IBM Watson Studio Features

Ensures privacy and security of customer data.

Visualizes text data through charts and graphs.

Receive data and information in real time

Interact with data visualization elements, such as charts and graphs, to drill down into data

Analyzes both structured and unstructured data

Interacts with data to prepare it for visualizations and models

Series of data points indexed in time order

Review data from past periods to reveal recurring tendencies and predict future performance

Permits profiling of data sets for increased organization, both by users and machine learning

Indexes metadata descriptions for easier searching and enhanced insights

Tools to (re)structure data in a manner that enables quick and accurate insight extraction

Allows self-service joining of tables

Provides the ability to combine data sources into one data set

Allows users and administrators to easily clean data to maintain quality and integrity

Offers collaborative functionality for sharing queries and data sets

Ensures user access management, data lineage, and data encryption

Offers natural language understanding services

Provides deep learning capabilities

Offers image recognition services

Offers natural language processing services

Offers artificial neural networks for users

Offers modeling capabilities

Creates data visualizations or graphs

Generates reports of data performance

Unifies information on a singular platform

Alter the layout and content of reports

Alter the layout and content of reports

Provides a channel for team members to share media files, communicate, and work together

Automatically retrieve and pull information from documents, websites, images, data sets, and other sources

Manage and store data in a database

Generate one-off reports that meet information requirements

View and track pertinent metrics to find patterns and gain insights from data

Predict future data based on historical data sets

Dashboard to view the status of ongoing processes, identify current incidents and track past activities

Define levels of authorization for access to specific files or systems

Interact with data visualization elements, such as charts and graphs, to drill down into data

Track the management and flow of data throughout the organization

Synchronizing data between two or more devices/systems and automatically updating changes to maintain consistency

Apply statistical/mathematical models to sets of data

Organize and group data or items based on various criteria

Review data from past periods to reveal recurring tendencies and predict future performance

Examines, analyzes, and organizes data to create relevant summaries or graphs.

Graphical representation of data

Application programming interface that allows for integration with other systems/databases

Allows users to manage data from a number of sources

Categorize emotions expressed in written text or images and identify if they are positive, negative or neutral

Search and filter data across systems to locate required information by entering keywords or certain criteria

Import and export data to and from software applications

Import, collect, and capture data from multiple sources

A virtual assistant that uses AI to pursue goals and complete tasks on behalf of users

Observe and track the demand, usage, progress or quality of a system, product, or user

Connect to big data sources

Transforming unstructured text into a structured format to identify meaningful patterns and new insights

Collection, analysis, and representation of numerical data and generation of reports to understand various patterns

Analyzing historical and current data and generating a model to help predict future outcomes.

Analyze and gain insights into data in real-time

Configure existing workflows to meet your organization's needs

Attach digital tags to documents and assets for identification, search, or monitoring purposes

Track status, assign actions, and control access to systems for devices within the organization

Drag and drop/visual interfaces that allow non-tech users to build without writing code

Transforming raw data to run it through machine learning algorithms to uncover insights or make predictions.

Examine established processes and records to ensure accuracy, compliance, and policy adherence

Examine large amounts of data to uncover hidden patterns, correlations, and other insights

Share, track, and store machine learning models and data.

Ability to handle large datasets

Track and document all activities across devices, networks, and other systems

Protect sensitive data for digital privacy

Create, design and manage workflows for repetitive tasks

Forecast customer demand using historical insights and simulations

Software program that continuously adjusts its behavior based on observed data

Assemble applications and processes by dragging over and arranging pre-built components

Software designed for the healthcare industry

Form predictions based on past and present data/trends

Automatically retrieve and pull information from documents, websites, images, data sets, and other sources

Set up connections to third-party platforms to improve business processes

Tools that provide relevant information at specific times to support judgments and courses of action

Using physical, mathematical, or logical models as a basis for simulations to generate data for managerial or technical decision-making

Alerts or notifications of various types such as pop-up messages, sounds, banners, or badges

View and track pertinent metrics to find patterns and gain insights from data

Allows users to manage data from a number of sources

For Retail Stores

Used for educational purposes

Discover and connect variety of data sources to the application for analysis

Create, design and modify the flow and processes of tasks in a project

A set of indicators that tracks the performance of networks, applications, systems, teams, etc.

