engine
• AI agents
• Pre-built connectivity to SaaS applications and databases
• Managed and secure cloud-based data pipelines
• Ready-to-query schemas
• Data catalog
• Field-level metadata management and data profiling
• Analytics and automation workflows
• Real-time synchronization using log-based change data capture (CDC)
• Cloud, client-managed, or hybrid deployment options
• Secure, private access between VPCs and on-premise networks
• Unlimited and optimized data movement to Qlik Cloud Analytics
• Qlik Open Lakehouse with ingestion and adaptive optimization for Apache Iceberg
• Automated and flexible transformations (ELT/ETL)
• Data warehouse, lake, and lakehouse automation
• Automated data mart creation
• End-to-end column-level lineage and impact analysis
• Spark batch processing for high-end data movement
• Application and API integration
• Data marketplace for trusted data products
• Data quality and profiling based on automatically recognized semantic types
• Data stewardship for reviews, validation, and remediation
• Qlik Talend Trust Score® for data readiness
• Data pipelines for AI and Generative AI use cases
• Integrated LLM extensibility
• Comprehensive connectivity to SAP applications and Mainframe sources
• Low-code/no-code development platform
• Automated machine learning for model creation and data exploration
• GenAI-driven knowledge assistant for unstructured data
• Integration of third-party data science and generative AI models
• Customizable themes, logos, and colors for embedded analytics
• Pre-built blocks for process automation
• JavaScript for lightweight visualizations
• Real-time data streaming
• Visual interface for workflow automation
• Multi-tenant security
• Governed self-service
• Capacity-based pricing for predictability
• Data governance, security, and software updates for iPaaS
• Data encryption and access controls
• Audit trails
• Secure software development lifecycle (SAFe, static code analysis, threat modeling, vulnerability scanning, pen-testing)
• Vulnerability management with Responsible Disclosure approach
• Proactive monitoring of production environments
• Privacy-by-design and privacy-by-default methodologies
• Data retention and access rules
• Regular data privacy and security training
• Comprehensive data privacy policies and notices
• Client-Managed-Key functionality for Qlik Cloud
• No-view service for cloud solutions with encrypted content data
• Server location selection by region
• AI-powered analytics
• Access to Answers Agents
• Access to MCP Server
• Connect and combine hundreds of data sources with standard connectors
• Interactive data visualizations and dashboards
• Automate report generation and delivery
• No code automation builder triggers dynamic actions across systems
• Leverage unstructured data and GenAI for deeper insights
• Managed and shared spaces for governance and collaboration
• Connect additional Qlik Talend Cloud data sources (cloud, SAP - Mainframe & legacy)
• Use augmented advanced analytics
• Predictive analytics powered by automated machine learning
• Additional GenAI capacity
• Anonymous access (public access)
• Seamless data extraction from SAP systems into Qlik Cloud
• Data lineage connectors
• Multi-Region tenants
• Automated anomaly detection
• Natural language processing for analysis and visualization generation
• Generative AI for SQL conversion

