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Qlik Sense for Insurance from Qlik
Delivers robust data integration, advanced analytics, interactive dashboards, and self-service BI to enhance claims, underwriting, regulatory reporting, and customer engagement in insurance.
Product analysis by function
Big Data Processing Frameworks for Business Intelligence and Analytics
Distributed computing environments that handle massive volumes of insurance data, including telematics, IoT sensor data, and external information sources.
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Data Ingestion and Integration
(12 Yes /12 Known /12 Possible features)
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Multi-source Data Support Ability to ingest and handle data from various sources (telematics, IoT devices, legacy systems, third-party providers). |
Qlik Sense supports data ingestion from a wide range of data sources including telematics, IoT, legacy systems, and third-party providers (see connectors and industry marketing on Qlik website). | |
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Streaming Data Ingestion Support for real-time/near real-time data input, e.g., from IoT sensors or telematics. |
Qlik's data streaming capabilities and connectors enable real-time or near-real-time ingestion, as described in product documentation. | |
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Batch Data Processing Support for scheduled or on-demand batch data loads. |
Qlik Sense supports batch data loads for analytics and scheduled updates, referenced in user/admin documentation. | |
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Schema Evolution Handling Framework's ability to accommodate changes in data structure over time. |
Schema evolution is supported via Qlik's data load editor and flexible associative engine, allowing ingestion of changing data structures. | |
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Data Deduplication Automated removal of duplicate records during ingestion. |
Data deduplication can be scripted using Qlik load scripts and transformation logic. | |
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Data Validation Checks for data quality and conformity to business rules upon ingestion. |
Qlik load scripts and built-in data profiling allow validation upon ingestion with data transformation and cleaning steps. | |
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Connectors and APIs Availability of pre-built connectors and APIs for popular insurance systems and data sources. |
Qlik provides many pre-built connectors and APIs to insurance/enterprise systems, as listed on their integration marketplace. | |
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Data Format Compatibility Support for a range of data formats (CSV, JSON, Parquet, Avro, XML, etc). |
Qlik supports a wide range of formats: CSV, JSON, XML, Excel, databases and others, as per product specs. | |
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Automated Metadata Extraction System can automatically recognize and record metadata for ingested datasets. |
Metadata extraction is part of Qlik's data catalog capabilities, automatically registering and describing ingested datasets. | |
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Change Data Capture (CDC) Identifies and processes only changed data since last run. |
Qlik's change data capture capabilities are available via specific connectors and the Qlik Data Integration platform. | |
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Data Lineage Tracking Tracks the flow and transformation of data from source to destination. |
Qlik lineage tracking features are available and visualized in Qlik Sense, especially with Qlik Catalog. | |
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Data Enrichment Ability to augment raw data with external or contextual information during or after ingestion. |
Qlik Sense supports data enrichment by joining contextual or third-party data during preparation or analysis. |
Distributed Processing Architecture
(8 Yes /8 Known /10 Possible features)
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Horizontal Scalability System can increase computing power seamlessly by adding nodes. |
Qlik Cloud and Qlik Sense scale horizontally through cloud deployment and elastic SaaS infrastructure. | |
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Elastic Resource Allocation Automatic provisioning or deprovisioning of resources based on workload. |
Qlik Cloud service automatically scales resources as workload demands change (elasticity feature in Qlik architecture). | |
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Fault Tolerance Built-in mechanisms to continue processing in case of node or task failure. |
Qlik architecture features redundancies and failure recovery measures, supporting fault tolerance. | |
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Cluster Management Tools Availability of native or integrated solutions for managing compute clusters. |
Qlik includes centralized management consoles and cluster/node management, especially in Qlik Sense Enterprise. | |
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Distributed Storage Support Integrates with distributed storage systems such as HDFS, S3, Google Cloud Storage, etc. |
Cloud and on-premise versions offer distributed storage support; integrates with S3, Azure Blob and others. | |
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Geographically Distributed Clusters Capability to manage and process data across data centers/regions. |
Qlik Cloud offers data residency and can process data across geographically distributed clusters. | |
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Resource Management Granularity Ability to allocate compute and memory at node, job, or task level. |
Resource management granularity is implemented via admin controls for apps, users, and spaces in Qlik management. | |
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High Availability (HA) Redundant components ensuring uptime in case of failures. |
Qlik provides high availability and failover, especially for enterprise deployments. | |
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Throughput Maximum data processing rate. |
No information available | |
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Latency Time taken from job submission to results in distributed environment. |
No information available |
Performance and Scalability
(7 Yes /7 Known /10 Possible features)
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Parallel Processing Support for simultaneous data processing using multiple threads/cores. |
Qlik’s associative engine makes extensive use of parallel processing for query and data loading performance. | |