Define and maintain business rules that determine workflow capabilities and criteria

A virtual assistant that uses AI to pursue goals and complete tasks on behalf of users

Process and analyze human language in text or audio form

Translate EDI formats into data suitable for use with company applications.

Clustering or grouping objects based on data similarities

Application programming interface that allows for integration with other systems/databases

Merge data from multiple sources to a single data set

Grouping log entries based on similar attributes.

Create, design and manage workflows for repetitive tasks

Streamlining repetitive tasks and activities through automated and predefined workflows

Observe and track the demand, usage, progress or quality of a system, product, or user

Track and document all activities across devices, networks, and other systems

Process of gathering, measuring, and analyzing accurate data

Define levels of authorization for access to specific files or systems

Predict future data based on historical data sets

Dashboard to view the status of ongoing processes, identify current incidents and track past activities

Analyze and gain insights into data in real-time

A virtual assistant that uses AI to pursue goals and complete tasks on behalf of users

Collection, analysis, and representation of numerical data and generation of reports to understand various patterns

Import and export data to and from software applications

Combining elements of both quantitative and qualitative data to conduct research

Track and analyze information regarding website visitors

Supports various file formats

Organize and group data or items based on various criteria

Manage and store data in a database

Collecting, analyzing, and utilizing feedback from users or customers to improve a product or service

Attach digital tags to documents and assets for identification, search, or monitoring purposes

Provides a channel for team members to share media files, communicate, and work together

Allow users to access multiple services after entering their login credentials once

Assemble applications and processes by dragging over and arranging pre-built components

Highlight content and/or make notations about parts of content

Add customized logos and colors to align with company branding

Processing and organizing collected information to a set of meaningful and cohesive categories for further analysis

Allows users to manage data from a number of sources

Application programming interface that allows for integration with other systems/databases

Search and filter data across systems to locate required information by entering keywords or certain criteria

Alter the layout and content of reports

Analyze survey results via statistical testing or crosstabs directly within the software

Software program that continuously adjusts its behavior based on observed data

Automatically retrieve and pull information from documents, websites, images, data sets, and other sources

View and track pertinent metrics to find patterns and gain insights from data

A virtual assistant that uses AI to pursue goals and complete tasks on behalf of users

Track the management and flow of data throughout the organization

Process of extracting, transforming, and loading data

Examine large amounts of data to uncover hidden patterns, correlations, and other insights

Establish guidelines about how much and what kind of data can be stored in the repository

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.

Allows users to generate text based on a text prompt.

Condenses long documents or text into a brief summary.

Use AI to generate content in the form of text, images, videos, etc.

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.

Use AI to generate content in the form of text, images, videos, etc.

Allows users to generate text based on a text prompt.

Use AI to generate content in the form of text, images, videos, etc.

Allows users to generate text based on a text prompt.

Condenses long documents or text into a brief summary.

Use AI to generate content in the form of text, images, videos, etc.

Allows users to generate text based on a text prompt.

Condenses long documents or text into a brief summary.

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.

Set up connections to third-party platforms to improve business processes

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

Set up connections to third-party platforms to improve business processes

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 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.

Manages the intelligent application for the user, reducing the need of infrastructure

Allows users to insert machine learning into operating applications

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.

Gives user ability to import a variety of data sources for immediate use

Receive data and information in real time

Supports a variety of scripting environments

Mines data from databases and prepares data for analysis

Applies statistical algorithms to selected data

Transforms raw data into features that better represent the underlying problem to the predictive models

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

Provides users with pre-built algorithms for simpler model development

Supplies large data sets for training individual models

Supports common databases such as MySQL and Oracle

Manage and support multiple languages

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.

Manage and support multiple languages

Review data from past periods to reveal recurring tendencies and predict future performance

Process of extracting and classifying information from text, such as tweets, emails, product reviews, etc

Apply statistical/mathematical models to sets of data

Analyze and gain insights into user experience

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 a wide range of possible integrations, including analytics, data integration, master data management, and data science tools

Allows businesses to easily integrate with analytics, data integration, master data management, and data science tools

Operationalizes data workflows to easily scale repeatable preparation needs

Provides a wide range of possible data connections, including cloud applications, on-premise databases, and big data distributions, among others

Allows businesses to easily connect to any data source

Offers API connections for cloud-based applications and data sources