Use cases

• Making data work for AI with trust, context, and adaptability
• Reducing risk, keeping operating costs in check, and scaling AI responsibly
• Rapidly delivering trusted data to drive smarter decisions
• Moving data from SaaS applications and databases
• Operationalizing real-time data movement at scale with change data capture
• Automating data transformation
• Supporting a wide variety of targets, formats, and architectures
• Creating data products to maximize data usage and value
• Ensuring data readiness for AI and analytics
• Creating data pipelines for AI and Generative AI use cases
• Enriching data and pipelines with integrated LLM extensibility
• Streamlining end-to-end data management
• Delivering immediate value and simplifying consumption for data consumers
• Driving success with domain-centric data products
• Enhancing data trust and governance
• Accelerating business outcomes and time-to-value for use cases
• Enabling informed decision-making and strategic initiatives with curated data products
• Providing reliable, compliant, and transparent data
• Closing the gap between data producers and consumers
• Building innovative solutions faster for ISVs
• Embedding AI and analytics into solutions
• Accelerating secure, scalable innovation
• Providing predictive insights to customers using automated machine learning
• Delivering personalized answers through GenAI-driven knowledge assistants
• Integrating third-party data science and generative AI models within Qlik applications
• Automating processes with pre-built blocks
• Activating flows and streaming real-time data
• Setting triggers and actions and managing workflows across platforms
• Maximizing value for ISVs and their customers
• Boosting customer experience and satisfaction
• Accelerating innovation and time to market for ISVs
• Scaling with SaaS flexibility, multi-tenant security, and governed self-service
• Integrating various applications and data sources across different cloud and on-premise environments (iPaaS)
• Streamlining workflows, improving data visibility and accessibility, and enhancing collaboration and productivity
• Improving services and delivering on mission for public sector
• Delivering federal government agency services more effectively, transparently, and efficiently
• Ensuring national security or monitoring food safety
• Improving public health and cost efficiency
• Creating scenarios and predicting outcomes
• Improving state and local government services and saving budget
• Improving citizen services and gaining transparency to reduce fraud, waste, and abuse
• Predicting crime and preparing law enforcement
• Tracking the meaning behind expenditures
• Raising student success rates across all levels of education
• Optimizing student success rates using predictive analytics
• Enabling data-driven personalized banking and agile operations
• Generating compliance requests and reports
• Creating a single source of truth for banking employees
• Managing high data volumes daily for financial institutions
• Addressing data silos, improving standardization, and ensuring transparency in banking
• Enhancing efficiency and strengthening decision-making in financial services
• Mitigating risks from regulatory complexities and data quality issues
• Fostering self-reporting and streamlining analytics across banks
• Enhancing trend analysis and dashboard creation
• Reducing human errors in financial operations
• Completing Customer 360 initiatives and leveraging AI/predictive models for personalized services
• Optimizing risk, understanding costs, and maximizing profit in financial services
• Making more competitive risk decisions and creating first-class customer experiences
• Solving use cases from credit and market risk to fraud detection
• Improving cash management in bank branches
• Getting a detailed picture of every customer with real-time data
• Improving loan book profitability
• Creating automated, real-time data pipelines and tracking/maintaining/protecting insurance data accuracy
• Transforming decisions across key insurance systems
• Accelerating risk and trading decisions, simplifying complex mathematical problems, and meeting regulatory requirements in securities and investments
• Mining data to drive customer-centricity and enhance guest experience in hospitality
• Reducing reporting time and increasing forecast accuracy in hospitality
• Unifying data across complex organizational landscapes for fast integrations and improved data quality
• Extending personalization of guest experiences and streamlining processes in hospitality
• Responding swiftly to market demands in hospitality
• Optimizing processes, improving supply chain agility, and better serving customers in manufacturing
• Transforming business towards industry 4.0 and a data-driven approach
• Improving operational efficiency and innovation through digitalization
• Surfacing highly accurate and groundbreaking real-time data and insights across the entire product lifecycle
• Improving production throughput and understanding OEE
• Better understanding plant operations and leveraging IoT data
• Understanding quality issues in context
• Streamlining data for improved decision-making in manufacturing
• Extracting and standardizing large volumes of data from various manufacturing systems
• Utilizing real-time data to increase operational efficiency
• Overcoming supply chain complexity and ensuring multi-channel, demand-driven inventory availability
• Harnessing data from disparate, internal, and external data sources for supply chain visibility
• Transforming disparate data into a profitable growth driver
• Consistent customer engagement and responding to shifting demand
• Understanding automotive dealer performance
• Measuring customer service and call center effectiveness
• Accelerating cloud analytics on AWS with real-time data integration and modern BI
• Automating continuous delivery of real-time, analytics-ready data into AWS data warehouses or data lakes
• Making data easily accessible through a governed catalog on AWS
• Supercharging cloud analytics with SAP data on AWS
• Efficiently capturing large volumes of changed data from source SAP systems to AWS
• Delivering analytics-ready data in real-time to Amazon Web Services
• Automating SAP data warehouse and data lake pipelines on AWS
• Unlocking mainframe data for modern cloud uses on AWS
• Replicating very large volumes of mainframe data in real-time to AWS
• Expanding access to Mainframe data by automatically creating and updating a cloud data warehouse on AWS
• Enabling new insights and data science by combining mainframe data with other trusted sources on AWS
• Thriving in the era of value-based, data-driven care in healthcare
• Balancing better patient outcomes with a healthier bottom line in healthcare
• Enhancing patient outcomes and improving service delivery in healthcare
• Supporting HIPAA compliance requirements for US healthcare customers
• Improving patient outcomes with better clinical intelligence
• Targeting people most at-risk for health problems
• Tracking results of programs and operations in healthcare
• Viewing key data within EHR workflows
• Streamlining processes and reducing variation in healthcare
• Providing stakeholders with consistent information in healthcare
• Balancing the financial side of value-based care
• Reducing costs and optimizing payments in healthcare
• Speeding reimbursements and cutting down on claim rejections
• Making connections in data to cut waste, streamline processes, and improve care delivery
• Understanding the patient journey and its intersection with operational functions
• Streamlining patient pathways and boosting employee productivity

