IBM Watson Studio Features

As reported in 14 IBM Watson Studio reviews. Supports a variety of scripting environments

As reported in 15 IBM Watson Studio reviews. Mines data from databases and prepares data for analysis

Applies statistical algorithms to selected data This feature was mentioned in 15 IBM Watson Studio reviews.

Based on 15 IBM Watson Studio reviews. Analyzes both structured and unstructured data

Interacts with data to prepare it for visualizations and models This feature was mentioned in 14 IBM Watson Studio reviews.

As reported in 14 IBM Watson Studio reviews. Offers modeling capabilities

Based on 15 IBM Watson Studio reviews. Creates data visualizations or graphs

Based on 13 IBM Watson Studio reviews. Generates reports of data performance

Unifies information on a singular platform This feature was mentioned in 14 IBM Watson Studio reviews.

Based on 34 IBM Watson Studio reviews. Supports programming languages such as Java, C, or Python. Supports front-end languages such as HTML, CSS, and JavaScript

Offers the ability for developers to drag and drop pieces of code or algorithms when building models 35 reviewers of IBM Watson Studio have provided feedback on this feature.

Based on 36 IBM Watson Studio reviews. Provides users with pre-built algorithms for simpler model development

Supplies large data sets for training individual models 37 reviewers of IBM Watson Studio have provided feedback on this feature.

As reported in 13 IBM Watson Studio reviews. Transforms raw data into features that better represent the underlying problem to the predictive models

Offers image recognition services 28 reviewers of IBM Watson Studio have provided feedback on this feature.

Offers natural language processing services This feature was mentioned in 35 IBM Watson Studio reviews.

Based on 28 IBM Watson Studio reviews. Offers artificial neural networks for users

Based on 12 IBM Watson Studio reviews. Offers natural language understanding services

As reported in 12 IBM Watson Studio reviews. Provides deep learning capabilities

Manages the intelligent application for the user, reducing the need of infrastructure This feature was mentioned in 32 IBM Watson Studio reviews.

Allows users to insert machine learning into operating applications This feature was mentioned in 33 IBM Watson Studio reviews.

Based on 31 IBM Watson Studio reviews. Provides easily scaled machine learning applications and infrastructure

Allows users to input models built in a variety of languages.

Allows users to choose the framework or workbench of their preference.

Records versioning as models are iterated upon.

Provides a way to quickly and efficiently deploy machine learning models.

Offers a way to scale the use of machine learning models across an enterprise.

Allows users to input models built in a variety of languages.

Allows users to choose the framework or workbench of their preference.

Records versioning as models are iterated upon.

Provides a way to quickly and efficiently deploy machine learning models.

Offers a way to scale the use of machine learning models across an enterprise.

Provides a wide range of possible data connections, including cloud applications, on-premise databases, and big data distributions, among others 13 reviewers of IBM Watson Studio have provided feedback on this feature.

As reported in 12 IBM Watson Studio reviews. Allows businesses to easily connect to any data source

Based on 14 IBM Watson Studio reviews. Offers API connections for cloud-based applications and data sources

Permits profiling of data sets for increased organization, both by users and machine learning This feature was mentioned in 14 IBM Watson Studio reviews.

As reported in 12 IBM Watson Studio reviews. Indexes metadata descriptions for easier searching and enhanced insights

As reported in 12 IBM Watson Studio reviews. Tools to (re)structure data in a manner that enables quick and accurate insight extraction

As reported in 13 IBM Watson Studio reviews. Allows self-service joining of tables

As reported in 12 IBM Watson Studio reviews. Provides the ability to combine data sources into one data set

Allows users and administrators to easily clean data to maintain quality and integrity 13 reviewers of IBM Watson Studio have provided feedback on this feature.

Based on 13 IBM Watson Studio reviews. Offers collaborative functionality for sharing queries and data sets

Ensures user access management, data lineage, and data encryption 12 reviewers of IBM Watson Studio have provided feedback on this feature.

Provides a wide range of possible integrations, including analytics, data integration, master data management, and data science tools This feature was mentioned in 12 IBM Watson Studio reviews.

Based on 12 IBM Watson Studio reviews. Allows businesses to easily integrate with analytics, data integration, master data management, and data science tools

Based on 12 IBM Watson Studio reviews. Operationalizes data workflows to easily scale repeatable preparation needs

Records and organizes all machine learning models that have been deployed across the business.

Tracks the performance and accuracy of machine learning models.

Provisions users based on authorization to both deploy and iterate upon machine learning models.

Allows users to manage model artifacts and tracks which models are deployed in production.

Records and organizes all machine learning models that have been deployed across the business.

Tracks the performance and accuracy of machine learning models.

Provisions users based on authorization to both deploy and iterate upon machine learning models.

Gives user ability to import a variety of data sources for immediate use 13 reviewers of IBM Watson Studio have provided feedback on this feature.

Control model usage and performance in production

Deploy mission-critical ML applications where and when you need them

Easily compare experiments—code, hyperparameters, metrics, predictions, dependencies, system metrics, and more—to understand differences in model performance.

Provides the ability to import data from a variety of sources and in multiple data formats.

Consistently maintains, updates, and tests data sources to ensure quality.

Allows users to analyze data easily without the need to code.

Ensures privacy and security of customer data.

Visualizes text data through charts and graphs.

Automates back-end technical manual processes.

Identifies entities such as organization, person name, location, etc

Extracts keyphrases to determine patterns and themes within text.

Automatically identifies and organizes text based on topic or subject matter.

Utilizes sentiment analysis to capture user feedback.

Identifies the language in which text was written in.

Provides the ability to identify syntax and parts of speech.

Allow capabilities to be customized (key-phrase, topics, sentiment, named entity) by adding keywords or exceptions.

Allow user to add custom functions to Analysis capabilities

User created models can be used as features/pre-built in other models

Allows users to generate text based on a text prompt.

Condenses long documents or text into a brief summary.

Allows users to generate text based on a text prompt.

Condenses long documents or text into a brief summary.

Allows users to generate text based on a text prompt.

Condenses long documents or text into a brief summary.

Allows users to generate text based on a text prompt.

Allows users to generate text based on a text prompt.

Condenses long documents or text into a brief summary.

Provides the ability to generate images from a text prompt.

Capability to perform complex tasks without constant human input

Ability to break down and plan multi-step processes

Works across multiple software systems or databases

Improves performance based on feedback and experience

Engages in human-like conversation for task delegation

Anticipates needs and offers suggestions without prompting

Makes informed choices based on available data and objectives