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What does it do?

  • Data Integration
  • Data Quality
  • Analytics
  • Real-Time Data Integration
  • Data Warehouse Automation
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How is it used?

  • Web app for real-time data integration and AI-powered analytics.
  • 1. Access web app
  • 2. Connect data sources
  • 3. Create interactive dashboards
  • 4. Leverage generative AI
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Who is it good for?

  • Data Analysts
  • Enterprise Decision Makers
  • Business Intelligence Professionals
  • IT Managers
  • Data Engineers

Details & Features

  • Made By

    QlikTech International
  • Released On

    1993-09-22

Qlik is a comprehensive data integration and analytics platform that empowers organizations to harness their data for informed decision-making and problem-solving. It offers a suite of tools designed to streamline data processes, from integration and quality management to advanced analytics and visualization.

Key features:
- Real-Time Data Integration: Provides change data capture streaming and data ingestion to improve data availability and agility while minimizing impact on production operations.
- Automated Transformation: Converts raw records into analytics-ready data using no-code data models and continuous refinement.
- Data Quality Management: Ensures enterprise-grade trusted data by discovering, remediating, and sharing data securely, offering a unified approach to data quality and governance.
- Data Warehouse Automation: Accelerates and simplifies the data warehouse lifecycle.
- Data Lakehouse Creation: Enables agile data lake creation.
- AI-Powered Analytics: Offers AI-driven insights, allowing users to explore data without coding or query knowledge.
- Self-Service Catalog: Provides a smart enterprise-scale data catalog for secure data sharing.
- Interactive Dashboards: Enables creation of highly interactive dashboards with fast controls.

How it works:
1. Users access Qlik through web and cloud-based platforms.
2. The platform connects to various data sources using its Data Ingestion Framework.
3. Database Replication Software copies and converts database objects and data into other formats.
4. Data Transport Architectures facilitate data movement.
5. Model-Driven Configuration Tools help design, build, and manage data lakes or warehouses.
6. The Enterprise-Scale Data Catalog offers on-demand access to analytics-ready data.
7. Users can then create interactive dashboards and leverage AI-powered analytics for insights.

Integrations:
AWS, Azure, Google Cloud, MySQL, MS SQL, MongoDB, Oracle, Salesforce, Workday, Zendesk, OpenAI, Databricks, SAP, Adobe, IBM, Jira, Apache, CircleCI, Snowflake

Use of AI:
Qlik leverages generative AI to enhance its analytics capabilities, providing AI-assisted insights and predictions. This approach makes analytics more accessible to users at all skill levels, enabling them to make informed decisions quickly.

AI foundation model:
The AI features are built on robust AI foundation models and large language models (LLMs), ensuring high-quality insights and predictions.

Target users:
- Data Professionals seeking robust data integration and analytics tools
- Business Analysts needing real-time insights and interactive dashboards
- IT Teams looking for scalable and flexible data solutions
- Enterprises requiring comprehensive data governance and quality management

How to access:
Qlik is available as a web app, cloud service, and API, making it versatile for various business needs. It is not open source but offers extensive support and resources for enterprise users.

Use Cases:
- Real-Time Data and Analytics: Used by companies like Domino's to improve efficiency, customer service, and sales
- Store Level Reporting: Urban Outfitters reduced reporting time from hours to minutes
- Company-Wide Portal: Intuit simplified analytics with a modern web experience
- Loan Prospect Conversion: Integra reduced costs and effort in converting loan prospects

  • Supported ecosystems
    iOS, Apple, Android, Google, AWS, Azure, Google Cloud, Google, OpenAI, AWS, Azure, Google Cloud, Google, OpenAI, Android, iOS, Microsoft, Android, Apple
  • What does it do?
    Data Integration, Data Quality, Analytics, Real-Time Data Integration, Data Warehouse Automation, Data Lakehouse Creation, AI-Powered Analytics, Interactive Dashboards, Real-Time Data and Analytics, Store Level Reporting
  • Who is it good for?
    Data Analysts, Enterprise Decision Makers, Business Intelligence Professionals, IT Managers, Data Engineers

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