(22)
4.8 out of 5
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Qlik AutoML
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Qlik AutoML Features
What are the features of Qlik AutoML?
Data Analysis
- Analysis
- Data Interaction
Decision Making
- Modeling
- Data Visualizations
- Report Generation
Model Development
- Drag and Drop
- Pre-Built Algorithms
- Model Training
- Pre-Built Algorithms
- Model Training
- Feature Engineering
Deployment
- Managed Service
- Application
- Scalability
- Managed Service
Qlik AutoML Categories on G2
Filter for Features
Statistical Tool
Scripting | Supports a variety of scripting environments This feature was mentioned in 19 Qlik AutoML reviews. | 75% (Based on 19 reviews) | |
Data Mining | Mines data from databases and prepares data for analysis 24 reviewers of Qlik AutoML have provided feedback on this feature. | 74% (Based on 24 reviews) | |
Algorithms | Applies statistical algorithms to selected data 25 reviewers of Qlik AutoML have provided feedback on this feature. | 81% (Based on 25 reviews) |
Data Analysis
Analysis | As reported in 30 Qlik AutoML reviews. Analyzes both structured and unstructured data | 79% (Based on 30 reviews) | |
Data Interaction | As reported in 30 Qlik AutoML reviews. Interacts with data to prepare it for visualizations and models | 83% (Based on 30 reviews) |
Decision Making
Modeling | Offers modeling capabilities This feature was mentioned in 28 Qlik AutoML reviews. | 87% (Based on 28 reviews) | |
Data Visualizations | Creates data visualizations or graphs This feature was mentioned in 29 Qlik AutoML reviews. | 83% (Based on 29 reviews) | |
Report Generation | Generates reports of data performance This feature was mentioned in 28 Qlik AutoML reviews. | 80% (Based on 28 reviews) | |
Data Unification | As reported in 25 Qlik AutoML reviews. Unifies information on a singular platform | 75% (Based on 25 reviews) |
Model Development
Drag and Drop | As reported in 27 Qlik AutoML reviews. Offers the ability for developers to drag and drop pieces of code or algorithms when building models | 85% (Based on 27 reviews) | |
Pre-Built Algorithms | As reported in 28 Qlik AutoML reviews. Provides users with pre-built algorithms for simpler model development | 87% (Based on 28 reviews) | |
Model Training | Based on 27 Qlik AutoML reviews. Supplies large data sets for training individual models | 85% (Based on 27 reviews) | |
Pre-Built Algorithms | As reported in 28 Qlik AutoML reviews. Provides users with pre-built algorithms for simpler model development | 86% (Based on 28 reviews) | |
Model Training | Based on 26 Qlik AutoML reviews. Supplies large data sets for training individual models | 84% (Based on 26 reviews) | |
Feature Engineering | As reported in 26 Qlik AutoML reviews. Transforms raw data into features that better represent the underlying problem to the predictive models | 82% (Based on 26 reviews) |
Machine/Deep Learning Services
Natural Language Processing | Offers natural language processing services 20 reviewers of Qlik AutoML have provided feedback on this feature. | 79% (Based on 20 reviews) | |
Natural Language Generation | Based on 10 Qlik AutoML reviews. Offers natural language generation services | 72% (Based on 10 reviews) | |
Natural Language Understanding | As reported in 17 Qlik AutoML reviews. Offers natural language understanding services | 76% (Based on 17 reviews) | |
Natural Language Generation | Offers natural language generation services This feature was mentioned in 10 Qlik AutoML reviews. | 77% (Based on 10 reviews) |
Deployment
Managed Service | Manages the intelligent application for the user, reducing the need of infrastructure 26 reviewers of Qlik AutoML have provided feedback on this feature. | 81% (Based on 26 reviews) | |
Application | Allows users to insert machine learning into operating applications 26 reviewers of Qlik AutoML have provided feedback on this feature. | 81% (Based on 26 reviews) | |
Scalability | Provides easily scaled machine learning applications and infrastructure 27 reviewers of Qlik AutoML have provided feedback on this feature. | 84% (Based on 27 reviews) | |
Managed Service | Manages the intelligent application for the user, reducing the need of infrastructure This feature was mentioned in 26 Qlik AutoML reviews. | 81% (Based on 26 reviews) | |
Application | As reported in 24 Qlik AutoML reviews. Allows users to insert machine learning into operating applications | 83% (Based on 24 reviews) | |
Scalability | Based on 24 Qlik AutoML reviews. Provides easily scaled machine learning applications and infrastructure | 83% (Based on 24 reviews) |
System
Data Ingestion & Wrangling | Based on 25 Qlik AutoML reviews. Gives user ability to import a variety of data sources for immediate use | 79% (Based on 25 reviews) | |
Drag and Drop | Offers the ability for developers to drag and drop pieces of code or algorithms when building models 24 reviewers of Qlik AutoML have provided feedback on this feature. | 82% (Based on 24 reviews) |
Generative AI
AI Text Generation | Allows users to generate text based on a text prompt. | Not enough data | |
AI Text Summarization | Condenses long documents or text into a brief summary. | Not enough data | |
AI Text Generation | Allows users to generate text based on a text prompt. | Not enough data | |
AI Text Summarization | Condenses long documents or text into a brief summary. | Not enough data | |
AI Text-to-Image | Provides the ability to generate images from a text prompt. | Not enough data |
Agentic AI - Data Science and Machine Learning Platforms
Autonomous Task Execution | Capability to perform complex tasks without constant human input | Not enough data | |
Multi-step Planning | Ability to break down and plan multi-step processes | Not enough data | |
Cross-system Integration | Works across multiple software systems or databases | Not enough data | |
Adaptive Learning | Improves performance based on feedback and experience | Not enough data | |
Natural Language Interaction | Engages in human-like conversation for task delegation | Not enough data | |
Proactive Assistance | Anticipates needs and offers suggestions without prompting | Not enough data | |
Decision Making | Makes informed choices based on available data and objectives | Not enough data |
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