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In-memory Computation Data and intermediate results can be stored in memory for faster processing. |
In-memory computation is a hallmark of Qlik’s architecture for ultra-fast analytics and ad hoc queries. | |
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Load Balancing Even distribution of work across all nodes in the cluster. |
Qlik handling of clusters and workloads ensures even distribution; load balancing described in Qlik Enterprise docs. | |
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Auto-scaling Automated increase/decrease of resources based on workload fluctuations. |
Qlik Cloud auto-scales up and down in response to user/workload demands. | |
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Performance Monitoring Real-time tracking of cluster and job-level metrics. |
Qlik provides real-time and historical performance monitoring at app and cluster levels via its admin console. | |
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Resource Utilization System's ability to maximize CPU, memory, and storage use while processing. |
Qlik’s associative engine optimizes for resource utilization (memory, cpu), maximizing performance. | |
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Job Throughput Number of jobs or queries processed per time period. |
No information available | |
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Maximum Data Volume The largest dataset size the framework can efficiently manage. |
No information available | |
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Concurrent User Support Number of users or processes that can submit jobs concurrently. |
undefined Qlik Sense supports many concurrent users, with performance scaling by tier (detailed in Qlik Sizing and Scalability docs). |
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Query Response Time Average time taken to return results for typical queries. |
No information available |
Data Storage and Management
(10 Yes /10 Known /10 Possible features)
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Support for Hybrid Storage Ability to leverage both local disk and cloud/object storage systems. |
Qlik supports local disk and cloud storage (e.g., AWS S3, Azure, Google) in Qlik Cloud and Enterprise. | |
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Data Partitioning Efficiently splits data into manageable and parallelizable chunks. |
Data partitions managed internally; Qlik manages and optimizes chunking for parallel load/processing. | |
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Compression Support for compressing data to save space and speed up processing. |
Compression options and optimized storage are available to reduce data footprint as described in Qlik docs. | |
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Data Retention Policies Configurable rules for automatically archiving or deleting old data. |
Admins can set document/data retention and archiving in Qlik platform. | |
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Tiered Storage Management Automatic movement of data across storage types based on usage or age. |
Tiered storage available; Qlik migrates inactive data to less expensive storage in Qlik SaaS. | |
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Metadata Catalog Centralized repository for storing and retrieving data schemas and attributes. |
Qlik Catalog or metadata repository functions provide a centralized schema and attribute registry. | |
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Transactional Consistency Support for ACID or eventual consistency as required. |
Qlik offers ACID transactional consistency for its repositories and supports data consistency as required. | |
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Backup and Restore Capabilities for regular data backups and disaster recovery. |
Backup and restore functionality is provided for both cloud and on-prem Qlik deployments. | |
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Role-based Access Control Granular permissions for data access and management. |
Role-based access control is a core Qlik Sense feature (granular permissions by user, group, and role). | |
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Immutable Data Storage Ability to store data in a non-modifiable state for compliance. |
Immutable data storage is available, supporting audit trails and compliance. |
Security and Compliance
(10 Yes /10 Known /10 Possible features)
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Data Encryption At Rest Encrypts stored data to prevent unauthorized access. |
Qlik encrypts data at rest in both SaaS and on-prem versions. | |
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Data Encryption In Transit Protects data using secure transmission protocols (e.g. TLS). |
Data in motion is encrypted via TLS and other protocols for secure transmission. | |
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User Authentication and Single Sign-On Supports centralized user authentication and SSO mechanisms. |
Centralized authentication and single sign-on (SSO) via SAML, OAuth or Active Directory supported. | |
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Granular Access Control Detailed permissions for datasets, jobs, and clusters. |
Qlik supports granular dataset/job/cluster permissions beyond role-based access. | |
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Audit Logging Comprehensive logs of user, job, and data access activity. |
Audit logs track user/job/data access across Qlik deployments. | |
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GDPR & Other Regulatory Compliance Assists in meeting regulations like HIPAA, GDPR, PCI DSS—especially important in insurance. |
Qlik Cloud and Enterprise have features to help meet regulatory requirements such as GDPR, HIPAA, etc. | |
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Tokenization and Masking Protects sensitive data fields such as PII. |
Data masking/tokenization of fields such as PII available in Qlik's data preparation tools. | |
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Multi-factor Authentication Extra security step for sensitive operations. |
Qlik supports multi-factor authentication out of the box for enhanced security. | |
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Data Access Auditing Detailed tracking of who accessed or queried what data and when. |
Comprehensive tracking of user access and data access events is supported (audit capabilities). | |
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Secure API Gateways Controls and monitors API access for data and system operations. |
API access is managed and secured via Qlik's API gateway and developer tools. |
Analytics and Machine Learning Support
(7 Yes /7 Known /10 Possible features)
