IBM Cloud Pak for Data Features
Statistical Tool (3)
Scripting
Supports a variety of scripting environments
Data Mining
Mines data from databases and prepares data for analysis
Algorithms
Applies statistical algorithms to selected data
Data Analysis (2)
Analysis
Analyzes both structured and unstructured data
Data Interaction
Interacts with data to prepare it for visualizations and models
Decision Making (4)
Modeling
Offers modeling capabilities
Data Visualizations
Creates data visualizations or graphs
Report Generation
Generates reports of data performance
Data Unification
Unifies information on a singular platform
Model Development (5)
Language Support
Supports programming languages such as Java, C, or Python. Supports front-end languages such as HTML, CSS, and JavaScript
Drag and Drop
Offers the ability for developers to drag and drop pieces of code or algorithms when building models
Pre-Built Algorithms
Provides users with pre-built algorithms for simpler model development
Model Training
Supplies large data sets for training individual models
Feature Engineering
Transforms raw data into features that better represent the underlying problem to the predictive models This feature was mentioned in 12 IBM Cloud Pak for Data reviews.
Machine/Deep Learning Services (6)
Computer Vision
Offers image recognition services
Natural Language Processing
Offers natural language processing services
Natural Language Generation
Offers natural language generation services
Artificial Neural Networks
Offers artificial neural networks for users
Natural Language Understanding
Offers natural language understanding services
Deep Learning
Provides deep learning capabilities
Deployment (3)
Managed Service
Manages the intelligent application for the user, reducing the need of infrastructure
Application
Allows users to insert machine learning into operating applications
Scalability
Provides easily scaled machine learning applications and infrastructure
Data Transformation (2)
Real-Time Analytics
Based on 27 IBM Cloud Pak for Data reviews and verified by the G2 Product R&D team. Facilitates analysis of high-volume, real-time data.
Data Querying
Based on 15 IBM Cloud Pak for Data reviews and verified by the G2 Product R&D team. Allows user to query data through query languages like SQL.
Connectivity (4)
Hadoop Integration
Based on 23 IBM Cloud Pak for Data reviews and verified by the G2 Product R&D team. Aligns processing and distribution workflows on top of Apache Hadoop
Spark Integration
Based on 22 IBM Cloud Pak for Data reviews and verified by the G2 Product R&D team. Aligns processing and distribution workflows on top of Apache Spark
Multi-Source Analysis
Based on 25 IBM Cloud Pak for Data reviews and verified by the G2 Product R&D team. Integrates data from multiple external databases.
Data Lake
Based on 24 IBM Cloud Pak for Data reviews and verified by the G2 Product R&D team. Facilitates the dissemination of collected big data throughout parallel computing clusters.
Operations (5)
Data Visualization
Based on 26 IBM Cloud Pak for Data reviews and verified by the G2 Product R&D team. Processes data and represents interpretations in a variety of graphic formats.
Data Workflow
Based on 25 IBM Cloud Pak for Data reviews and verified by the G2 Product R&D team. Strings together specific functions and datasets to automate analytics iterations.
Governed Discovery
Based on 23 IBM Cloud Pak for Data reviews and verified by the G2 Product R&D team. Isolates certain datasets and facilitates management of data access.
Embedded Analytics
Based on 24 IBM Cloud Pak for Data reviews and verified by the G2 Product R&D team. Allows big data tool to run and record data within external applications.
Notebooks
Based on 13 IBM Cloud Pak for Data reviews and verified by the G2 Product R&D team. Use notebooks for tasks such as creating dashboards with predefined, scheduled queries and visualizations
Customization (3)
Custom VMs
Allows users to create virtual machines to meet specific needs and optimize performance.
Console Configuration
Provides interface for building custom machines and analytics.
Operating Systems
Supports the necessary operating system and linux distributions for custom machines.
Infrastructure (5)
Network Management
Lets users provisionnetworks, deliver content, balance loads, and manage traffic.
Virtual Machines
Provides virtual networks and operating systems.
Security
Securesapplications, encrypt data, and manage identities.
Maintenance
Enables maintenance to existing virtual machines to improve functionality and security.
Scalability
Expands functionality while maintaining balanced loads. Serves growing demand without reducing functionality.
Management (8)
Cloud Migration
Allows transferring data and virtual machines during adoption and maintenance.
Storage Management
Provides management tools for data storage, database configuration, and scaling.
Analytics
Lets users analyze storage, performance, and connectivity.
Database Management
Supports for managing different types of databases and integration methods.
Logging
Captures information related to IP traffic and network usage.
Pay by Usage
Services are offered under a pay-as-you-go or utilization-based purchase model.
Usage Tracking
Track a business' IaaS usage statistics through dashboards, metrics, and reporting.
