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Analyzing data

Qlik Cloud Analytics offers industry-leading modern analytics capabilities across a full range of users and use cases — from self-service analytics to interactive dashboards and applications, conversational analytics, metadata catalog and lineage, mobile analytics, reporting and alerting.

It augments and enhances human intuition with AI (artificial intelligence) powered insight suggestions, automated machine learning, automation, and natural-language interaction.

Qlik Cloud Analytics is designed to promote human intuition and data literacy for users of all skill levels, allowing people to easily explore information and quickly gain trusted insights to solve problems – from the simple ones to the most complex.

  • Qlik Cloud Analytics is a collaborative environment for developing and sharing content. Shared and managed spaces provide intuitive and easy control over your app content.

  • A user interface with simple authoring tools that can help users of all levels create advanced charts and visualizations.

  • A fully conversational analytics experience native to Qlik CloudInsight Advisor—uses natural language processing to understand user intent and learns with each interaction to reveal associations, correlations, and trends within your data.

  • Qlik Cloud Analytics metadata catalog provides understanding and views into the datasets to which you have access. After determining which content best meets your needs, you can select datasets, tables, and fields from the catalog to load directly into your apps.

  • Quick detection of outliers and anomalies in your data with alerts.

  • Lineage and impact analysis help you to fully understand the data flowing through your data pipelines from source to analysis.

  • Qlik AutoML provides both machine learning experts and citizen data scientists a simple, code-free experience to generate models, make predictions, and test business scenarios.

Get started

Qlik Cloud Analytics activity centers

The Qlik Cloud Analytics activity centers, Insights and Analytics, are where you can create, share, and view analytic apps.

Understanding apps

Apps are task-specific applications that help you to understand and analyze data.

Tutorials for Qlik Sense

Get to know the Qlik Cloud Analytics environment and get started building apps and visualizations.

Using analytics to explore data

Exploring data with visualizations

When you make a selection when analyzing data, all associated visualizations update immediately to reflect that selection.

Exploring analyses with Insight Advisor

Learn how to use Insight Advisor to build and explore your own analyses.

Discovering your data with associative insights

Associative insights reveal relationships in your data and highlights interesting data for further exploration.

Creating analytics and visualizing data

Working with apps

Qlik Cloud apps are purpose-built applications created with data. App users explore data through visualizations that are selected and enhanced by app developers.

Working with sheets

Organize data visualizations for your app consumers in sheets. Create a logical flow by structuring your ideas and defining the purpose of your app..

Tutorial - Build an analytics app

Follow this tutorial to build a Qlik Cloud Analytics app by adding data, creating charts, and building a presentation.

Loading and modeling analytics data

Adding and managing your analytics data

Add data files and connections to your data sources to your spaces. You can then use them to add data in apps.

Understanding your data with catalog tools

Qlik Cloud Catalog provides access to critical business metadata, profile statistics, lineage, impact analysis, and tools for filtering and search.

Best practices for data modeling

There are a number of ways you can load your data into a Qlik Cloud Analytics app. The method you use depends on how the data is structured and the data model you want to achieve.

Machine learning with Qlik AutoML

Introducing automated machine learning

Qlik AutoML's simple code-free interface helps you create machine learning experiments to generate models and make predictions

Understanding machine learning

Learn about the practice of using mathematical algorithms to recognize patterns in data and then use those patterns to make predictions.

Tutorial – Generating and visualizing prediction data

Follow along with an example workflow involving model training and deployment, prediction generation, and using the data in data modeling and app building.

Collaborating with other users

Capturing and sharing insights using Notes

Create notes with snapshots of data to capture a personal narrative, and to collaborate with others.

Working in spaces

Learn how to use spaces to collaborate with other users and control access to content.

Granting access to sheets, sheet groups, bookmarks, and stories

Learn how to make content in an app available to other users.

Qlik Sense Mobile SaaS

Qlik Sense Mobile SaaS

Use the Qlik Sense Mobile SaaS app to access and consume analytics apps.

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