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Built-in Analytics Libraries Out-of-the-box support for descriptive, diagnostic, and predictive analytics. |
Qlik Sense provides built-in libraries for descriptive and diagnostic analytics; third-party extensions support predictive analytics. | |
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Distributed Machine Learning Training Ability to process ML workloads over big, distributed datasets. |
No information available | |
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Model Versioning Track and manage multiple versions and iterations of analytic models. |
No information available | |
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Pipeline Orchestration Automate and schedule end-to-end data science workflows. |
Qlik Automation and Qlik Application Automation support pipeline orchestration. | |
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AutoML Capabilities Support for automatic machine learning to optimize model selection and parameters. |
No information available | |
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GPU Acceleration Leverage GPU resources for faster analytics/modeling. |
Qlik supports GPU acceleration on some advanced analytics or via integrations. | |
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Support for R/Python/Scala APIs Code analytic and ML logic using popular data science languages. |
Qlik supports R and Python APIs for embedding and executing scripts; partial support for Scala. | |
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Model Deployment at Scale Automated deployment and inference of trained models across production environments. |
Model deployment at scale is supported via Qlik automation and integration APIs. | |
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Integration with External ML Platforms Connectors or APIs for TensorFlow, PyTorch, H2O.ai, etc. |
Qlik integrates with external ML platforms such as TensorFlow, DataRobot, and others. | |
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Model Monitoring Continuously tracks model performance and drift in production. |
Qlik includes monitoring of embedded or integrated models (drift can be detected via analytics). |
Data Governance and Quality
(9 Yes /9 Known /10 Possible features)
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Data Cataloging Central source to register, discover, and search all datasets. |
Data catalog features available for dataset registration and discovery (Qlik Catalog). | |
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Data Lineage Visualization Visual tracking of data's journey, including transformations and usage. |
Qlik’s Data Lineage and Qlik Catalog allow visualization of transformation and data flow. | |
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Data Quality Monitoring Automatic scanning for inconsistencies, errors, and anomalies. |
Data quality rules and automatic monitoring are available in Qlik Catalog and data load editor. | |
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Policy-based Data Governance Rules that automate governance actions based on policies. |
Policy-based governance can be implemented in Qlik via admin controls and auditing. | |
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Data Stewardship Tools Interfaces and workflows for designated users to resolve or annotate data issues. |
No information available | |
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Data Profiling Automated generation of dataset statistics and summaries. |
Automated profiling with dataset statistics is part of Qlik’s data load process and Catalog. | |
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Custom Quality Rules Ability to define and enforce custom data validation checks. |
Qlik allows custom rules and expressions for validation and transformation. | |
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Master Data Management Integration Ensures accurate, consistent 'golden records' for all entities. |
Integration with master data management solutions possible via APIs or connectors. | |
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Data Masking and Redaction Built-in capabilities for masking sensitive data. |
Data masking/redaction tools available for PII and sensitive fields, through Qlik’s load scripts and catalog. | |
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Data Audit Trails Comprehensive records showing when and how datasets were modified. |
Audit trails for dataset modifications are maintained. |
Interoperability and Extensibility
(10 Yes /10 Known /10 Possible features)
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Open Source Ecosystem Support Ability to use and extend popular open source big data frameworks like Hadoop, Spark, Flink, etc. |
Qlik is interoperable with open source big data tools like Apache Spark (through connectors/APIs). | |
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RESTful API Availability Exposes standardized APIs for integration with other business services or systems. |
Qlik platform exposes standardized REST APIs for integration. | |
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Data Export Easily extract processed/analytic data to other systems or BI tools. |
Data export to external BI/analytics is natively supported. | |
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Plugin/Extension Architecture Framework allows custom modules, processors, or logic to be added. |
Qlik supports extension/plugin architecture, enabling custom logic to be added. | |
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Workflow Integration Connects with ETL/ELT and workflow orchestration tools (e.g., Airflow, NiFi). |
Integrates with workflow/orchestration tools (e.g., Qlik Application Automation, Airflow integration possible). | |
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BI & Visualization Integration Connect data output to BI tools like Tableau, Power BI, or Qlik. |
BI/visualization integration is central (Qlik Sense is a BI tool; also can connect to other BI tools via export or APIs). | |
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Custom Scripting Support Ability to create user-defined functions or scripts for processing tasks. |
Custom scripting is core to Qlik load scripts and expressions. | |
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Cross-platform Compatibility Runs across different operating systems and hardware. |
Qlik is cross-platform, supporting cloud, Windows, on-prem, and browser-based use. | |
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Multiple Language APIs Support for multiple programming languages (Java, Python, Scala, R). |
Qlik supports multiple language APIs (Python, R, JavaScript among others); SDKs available. | |