Performance Tracking
Track a business' IaaS performance statistics through dashboards, metrics, and reporting.
Infrastructure Provision (8)
Public Cloud
Provides public cloud capabilities.
Private Cloud
Provides private cloud capabilities.
Hybrid Cloud
Provides hybrid cloud capabilities.
Bare Metal
Provides bare metal servers.
High-Performance Computing (HPC)
Provides high-performance computing (HPC) capabilities.
Virtual Machines (VMs)
Provides virtual machines (VMs).
Edge Computing
Provides edge computing capabilities.
Virtual Networks
Provides virtual networking capabilities.
System (1)
Data Ingestion & Wrangling
Gives user ability to import a variety of data sources for immediate use This feature was mentioned in 11 IBM Cloud Pak for Data reviews.
Functionality (1)
Resource Auto-Scaling
Scales infrastructure resources automatically to meet capacity or computational demands
Data Management (4)
Data Integration
Consolidate data from various disparate sources in a single unified view
Data Discovery
Understand the state of data, applications, systems and services
Multi - Platform
Manage data across environments (on-premises cloud, hybrid, and multi-cloud)
Metadata
Provides metadata management and lineage capabilities
Analytics (1)
Data Analytics
Supports advanced analytics solutions for better business decision making
Security (3)
Compliance
Rules and regulations inherited from source systems or defined to secure sensitive data
Governance
Grant or restrict data access and control
Data Protection
Built - In Backup and Disaster Recovery
Generative AI (7)
AI Text Generation
Allows users to generate text based on a text prompt.
AI Text Summarization
Condenses long documents or text into a brief summary.
AI Text Generation
Allows users to generate text based on a text prompt.
AI Text Summarization
Condenses long documents or text into a brief summary.
AI Text Generation
Allows users to generate text based on a text prompt.
AI Text Summarization
Condenses long documents or text into a brief summary.
AI Text-to-Image
Provides the ability to generate images from a text prompt.
Scalability and Performance - Generative AI Infrastructure (3)
AI High Availability
Ensures that the service is reliable and available when needed, minimizing downtime and service interruptions.
AI Model Training Scalability
Allows the user to scale the training of models efficiently, making it easier to deal with larger datasets and more complex models.
AI Inference Speed
Provides the user the ability to get quick and low-latency responses during the inference stage, which is critical for real-time applications.
Cost and Efficiency - Generative AI Infrastructure (3)
AI Cost per API Call
Offers the user a transparent pricing model for API calls, enabling better budget planning and cost control.
AI Resource Allocation Flexibility
Provides the user the ability to allocate computational resources based on demand, making it cost-effective.
AI Energy Efficiency
Allows the user to minimize energy usage during both training and inference, which is becoming increasingly important for sustainable operations.
Integration and Extensibility - Generative AI Infrastructure (3)
AI Multi-cloud Support
Offers the user the flexibility to deploy across multiple cloud providers, reducing the risk of vendor lock-in.
AI Data Pipeline Integration
Provides the user the ability to seamlessly connect with various data sources and pipelines, simplifying data ingestion and pre-processing.
AI API Support and Flexibility
Allows the user to easily integrate the generative AI models into existing workflows and systems via APIs.
Security and Compliance - Generative AI Infrastructure (3)
AI GDPR and Regulatory Compliance
Helps the user maintain compliance with GDPR and other data protection regulations, which is crucial for businesses operating globally.
AI Role-based Access Control
Allows the user to set up access controls based on roles within the organization, enhancing security.
AI Data Encryption
Ensures that data is encrypted during transit and at rest, providing an additional layer of security.
Usability and Support - Generative AI Infrastructure (2)
AI Documentation Quality
Provides the user with comprehensive and clear documentation, aiding in quicker adoption and troubleshooting.
AI Community Activity
Allows the user to gauge the level of community support and third-party extensions available, which can be useful for problem-solving and extending functionality.
Agentic AI - Data Fabric (5)
Autonomous Task Execution
Capability to perform complex tasks without constant human input
Multi-step Planning
Ability to break down and plan multi-step processes
Cross-system Integration
Works across multiple software systems or databases
Adaptive Learning
Improves performance based on feedback and experience
Decision Making
Makes informed choices based on available data and objectives
Agentic AI - Data Science and Machine Learning Platforms (7)
Autonomous Task Execution
Capability to perform complex tasks without constant human input
Multi-step Planning
Ability to break down and plan multi-step processes
Cross-system Integration
Works across multiple software systems or databases
Adaptive Learning
Improves performance based on feedback and experience
Natural Language Interaction
Engages in human-like conversation for task delegation
Proactive Assistance
Anticipates needs and offers suggestions without prompting
Decision Making
Makes informed choices based on available data and objectives