AI approach

Qlik integrates AI and machine learning capabilities across its data integration and analytics platforms. It offers an 'Agentic AI framework' for data integration and analytics, and provides AI-powered analytics, automated machine learning for model creation, GenAI-driven knowledge assistants, and predictive analytics. Qlik also has an AI Council to advise on AI developments and ethical AI practices, and has achieved ISO 42001 certification for AI Management System. They integrate third-party data science and generative AI models within Qlik applications and offer LLM extensibility.

Tech named: Agentic AI, Automated Machine Learning, Generative AI, LLM extensibility, Qlik Answers, Qlik Predict, Discovery Agent, Qlik Insight Advisor, Generative SQL Assistant

Industries served

• Software Development
• Financial Services
• Public Sector
• Government
• Education
• Healthcare
• Manufacturing
• Hospitality
• Retail
• Automotive

What it says sets it apart

• Agentic AI framework makes powerful data integration and AI-powered analytics platforms simple to use
• Faster Time to Value, Easier Adoption, Swift Insight to Action
• Leader in Gartner Magic Quadrant for Data Integration and Augmented Data Quality Solutions
• Used by 75% of the Fortune 500
• Works with existing systems and partners, avoiding lock-in
• Comprehensive data integration, quality, and governance in a single solution (Qlik Talend Cloud)
• Automated, governed, real-time data pipelines
• Qlik Talend Trust Score® to ensure data readiness for AI and analytics
• Ability to create data products for domain-specific business outcomes
• Low-code/no-code development platform for embedding analytics and AI
• SaaS flexibility, multi-tenant security, and governed self-service for scalability
• Extensive pre-built connectors and APIs for iPaaS
• Advanced security features including data encryption, access controls, and audit trails
• Compliance with FedRAMP Moderate Impact Level (IL) and DOD IL2 for government sector
• HIPAA compliance support for healthcare
• ISO 27001, ISO 27017, ISO 27018, ISO 42001 certifications
• AI Council to guide ethical AI practices and product direction
• Capacity-based pricing for predictable costs
• Agnostic platform supporting various data sources, cloud targets, and analytics platforms
• Real-time data delivery for immediate action
• Automated data warehouses and lakes
• Trusted, enterprise-ready data from ingestion through publishing
• Ability to analyze immense data volumes from disparate applications (e.g., e-commerce, transactional, back office)
• Unique LOB Solutions (Order to Cash, Financial Analytics, Inventory Analytics)
• Qlik & AWS QuickRamp for free POCs for SAP and mainframe data integration to AWS
• Integrated within EHR workflows (Cerner, Epic) for healthcare
• Strong focus on corporate responsibility, sustainability, and data literacy programs