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SDKs and Developer Tools Resources and libraries for developers to build custom solutions. |
SDKs and developer tools provided. |
Deployment and Operations
(8 Yes /8 Known /10 Possible features)
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Cloud-native Deployment Optimized for AWS, Azure, GCP, and/or hybrid/multi-cloud operation. |
Qlik Cloud is a cloud-native deployment; also supports hybrid/multi-cloud. | |
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On-premises Deployment Can be installed and run within an enterprise data center. |
On-premises deployment supported by Qlik Sense Enterprise. | |
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Containerization Support for Docker/Kubernetes for portability and orchestration. |
Qlik Cloud leverages containerization and Kubernetes for deployment and orchestration. | |
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Rolling Upgrades Ability to update or patch the system without downtime. |
No information available | |
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Automated Provisioning Self-service or automated cluster setup and resource allocation. |
Self-service automation and provisioning features are available in Qlik Cloud. | |
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Monitoring & Alerting Centralized dashboards; notifications for infrastructure and job health. |
Qlik provides centralized monitoring and alerting through the management console. | |
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Self-healing Capabilities Automatic detection and remediation of node or service failures. |
No information available | |
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Disaster Recovery Automated failover, backup, and restoration processes. |
Disaster recovery measures (auto failover, backup/restore) described in Qlik architecture documents. | |
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Multi-tenancy Support Logical separation and resource isolation for different departments or teams. |
Supports multi-tenancy (separation by streams/spaces, user groups, etc). | |
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License/Subscription Management Built-in tools for managing product usage, licensing, and billing. |
Subscription and license management are included as a service in Qlik Cloud. |
Usability and User Experience
(10 Yes /10 Known /10 Possible features)
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Visual Workflow Design Drag-and-drop or graphical tools for building data pipelines and transformations. |
Visual drag-and-drop workflow design is central to Qlik Sense. | |
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Job Scheduling UI Easy interface for scheduling and managing batch/stream analytics jobs. |
Job scheduling and management UI is built into Qlik Cloud and Enterprise. | |
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Integrated Documentation Comprehensive, context-sensitive help inside the product. |
Integrated documentation, help pop-ups, and guided tours are present. | |
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Interactive Data Exploration Exploratory analysis tools for ad hoc queries and visualization. |
Interactive data exploration and visual discovery are core functions of Qlik Sense. | |
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Template Workflows A library of pre-built workflows and pipelines for common insurance analytics use cases. |
Pre-built template workflows and insurance use case solutions are available from Qlik. | |
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Customizable Dashboards Personalized dashboards for monitoring jobs, clusters, and data assets. |
Dashboards are fully customizable at user/group/role levels. | |
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Multi-language Support Localization and internationalization features for global teams. |
Multi-language localization is supported in Qlik Sense UI. | |
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Notebook Integration Support for Jupyter and other data science notebooks for collaborative analytics. |
Qlik integrates with Jupyter and supports other notebook interfaces. | |
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Role-based User Interfaces Tailored views and permissions based on user type (data engineer, analyst, admin, etc). |
Role-based UIs are configurable; different users have different views of the Qlik environment. | |
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Mobile Accessibility Access dashboards and reports from smartphones/tablets. |
Qlik Sense offers mobile accessibility through responsive web and native mobile apps. |
Cost Management and Optimization
(5 Yes /5 Known /10 Possible features)
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Cost Tracking and Reporting Detailed breakdowns of resource usage and costs by user, job, or department. |
Resource/cost tracking per user/job/team is available in Qlik Cloud; billing usage reports by department. | |
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Auto-termination of Idle Resources Releases unused or underutilized resources automatically to save costs. |
No information available | |
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Spot/Preemptible Instances Support Leverage lower-cost compute instances for non-critical workloads. |
No information available | |
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Budget Alerts Notifications when budgets approach or exceed defined limits. |
Budget and cost alerts are included in Qlik Cloud as part of subscription management. | |
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Usage Quotas Policies to limit maximum resource usage per job/user/project. |
Usage quotas can be configured in enterprise deployments (user/license limits, API limits). | |
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Resource Usage Forecasting Predicts future costs and resource needs based on job history. |
No information available | |
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Data Storage Tier Optimization Automatically moves rarely accessed data to lower-cost storage. |
Inactive data is automatically tiered/moved to lower cost storage in Qlik Cloud. | |
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Chargeback/Showback Reporting Generates reports to allocate technology costs to business units. |
Showback/chargeback reports available for cost allocation. | |
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Automated Scaling Policies User-defined policies to control scaling and associated costs. |
No information available | |
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Cost-aware Scheduling Optimizes job scheduling based on spot/discounted resource pricing. |
No information available |
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