Qlik Sense

Qlik Sense

Qlik Sense is a business intelligence and analytics platform that allows users to create interactive data visualizations and dashboards. It supports self-service data analytics with an intuitive drag-and-drop interface.
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Qlik Sense: Interactive Business Intelligence Platform

Qlik Sense is a business intelligence and analytics platform that allows users to create interactive data visualizations and dashboards. It supports self-service data analytics with an intuitive drag-and-drop interface.

What is Qlik Sense?

Qlik Sense is a business intelligence and analytics platform designed for modern, self-service oriented analytics. It allows users of all skill levels to easily create interactive data visualizations, dashboards, and applications to gain insights from multiple data sources.

Some key features of Qlik Sense include:

  • Associative data model and in-memory analytics engine for rapid analysis across all data
  • Drag-and-drop interface to support self-service analytics and data visualization without coding
  • responsive and fully interactive dashboards accessible across devices
  • Collaboration tools to share analytics apps with other users
  • Advanced analytical integration powered by AI and machine learning
  • Robust governance, security, and administration tools for the full analytics workflow

Qlik Sense enables a data literacy culture by allowing users of all skill sets to unlock value from data. Its self-service approach can lead to faster innovation and decision making based on data-driven insights. It handles large or complex datasets for deeper analysis with its in-memory architecture.

Qlik Sense Features

Features

  1. Drag-and-drop interface for data visualization
  2. Self-service analytics
  3. Interactive dashboards
  4. Data storytelling
  5. Mobile analytics
  6. Embedded analytics
  7. Geo-analytics
  8. Alerting

Pricing

  • Subscription-Based
  • Pay-As-You-Go

Pros

Intuitive and easy to use

Powerful data visualization capabilities

Real-time data analytics

Scalable to large data sets

Integrates well with other systems

Cons

Steep learning curve for advanced features

Limited forecasting and predictive analytics

Can be expensive for large deployments


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